Forest Disturbances in a Changing Climate

(click to download a formatted pdf of this complete article or a one-page synopsis)

By Jennifer Hushaw

Disturbance shapes the character and composition of ecosystems and it is “a pervasive feature of forests” (Perry 1994). Wildfires, blowdowns, pests and other disturbance agents affect the spatial patterns of vegetation and ecosystem processes, creating a diversity of conditions across the landscape, and they can leave an imprint that shapes forest dynamics for decades to centuries after the initial disturbance event (Turner 2010).

There is an increasing amount of research on forest disturbance in a changing climate, including a number of studies that suggest certain types of disturbance (e.g., wildfire or insect outbreaks) are increasing over time (as noted in previous bulletins). In a recent review in the journal Nature Climate Change, researchers noted that increases in the occurrence and severity of forest disturbance have been documented worldwide and they provide a comprehensive analysis of these changing dynamics by elucidating global trends from hundreds of separate studies (Seidl et al., 2017).


Researchers synthesized results from over 670 studies (published from 1990 to the present) that assessed how forest disturbance changed in response to a change in climate, focusing on six disturbance agents (fire, drought, wind, snow and ice, insects, and pathogens). From these results, they isolated over 1,600 observations for further analysis.

For each type of disturbance, they looked at the evidence for direct, indirect, and interaction effects of climate change. They determined whether climate change had a predominantly amplifying or dampening effect on disturbance, as well as the relative size of that effect. This allowed them to assess the degree of climate sensitivity. In particular, they examined whether disturbance was likely to increase or decrease under either (1) warmer and wetter or (2) warmer and drier conditions.

Note: The disturbance agents included in this study have been discussed in previous CSLN bulletins, including wildfire (Part I & Part II), drought (here & here), wind, snow and ice (Part I & Part II), and pests/pathogens. Refer to those publications for a more in-depth discussion of climate change effects.  


Climate Shapes Disturbance Regimes

  • Climate has a “substantial influence” on forest disturbance – direct effects were most common (~57% of observations), followed by indirect (25%) and interaction (~18%) effects.
  • Temperature had a greater influence on disturbance at higher latitudes (most important in boreal regions), while water availability was more influential at lower latitudes (most important in the tropics).
  • Interaction between agents tended to increase disturbance – posing an increased risk of crossing ecological tipping points.
    • “In particular, disturbances by drought and wind strongly facilitate the activity of other disturbance agents, such as insects and fire […].”
  • Indirect climate effects commonly had a dampening influence by reducing ecosystem vulnerability to disturbance over the long-term,
    • g. a climate-mediated shift toward more drought tolerant tree species reduces potential for drought-induced forest mortality.
  • It can take years to centuries for the disturbance regime to respond to the change in climate.
    • Interaction effects resulted in the fastest response time (< 6 years in 81% of cases),
      • g. drought weakens tree defenses, leading to an increased risk of bark beetle outbreak within a few years.
    • Indirect effects resulted in the slowest response time (> 25 years in ~45% of cases),
      • g. a forested area becomes progressively drier over time, leading to self-thinning and a reduction in stand density (after many decades), which reduces risk of wildfire.

Forest Disturbance Will Likely Increase in the Future

  • Recently documented increases in disturbance are “likely to continue in the coming decades as climate warms further.”
    • Studies indicate disturbance activity will increase in all biomes and more for conifer forests than broadleaved and mixed forest types.
  • Overall, disturbances from fire, drought, wind, insects, and pathogens are likely to increase, while disturbances from snow and ice are likely to decrease.
    • Fire, insects, and pathogens will increase “regardless of changes in water availability.”
    • Drought, wind, and snow will be “strongly contingent on changes in water availability.”
  • Under warmer and drier conditions, most studies show:
    • ↑ fire
    • ↑ drought
    • ↑ insect activity
  • Under warmer and wetter conditions, most studies show:
    • ↑ wind disturbance
    • ↑ pathogen disturbance


  • Longer term effects of climate change on disturbance regimes may be underestimated because the analysis is limited by the length of the observational period used in the original studies.
  • The predominance of direct climate effects may be partially due to the fact that they are easier to detect and measure than indirect or interaction effects.
  • The majority of observations they analyzed were from ecosystems in North America and Europe, making it unclear whether some of the observed trends (e.g. greater impacts on disturbance in boreal regions) are due to the degree of climate change and ecosystem characteristics or (at least partially) the result of publication bias.
  • The scientific literature focused more on fire, drought, insects, and pathogens than the other disturbance agents.
  • Invasive alien pests were not considered in their analysis, but will likely play a part in future disturbance change.

Things to Do

Forest management can ameliorate negative impacts from increasing disturbance, by actively promoting the characteristics of resilient forests, and shifting species composition, stand density, and other features in a way that reduces vulnerability to disturbance and ensures that when disturbance (inevitably) happens the damage is minimized.


Addressing changes in forest disturbance is an important part of climate change adaptation. In fact, “Plan for and respond to disturbance” is one of the ten major adaptation strategies proposed by the USDA Forest Service in Forest Adaptation Resources: Climate Change Tools and Approaches for Land Managers. The approaches they suggest include:

  • Prepare for more frequent and more severe disturbances
  • Prepare to realign management of significantly altered ecosystems to meet expected future environmental conditions
  • Promptly revegetate sites after disturbance
  • Allow for areas of natural regeneration after disturbance
  • Maintain seed or nursery stock of desired species for use following severe disturbance
  • Remove or prevent establishment of invasives and other competitors following disturbance (Butler et al., 2012)

In previous bulletins we have discussed various management actions that can be taken to reduce the effects of specific types of disturbance. For example…



In addition to active management that reduces the likelihood, severity, or extent of forest disturbance, it will be increasingly important to monitor changes in disturbance regimes such as those outlined in the Seidl et al. (2017) study. We are addressing this need through the Resiliency Assessment Framework, which is currently under development. The major categories of monitoring information that will be collected are related to forests, climate, disturbance, and operations. Potential research questions and example monitoring metrics for disturbance agents are listed below:

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Butler, P.R., Swanston, C.W., Janowiak, M.K., Parker, L.R., St. Pierre, M.J., Brandt, L.A. 2012. Adaptation Strategies and Approaches. In: C.W. Swanton and M.K. Janowiak, editors. Forest Adaptation Resources; Climate change tools and approaches for land managers. Gen. Tech. Rep. NRS-87. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, p. 15-34.

Perry, D.A. 1994. “Disturbance in Forest Ecosystems.” In: Forest Ecosystems, p. 127. Baltimore, Maryland: Johns Hopkins University Press.

Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M., Vacchiano, G., Wild, J., Ascoli, D., Petr, M., Honkaniemi, J., Lexer, M.J., Trotsiuk, V., Mairota, P., Svoboda, M., Fabrika, M., Nagel, T.A., Reyer, C.P.O. 2017. Forest disturbances under climate change. Nature Climate Change. 7: 395-402.

Turner, M.G. 2010. Disturbance and landscape dynamics in a changing world. Ecology. 91(10): 2833–2849.

New Evidence of Tree Species on the Move

(click to download a pdf of this complete article or download a one-page synopsis)

By Jennifer Hushaw

There has been significant debate and research about where, how quickly, and to what degree our forests will shift with the changing climate. These questions have primarily been tackled through modeling (e.g., see Modeling Future Forests bulletin) or studying plant response in the distant past through paleoecology. Quite a bit of uncertainty remains because we do not have complete information about the physiological limits, tolerances, and life history traits of all species, or a good understanding of how changes in relative competiveness will play out (Corlett & Westcott 2013). The paleo record offers us a few examples of vegetation response to abrupt climatic change, but we are generally limited to episodes that were far more gradual than the relatively rapid warming we see today (Williams & Burke in press). There is also the confounding factor of human influence on the landscape, via land use, forest management, wildlife management, introduction of new species, and so on.

Given this uncertainty, researchers have used recent observational data to detect early signs of tree species migration and ecosystem shifts. The results have been mixed, as to whether large-scale shifts are underway and whether they are due to climate change. In this bulletin, we highlight a noteworthy new study in the eastern U.S. that shows evidence of significant changes in abundance for a number of tree species. We look at how these results compare with previous research, highlight some overarching themes, and conclude with action items for managers.

New Evidence of Tree Species Shifts  

A recently published study by Fei et al (2017), entitled Divergence of species responses to climate change, found “prominent westward and poleward shift in abundance for most tree species in the eastern United States during the last 30 years.” The study provides evidence that eastern tree species are responding to recent changes in climate, and the details of their findings highlight the individual responses of different species groups.


Researchers used tree abundance data from the U.S. Forest Inventory & Analysis (FIA) program for 86 species/groups in the eastern U.S. They looked at shifts in abundance between two inventory periods: 1980-1995 (depending on the state) and 2015 (the most recent completed year)—with an average window of about 30 years. They analyzed the relationship between observed species shifts and climate (specifically, mean annual temperature (MAT), total annual precipitation (TAP), and Palmer Drought Severity Index (PDSI)), as well as forest succession status. They also looked at whether there were differences in species response depending on functional traits (drought tolerance, wood density, and seed weight) or evolutionary lineage.

  • Distinct spatial patterns
    • 73% of species shifted their abundance centers westward *
    • 62% of species shifted their abundance centers poleward **
    • Shifts were primarily due to changes in subpopulations at the leading edges
    • There were regional differences in the primary direction of abundance shifts:
      • Northern Hardwood = poleward
      • Central Hardwood = westward
      • Southern Pine-Hardwood = westward
      • Forest-Prairie Transition = westward
    • Sapling abundance shifted in higher proportions (and farther) than adult tree abundance
    • Longitudinal shift was 1.4 times faster than latitudinal
    • Observed a poleward shift rate of 11.0 km per decade, similar to estimates from previous studies
  • Influence of climate and succession
    • Changes in abundance were more strongly related to moisture (precipitation and drought index) than temperature
      • “…changes in mean annual precipitation alone explained about 19% of the variability in species abundance change and spatial shift.”
    • Early successional forests had more gains in abundance than forests in late successional stages
  • Different shifts depending on traits and evolutionary lineage
    • Influence of physiological tolerance and dispersal ability
      • Generally, species that shifted westward had larger seed size and higher wood density than species that shifted eastward
      • Species with medium to high drought tolerance shifted westward at a faster rate than those with low drought tolerance
      • Species that shifted northward were associated with lower annual precipitation and lower wood density than southward shifting species
      • Wind-pollinated species primarily shifted northward, while animal-pollinated shifted southward ****
    • Influence of phylogeny (evolutionary lineage)
      • 5% of angiosperms (hardwoods/flowering plants) shifted westward ***
      • 4% of gymnosperms (softwoods/non-flowering plants) shifted northward, along with all poplar and most birch species
* 65% of these were statistically significant

** 55% of these were statistically significant

*** 52.3% of these were statistically significant

**** Similar northward shifts occurred in New England 10–8K years ago (during the early Holocene)


The results of this study suggest some interesting implications for tree species migration in the eastern U.S., including the following highlights from the discussion section:

  • Vegetation dynamics appear to be a more sensitive to moisture than temperature, at least in the near-term.
  • While the western portion of the study area is drier than the east, it experienced an increase in total annual precipitation over the study period, suggesting that drought tolerant species shifted westward because they could more readily take advantage of the increased moisture.
  • Poleward shifts were more prominent at higher latitudes, where the greatest warming has taken place to date.
  • The stronger trend observed for saplings supports the idea that saplings will respond more quickly to climatic change and exhibit greater sensitivity to drought than adults.
  • Results support the idea that initial changes will be most prominent at species range margins, particularly the leading edge.
  • Gymnosperms have less efficient water transport systems that lead to lower maximum growth rates (compared with angiosperms), so their primarily northward shift may be due to a lack of competitiveness in the drier western region of the study area.
  • Seed size may be an important factor because it is linked to different colonization, tolerance, and competitive strategies used by different species.
  • Higher wood density is often associated with greater survival, which may explain the preferential shift of high wood density species into the droughty (southern) and relatively dry (western) portions of the study area.
  • Non-climatic factors also played a role, including successional processes, forest densification related to fire suppression, and (potentially) infestations (of pests, plants, and pathogens), forest conservation, and plantation efforts.

Previous Research

Numerous studies have documented species range shifts that are consistent with what we would expect in a warming world, namely upward shifts in elevation and latitude, for plants and many other types of organisms (Root et al 2003; Parmesan & Yohe 2003; Parmesan 2006; Chen et al 2011). For tree species, in particular, these types of elevational or poleward shifts have been previously documented in temperate (Lenoir et al 2008; Beckage et al 2008; Woodall et al 2009; Wright et al 2016), boreal (Soja et al 2007), and even tropical (Feeley et al 2011) biomes.

Although, the studies that have detected changes (including Fei et al 2017) show discernible shifts for only some fraction of species. Not all tree species are responding (yet), and some are responding in ways we might not expect, including instances of downhill shifts (Crimmins et al 2011) and the expansion of some species into more southerly areas (Woodall et al 2009). This is due to the complex array of factors that influence where and how tree species will grow, and researchers have cited a number of these to explain the apparent lack of movement or counterintuitive shifts among some species, including competition from established species, changes in moisture availability, adaptation, and so on.

In some cases, we also see contradictory results. For example, a 2012 study by Zhu and colleagues examined FIA data for over 90 species in the eastern U.S. and they found that only ~20% of species showed a pattern of northward shift (with close to 60% exhibiting evidence of range contraction) and no apparent relationship between these observed patterns and seed size, dispersal characteristics, or degree of climate change, which is in contrast to the findings of Fei et al (2017). However, the two studies used different methodologies, which may explain the difference. In fact, the issue of methodology has been pointed to as a partial explanation for the lack of evidence of species shifts to date. Shifts may be happening that our methods can’t sufficiently detect because of challenges with accurately identifying species range margins and data availability across entire species’ distributions (Jump et al 2009).

In fact, previous studies have used a variety of a different approaches to determine whether species are on the move, including comparing the average latitude of tree biomass with the average latitude of seedlings for a given species (Woodall et al 2009), comparing the 5th and 95th percentile latitudes for seedlings and trees (Zhu et al 2012), assessing change in the average elevation of recruitment over time (Wright et al 2016), and others. Fei et al (2017) is different from many preceding studies in using abundance data throughout the species range, rather than focusing solely on range margins for detecting changes.

Take Homes

Despite the inherent uncertainty in forecasting future forests, current scientific understanding suggests some general rules-of-thumb regarding tree species shifts, such as:

  • Tree species will respond independently, not as cohesive forest types
  • Significant time lags are likely
  • There is potential for faster change with mortality from extreme events
  • Changing moisture availability will likely be more important than changing temperature for driving species shifts in the near-term
  • Most species will experience climate conditions that are novel for that species (in some portion of their range)
  • Look for initial forest composition changes at range margins
  • Look for initial changes in regeneration, rather than the overstory
  • Uncertainty is not if tree distributions and abundance will shift, but exactly where and when
  • Generally, we expect…
    • Range expansion at the leading edge (northern and higher elevations)
    • Range contraction at the trailing edge (southern and low-altitudinal limits)

The Fei et al (2017) study supports many of these and also provides a useful illustration of how to think about these types of changes. This is often framed as a question of whether a particular species will disappear from the landscape in the next 50 to 100 years (e.g. Will all the sugar maple disappear from New England?), but the more relevant question(s) should be things like:

  • Will the species become more or less prevalent (in terms of relative abundance)?
  • How will changes in relative competitiveness manifest?
  • Will the species experience growth declines due to less optimal climate conditions and/or a reduced capacity to fend off threats, such as insect infestation?
  • Is the overall species range likely to shift, contract, or expand in the long-term?

Things to Do

Two important things managers can do are (1) monitor and (2) promote regeneration. Monitoring includes watching for changes in the forests you manage (e.g. changes in moisture availability or in regeneration success, relative abundance, and/or competitiveness among species) and keeping an eye on the results of large-scale studies like the new research highlighted here. This is especially important in light of the distinct regional differences observed by Fei and colleagues. This will also be an important component of the Resiliency Assessment Framework that is currently under development, which is designed to provide informative metrics for detecting the impacts of climate change on North American forests.

Regeneration is the phase when species have the best opportunity to express adaptation to new climate conditions through phenotypic plasticity and it is the mechanism of species migration, so promoting regeneration can be the first step in moving a forest stand toward a condition/composition that may be more resilient in the face of changing climate conditions.


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Beckage, B., Osborne, B., Gavin, D.G., Pucko, C., Siccama, T., Perkins, T. 2008. A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont. PNAS. 105(11): 4197-4202.

Chen, I-C., Hill, J.K., Ohlemüller, R., Roy, D.B., Thomas, C.D. 2011. Rapid Range Shifts of Species Associated with High Levels of Climate Warming. Science. 333: 1024-1026.

Corlett, R.T., Westcott, D.A. 2013. Will plant movements keep up with climate change? Trends in Ecology & Evolution. 28(8): 482–488.

Crimmins, S.M., Dobrowski, S.Z., Greenberg, J.A., Abatzoglou, J.T., Mynsberge, A.R. 2011. Changes in Climatic Water Balance Drive Downhill Shifts in Plant Species’ Optimum Elevations. Science. 331(6015): 324-327.

Feeley, K.J., Silman, M.R>, Bush, M.B., Farfan-Rios, W., Cabrera, K.G., Malhi, Y., Meir, P., Salinas, N., Raurau-quisiyupanqui, M.N., Saatchi, S. 2011. Upslope migration of Andean trees. Journal of Biogeography. 38(4): 783-791.

Fei, S., Desprez, J.M., Potter, K.M., Jo, I., Knott, J.A., Oswalt, C.M. 2017. Divergence of species responses to climate change. Science Advances. 3: e1603055.

Jump, A.S., Mátyás, C., Peñuelas, J. 2009. The altitude-for-latitude disparity in the range retractions of woody species. Trends in Ecology & Evolution. 24(12): 694-701.

Lenoir, J., Gégout, J.C., Marquet, P.A., de Ruffray, P., Brisse, H. 2008. A Significant Upward Shift in Plant Species Optimum Elevation During the 20th Century. Science. 320: 1768-1771.

Parmesan, C. 2006. Ecological and Evolutionary Responses to Recent Climate Change. Annu. Rev. Ecol. Evol. Syst. 37: 637-669.

Parmesan, C., Yohe, G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 421: 37-42.

Root, T.L., Price, J.T., Hall, K.R., Schneider, S.H., Rosenzweig, C., Pounds, J.A. 2003. Fingerprints of global warming on wild animals and plants. Nature. 421: 57-60.

Soja, A.J., Tchebakova, N.M., French, N.H.F., Flannigan, M.D., Shugart, H.H., Stocks, B.J., Sukhinin, A.I., Parfenova, E.I., Chapin III, F.S., Stackhouse Jr., P.W. 2007. Climate-induced Boreal Forest Change: Predictions versus Current Observations. Global and Planetary Change. 56(3-4): 274-296.

Williams, J.W. & Burke, K. (in press). Past abrupt changes in climate and terrestrial ecosystems. In Climate Change and Biodiversity (eds T. Lovejoy & L. Hannah)

Woodall, C.W., Oswalt, C.M., Westfall, J.A., Perry, C.H., Nelson, M.D., Finley, A.O. 2009. An indicator of tree migration in forests of the eastern United States. Forest Ecology and Management. 257: 1434-1444.

Wright, D.H., Nguyen, C.V., Anderson, S. 2016. Upward shifts in recruitment of high-elevation tree species in the northern Sierra Nevada, California. California Fish and Game. 102(1):17-31.

Zhu, K., Woodall, C.W., Clark, J.S. 2012. Failure to migrate: lack of tree range expansion in response to climate change. Global Change Biology. 18: 1042-1052.

Shifting Phenology in a Changing Climate

(click here to download a pdf of this full article or a one-page synopsis)

By Jennifer Hushaw

Phenology is the study of the seasonal rhythms of plants and animals, especially the timing of natural cycles as related to weather and climate. It is a sensitive indicator of climate change, with far reaching implications for ecosystem processes, productivity, and even the global carbon budget.

In previous bulletins, we discussed how phenology is expected to shift due to a warming climate, leading to a whole host of direct and downstream impacts. In this bulletin, we delve into more detail and reveal how phenology of boreal and temperate trees, in particular, has already shifted and is likely to continue changing, as well as the potential ramifications for forestry. We also discuss some of the major questions that still remain to be answered, such as which species are most well-suited to track warming trends and maintain optimal phenology in the future.



Phenology is sometimes described as “the pulse of the planet” because of the way it mediates seasonal and annual processes related to carbon, water, and nutrient cycling. By controlling the timing and extent of leaf area, flowering, leaf fall and other developments, phenology directly influences productivity, growth, evapotranspiration, runoff, decomposition, and mineralization (Richardson et al. 2013). It is also relevant on a global scale because it influences vegetation-related feedbacks to the climate system, such as:

  • Albedo, e.g. changes in reflected solar radiation when deciduous forests move from leaf-off to leaf-on conditions
  • Canopy conductance, e.g. changes in the amount of leaf area that affect transpiration rates and CO2 uptake
  • Flows of water and energy, e.g. increased transfer of water vapor to the lower atmosphere following leaf-out
  • CO2 fluxes, e.g. changes in the balance between forest canopy photosynthesis and ecosystem respiration

Through these feedbacks, phenology not only influences regional weather patterns, but can also affect long-term global climate (Richardson et al. 2013). All this means that phenology has massive implications for global change science, ecosystem processes, and land management (including forestry).

For a more detailed description of climate feedbacks, including those associated with forests, revisit the June 2015 bulletin, Uncertainty in Climate Change and Forest Response: Part I.


Temperate and boreal trees go into dormancy every winter to protect their tissues against damage from cold temperatures, creating an annual cycle where dormancy is induced in the fall and released in the spring. These phenological shifts are cued and mediated by four primary factors:

  • Degree of warming in spring
  • Onset of cold temperatures in fall
  • Degree and duration of winter chilling
  • Photoperiod (i.e. day length relative to night length)

(Way & Montgomery 2015)

The diagram in Figure 1 illustrates how this process generally unfolds. In autumn, shorter days and lower temperatures induce endodormancy (an internally, genetically controlled, set state of inactivity), where growth ceases. Trees can only resume growth in the spring after they receive a signal that winter has ended, in the form of exposure to cool, non-freezing temperatures (also known as ‘chilling’). Although the amount of chilling required varies from species to species, it is a necessary prerequisite to move the tree into ecodormancy (a state of inactivity imposed by unfavorable environmental conditions), which is when they become sensitive to temperature and photoperiod cues. Once a certain amount of warming (i.e. degree-days) have been accumulated or certain photoperiod thresholds are met, the plant is released from ecodormancy and experiences the onset of bud burst, leaf unfolding, flowering, etc. (Basler & Körner 2014).

Clearly, much of this process is strongly mediated by temperature, including the rate at which buds and leaves develop after dormancy, but photoperiod and chilling are critical controls as well. As we discuss in a later section, the degree to which particular species are sensitive to chilling and/or photoperiod has the potential to constrain how well they track warming temperatures and adapt to changes in climate.


Complexity arises because the relative importance of the four factors listed above varies by species, genetic makeup, gene expression (i.e. phenotype), successional strategy, and region of origin (Way & Montgomery 2015; Basler & Körner 2014; Körner & Basler 2010; Kramer et al. 2017; Laube et al. 2014; Rohde et al. 2011). It also depends whether we are considering spring or fall phenology, since the latter is generally more sensitive to photoperiod than the former (Way & Montgomery 2015).

For example, one key factor is sensitivity to photoperiod. Trees that rely strongly on day length to signal phenology, rather than temperature cues, have certain advantages and disadvantages. Relying on photoperiod can help trees guard against leafing out too early and experiencing late season frosts, but responding to temperature gives trees the flexibility to take advantage of the extended period for photosynthesis (and the associated growth increase) offered by earlier onset of the frost-free season. As a result, species that are sensitive to photoperiod are less likely to experience earlier leaf out in response to warming. A common example is Fagus sylvatica (European beech), which is known to be particularly sensitive to photoperiod (less so to temperature) and has demonstrated a low level of variability in the timing of leaf unfolding from year to year, despite variability in temperature (Basler & Körner 2014). See Table 1 (below) for the categorization of some common species from across the globe.

Phenology: An Indicator of Change

People have been recording the timing of the seasons through plant phenology for centuries. The longest known records date back to the 9th century and describe the flowering of Japanese cherry trees, which are now blooming earlier than at any point in the last 1200 years (Primack et al. 2009). Over the past few decades, phenology has increasingly been recognized as a useful indicator of long-term ecosystem change (Richardson et al. 2013) and is now a prominent part of efforts to track the impact of a warming climate. In fact, the U.S. Global Change Research Program (USGCRP) includes the start of spring as one of their 14 initial indicators of climate change.


Spring phenology is well-understood and has been more extensively studied than autumn, in large part because it is easier to measure and detect the changes associated with phenomena like leaf out and flowering than the gradual process of fall senescence.

Evidence from ground-based and satellite studies (mostly in the Northern Hemisphere) shows spring advancement for “hundreds of plant and animal species in many regions” and, globally, spring has been advancing earlier at an average rate of around 3.3 (± 0.87) days per decade for tree species, with larger changes generally at higher latitudes (Settele et al. 2014). Indeed, a recent analysis of 25 years of satellite data detected an advance of 14.5 days in the start of the growing season in northern high latitude areas (> 45⁰N) (Jeganathan et al. 2014). Advance in the timing of spring onset in temperate trees over the last four decades can be attributed to warming temperatures (Richardson et al. 2013).

In the U.S., there has been a general trend toward earlier springs since 1984 (USGCRP). In fact, the year 2012, which was the hottest year on record for the U.S., stands out as the earliest spring start (Figure 2). Although, that record may soon be broken because “2017 is shaping up to be two to three weeks earlier than 2012 in many parts of the country” (NPN 2017) and up to three weeks earlier than normal (compared to 1981-2010) in some locations in the southeast (Figure 3).


The effect is less pronounced than for spring, but there have been documented delays in autumn senescence in European and North American temperate forests of 3-4 days per decade since 1982 (Rosenzweig et al. 2007; Richardson et al. 2013). The work by Jeganathan et al. (2014), mentioned above, also detected a 16-day delay in the end of the growing season in high northern latitudes over the last several decades.


These shifts in phenology, combined with a lengthening of the frost-free season, have increased the length of the growing season in many places (as we discussed in a previous bulletin). In the U.S., it has increased by as much as ten days since the 1980’s (EPA; Figure 4), with some parts of the country experiencing increases of up to 50 days in the period since 1895 (EPA; Figure 5). This has the potential to be a boon for the productivity of many ecosystems, including forests, e.g. research suggests lengthening the growing season by 5-10 days may increase annual net primary productivity of forest systems, by as much as 30% (Jackson et al. 2001) and other studies have shown that a difference of just one week in the timing of canopy development can mean a 20% difference in photosynthetic production from year to year (Myneni et al. 1997).

Shifting Phenology in a  Warmer World

Given the importance of temperature for signaling tree species phenology, what are the implications of climate change for our forests? This is an important question because changes in phenology have implications for productivity, survival, inter-species competition, pest and disease impacts, wildlife, and more. A review of the latest science suggests the following:

  • Overall extension of the growing season will increase forest productivity
  • Pioneer species (which have lower chilling requirements) may benefit from warmer winters
  • Many species demonstrate phenotypic plasticity, or an ability to shift their phenology to take advantage of warmer temperatures
  • Most species are likely to experience decreases in frost damage over time (on average)
  • Many species are likely to experience increased frost damage in some part of their distribution, particularly on the margins (even if they see a decrease on average)
  • Invasive species tend to have lower chilling requirements and less sensitivity to photoperiod, so they will benefit from warmer winters and take advantage of earlier spring warmth
  • Species composition may change due to phenologically-induced changes in understory light conditions that influence seedling survival
  • Certain characteristics, such as sensitivity to photoperiod, appear to be genetically determined, so some species will be limited in their ability to response to warming temperatures (especially in autumn when phenology is more strongly controlled by photoperiod)
  • For some species, milder winters will make it difficult to meet chilling requirements—leading to delays in spring phenology that may reduce their competitive advantage and growth potential, but also reduce their risk of late season frost
  • There will be changes in competitive advantage between species, based on varying ability to track warmer temperatures and take advantage of a longer growing season

(Laube et al. 2014; Kramer et al. 2017; Morin & Chuine 2014; Körner & Basler 2010; Basler & Körner 2014; Fu et al. 2015; Chen et al. 2017)

Emerging Research & Remaining Questions

The relationship between a warming world and forest phenology may seem straightforward—warmer temperatures, longer growing season, increased growth and productivity. However, a review of the current science reveals that it’s not quite that simple. Tree species, and even particular provenances, have unique sensitivities to the various seasonal cues, which makes it challenging to anticipate exactly how the timing of phenological events will shift on a local scale. Since there are many factors at play in determining how a particular species or site will change, it will be important to watch your own forest carefully to see which species are responding most effectively to warming temperatures.

As new research emerges, we will be better able to accurately pin down likely changes and identify the potential impacts for forest health, productivity, and composition. The following lists major uncertainties in the science, on-going research needs, and key questions that remain to be answered:

  • Relative importance of photoperiod versus temperature
  • Species-specific responses
  • Degree of phenotypic plasticity of particular species
  • Change in likelihood of frost damage (overall)
  • Better understanding/more research into climate change impacts on autumn phenology
  • Tension between scientific evidence for constraints on phenology (e.g. photoperiod sensitivity) and demonstrated species plasticity
  • Potential role of air humidity as a control on phenology
  • Improved phenological models that are more generalizable
  • Improved representation of phenological processes in terrestrial ecosystem models
  • Extremes can fundamentally alter phenological response—posing a challenge for prediction
  • Effective temperature range for chilling is only vaguely known for forest trees
  • Potential role of soil water in mediating phenology
  • Lack of an underlying ecological or physiological scheme that differentiates between photoperiodically sensitive and insensitive trees species—to facilitate prediction under future climate

(Basler & Körner 2014; Way & Montgomery 2015; Tansey et al. 2017; Kramer et al. 2017; Morin & Chuine 2014; Richardson et al. 2013; Laube et al. 2014b; Delpierre et al. 2016; Carter et al. 2017; Delpierre et al. 2017)

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Basler, D., and Körner, C. 2014. Photoperiod and temperature responses of bud swelling and bud burst in four temperate forest tree species. Tree Physiology. 34: 377-388.

Carter, J.M., Orive, M.E., Gerhart, L.M., Stern, J.H., Marchin, R.M., Nagel, J., Ward, J.K. 2017. Warmest extreme year in U.S. history alters thermal requirements for tree phenology. Oecologia. 183(4):1197-1210.

Chen, X., Wang, L., Inouye, D. 2017. Delayed response of spring phenology to global warming in subtropics and tropics. Agricultural and Forest Meteorology. 234-235; 222-235.

Delpierre, N., Vitasse, Y., Chuine, I., Guillemot, J., Bazot, S., Rutishauser, T., Rathgeber, C.B.K. 2016. Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models. Annals of Forest Science. 73: 5-25.

Delpierre, N., Guillemot, J., Dufrêne, E., Cecchini, S. 2017. Tree phenological ranks repeat from year to year and correlate withgrowth in temperate deciduous forests. Agricultural and Forest Meteorology. 234-235: 1-10.

Fu, Y.H., Zhao, H., Piao, S., Peaucelle, M., Peng, S., Zhou, G., Ciais, P., Huang, M., Menzel, A., Peñuelas, J., Song, Y., Vitasse, Y., Zeng, Z., Janssens, I.A. 2015. Declining globalwarming effects on the phenology of spring leaf unfolding. Nature. 526: 104-107.

Jackson, R.B., Lechowicz, M.J., Li, X., Mooney, H.A. 2001. Phenology, growth, and allocation in global terrestrial productivity. In: Saugier, B., Roy, J., and Mooney, H.A. (Eds.) Terrestrial Global Productivity: Past, Present, and Future. Academic: San Diego, CA, pp. 61-82.

Jeganathan, C., Dash, J., Atkinson, P.M. 2014. Remotely sensed trends in the phenology of northern high latitude terrestrial vegetation, controlling for land cover change and vegetation type. Remote Sensing of Environment. 143: 154-170.

Körner, C. and Basler, D. 2010. Phenology Under Global Warming. Science. 327: 1461-1462.

Kramer, K., Ducousso, A., Gömöry, D., Hansen, J.K., Ionita, L., Liesebach, M., Lorent, A., Schüler, S., Sulkowska, M., de Vries, S., von Wühlisch, G. 2017. Chilling and forcing requirements for foliage bud burst of Europeanbeech (Fagus sylvatica L.) differ between provenances and arephenotypically plastic. Agricultural and Forest Meteorology. 234-235: 172-181.

Laube, J., Sparks, T.H., Estrella, N., Höfler, J., Ankerst, D.P., Menzel, A. 2014. Chilling outweighs photoperiod in preventing precocious spring development. Global Change Biology. 20: 170-182.

Laube, J., Sparks, T.H., Estrella, N., Menzel, A. 2014b. Does humidity trigger tree phenology? Proposal for an air humidity based framework for bud development in spring. New Phytologist. 202: 350-355.

Morin, X. and Chuine, I. 2014. Will tree species experience increased frost damage due to climate change because of changes in leaf phenology? Can.J. For. Res. 44: 1555-1565.

Myneni, R.B., Keeling, C.D., Tucker, C.J., Asrar, G., Nemani, R.R. 1997. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature. 386: 698-702.

Primack, R.B., Higuchi, H., Miller-Rushing, A.J. 2009. The impact of climate change on cherry trees and other species in Japan. Biological Conservation. 142(9): 1943-1949.

Richardson, A.D., Keenan, T.F., Migliavacca, M., Ryu, Y., Sonnentag, O., Toomey, M. 2013. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology. 169: 156-173.

Rohde, A., Bastien, C., Boerjan, W. 2011. Temperature signals contribute to the timing of photoperiodic growth cessation and bud set in poplar. Tree Physiology. 31: 472-482.

Rosenzweig, C., G. Casassa, D.J. Karoly, A. Imeson, C. Liu, A. Menzel, S. Rawlins, T.L. Root, B. Seguin, P. Tryjanowski, 2007: Assessment of observed changes and responses in natural and managed systems. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 79-131.

Settele, J., R. Scholes, R. Betts, S. Bunn, P. Leadley, D. Nepstad, J.T. Overpeck, and M.A. Taboada, 2014: Terrestrial and inland water systems. In: Climate Change 2014: Impacts,Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L.White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 271-359.

Tansey, C.J., Hadfield, J., Phillimore, A.B. 2017. Estimating the ability of plants to plastically track temperature-mediated shifts in the spring phenological optimum. Global Change Biology. Available from, DOI: 10.1111/gcb.13624.

Way, D.A., and Montgomery, R.A. 2015. Photoperiod constraints on tree phenology, performance and migration in a warming world. Plant, Cell and Environment. 38: 1725-1736.



Attributing Extremes to Climate Change

(click here to download a formatted pdf of this full article or a one-page synopsis)

By Jennifer Hushaw

In previous bulletins, we described how climate change is altering the frequency and intensity of certain types of extreme weather (see Climate Change and Extreme Weather: Part 1) and how these extremes shape plant communities, forest health, and the global carbon budget (see Climate Change and Extreme Weather: Part 2). This is still front and center, as there have been many record-breaking extremes across the globe in the last few years (Otto 2016) and an increasing prevalence of heatwaves and/or heavy rain events in many regions.

In this bulletin, we are highlighting the science of extreme event attribution—an emerging field of research aimed at estimating exactly how much human-induced climate change contributes to individual extreme events. In some cases, scientists can now go beyond the often repeated line that “no individual weather event can be attributed to climate change” and instead provide quantitative estimates of how much the likelihood, frequency, or magnitude was influenced by anthropogenic warming. This information improves climate risk assessment and can help determine the appropriate management response, by differentiating between truly rare events and those that represent part of an on-going trend that warrants a shift in management.

Event Attribution

Over a decade ago, many thought it was essentially impossible to attribute individual weather events to climate change with any degree of certainty, but a new field of inquiry was sparked after a commentary in 2003 raised the question of liability for damages from extremes. The 2003 European heatwave was the first event subjected to this type of attribution analysis and researchers found climate change more than doubled the risk of such extreme heat (Stott et al. 2004). Since then, the field has taken off and the number of submitted studies about attribution grew by a factor of five between 2012 and 2015 (National Academies 2016).

There are a number of cooperative efforts working on this type of research, including the World Weather Attribution project, which is an international partnership providing rapid, near-real time analysis of major extreme events. Another is the weather@home project, which uses regional climate models (run through a volunteer computing network that is part of the platform) to determine how climate change affects weather on a smaller scale.


There are two general approaches in this type of research—utilizing the historical record or modeling—and a hybrid approach is most common. In the former, researchers look at the historical context to see whether the rarity of an observed event (e.g. heatwave, heavy downpour, etc.) has changed over time. They may also look to see whether the recent extreme is different in any way from similar meteorological events in the past. In the latter, researchers run model simulations of the climate with and without human influence to see whether anthropogenic carbon emissions changed the probability or intensity of a particular type of extreme.

With the modeling approach, there are a number of metrics that quantitatively describe the change in risk. A common one is Fraction of Attributable Risk (FAR)—the portion of the risk of a particular extreme that is attributable to human influence, where FAR = 1 means all of the current risk is attributable to human-induced climate factors and FAR = 0 means all of the risk is attributable to natural factors (Pall et al. 2016).  For example, the Australian summer of December 2012 to February 2013 was the hottest on record and an attribution study revealed the FAR for average summer temperatures was 0.72, meaning there was a more than threefold increase in the risk of record summer temperatures as a result of human influence on the climate (Lewis and Karoly 2013).


There has been rapid progress over the last five years, both in the sophistication of the science and the speed with which attribution assessments can be done. In many cases, an assessment can be made within weeks, as compared to months (and publication of results long after the event). This is thanks to improved scientific understanding of the climate and weather mechanisms that produce extremes, advances in methodology, and increases in computing power (National Academies 2016; Pall et al. 2016). As an example, researchers with the World Weather Attribution project were able to turn around an attribution assessment for the May 2016 European flooding less than two weeks after the event.


Some events can be attributed to climate change more confidently than others. We have the greatest confidence in studies with the following:

  • A solid understanding of the physical mechanisms underlying the extreme event.
  • Consistent evidence from a high-quality observational record.
  • Climate models that accurately simulate and reproduce the class of extreme event.

(National Academies 2016; Hassol et al. 2016)

Meeting these criteria yields the most reliable results, but it is more difficult to “check all the boxes” for some classes of extremes, which is why uncertainty often depends on the type of event in question. There is more confidence in attribution studies about extremes directly linked to temperature (e.g. heatwaves) than about extremes indirectly related to temperature that are driven by multiple factors (e.g. convective storms or wildfires). Generally, the more direct the link with temperature, the easier it is to determine attribution with a great degree of confidence (Climate CIRCulator 2016; National Academies 2016).

This hierarchy is reflected in Figure 1 (below), which ranks various extremes in terms of the criteria mentioned above. Extremes directly related to temperature are toward the left and as you move right the extremes are more indirectly related to temperature and more complex in terms of the underlying mechanisms. Wildfire, for example, is a complex phenomenon that falls toward the right of the figure in terms of attribution confidence because the intensity and occurrence is not directly related to temperature, but is instead related to many factors, including humidity, antecedent conditions, fuel loads, and others (as we discussed in a recent bulletin on wildfire).

A Recent Example

Texas experienced a record-setting drought and heatwave in 2011 that had far reaching impacts, including on the forest industry. Not only were there a record number of acres burned in wildfires that year, but commercial timber losses from the drought were estimated at $755 million (with only 13% of that due to fire), according to the Texas Forest Service (Hoerling et al. 2013). Analysis revealed that the biggest factor contributing to the intensity of the heatwave was a precipitation deficit driven by changes in sea surface temperature, including a La Niña event. This natural variability explained about 80% of the temperature increase associated with the heatwave, but an additional 20% was attributable to human-induced climate change, specifically summertime temperature trends (Hoerling et al. 2013). This is an example where an extreme was largely caused by natural processes, but anthropogenic warming likely made the overall impact and damages worse than they may otherwise have been.

Using Attribution Information to Inform Forest Management

Extremes can have a huge influence on forest health, composition, and productivity (as we described in a previous bulletin) and event attribution research will help more accurately pin down the role of climate change in these events. This improves our understanding and helps avoid over- or under-estimation of the risks.

This is important because the way we perceive and frame the causes of an event influences how we respond to it, including post-disaster actions, preventive practices, and adaptation or mitigation initiatives (Lidskog & Sjödin 2016). If attribution studies suggest a particular extreme event is part of an on-going trend (rather than a rare, one-off occurrence), it makes sense to take action that reduces that risk in the future. For example, a homeowner whose property is severely damaged by a storm surge may decide whether to rebuild or relocate based on this type of information because it sheds light on whether they can expect a repeat in the future.

The following are some example forest management scenarios that illustrate how you might apply this idea in practice:

  1. A major storm event causes numerous blow downs in forest stands. A subsequent study suggests that a storm of that magnitude was twice as likely because of climate change. With the expectation that these types of storm events may become more frequent, you divert resources toward pro-active management that develops increased wind-firmness in intact and newly established stands, rather than focusing solely on salvage efforts.
  2. A mild drought that would historically leave stands largely unaffected results in some tree mortality due to the subsequent onset of a prolonged heat wave. Studies indicate the extreme heat was largely due to human-induced climate change (e.g. FAR = 0.8) and similar heat events will become more likely in the future. You consider planting more drought-tolerant variants or reducing density in established stands because evidence indicates that particular site will be more prone to drought-related forest mortality going forward.
  3. A severe winter storm leads to extensive ice damage in forest stands, but subsequent research indicates the storm was largely the result of natural climate forces and, while rare, icing events of similar magnitude were experienced in the past. You undertake any necessary salvage, but otherwise refrain from changing your management because evidence suggests the storm was an infrequent, but not unusual weather event.
  4. Culverts on a forest road, that were sized following the typical standard, wash out during an unusually heavy downpour. Analysis shows the rain event was more intense as result of warming trends. When replacing the culverts, you upsize in anticipation of larger peak flows in the future.

Manomet’s Resiliency Assessment Framework, which is currently under development, lays the groundwork for an enhanced forest monitoring system that will improve the quality and length of the observational record for key variables—a necessary component of robust attribution assessments (as discussed above). Our ultimate goal is to discern signal from noise in forest trends, by combining the data from this monitoring framework with the rapidly advancing science of attribution, which will enable more effective management that reduces forest vulnerability and capitalizes on potential advantages.

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Allen, Myles. 2003. Commentary: Liability for Climate Change. Nature. 421: 891-892.

Climate CIRCulator. Linking Extreme Weather to Climate Change. June 30, 2016. Accessed at:

Hassol, S.J., Torok, S., Lewis, S., Luganda, P. 2016. (Un)Natural Disasters: Communicating Linkages Between Extreme Events and Climate Change. World Meteorological Organization. Bulletin, Vol. 65(2). Accessed online at:

Hoerling, M., Kumar, A., Dole, R., Nielsen-Gammon, J.W., Eischeid, J., Perlwitz, J., Quan, X., Zhang, T., Pegion, P., Chen, M. 2013. Anatomy of an Extreme Event. Journal of Climate. 26: 2811-2832.

Lewis, S.C. and Karoly, D.J. 2013. Anthropogenic contributions to Australia’s record summer temperatures of 2013. Geophysical Research Letters. 40: 3705-3709.

Lidskog, R. and Sjödin, D. 2016. Extreme events and climate change: the post-disaster dynamics of forest fires and forest storms in Sweden. Scandinavian Journal of Forest Research. 31(2): 148-155.

National Academies of Sciences, Engineering, and Medicine. 2016. Attribution of Extreme Weather Events in the Context of Climate Change. Washington, DC: The National Academies Press. Doi: 10.17226/21852

Otto, F.E.L. 2016. News & Views, Extreme Events: The art of attribution. Nature Climate Change. 6: 342-343.

Pall, P., Wekner, M., Stone, D. Chapter 3: Probabilistic extreme event attribution. In: Dynamics and Predictability of Large-Scale, High-Impact Weather and Climate Events. Special Publications of the International Union of Geodesy and Geophysics. [Li, J., Swinbank, R., Grotjahn, R., Volkert, H. (eds.)] Cambridge University Press, United Kingdom, 2016.

Stott, P.A., D.A. Stone, & M.R. Allen, 2 December 2004. Human contribution to the European heatwave of Nature. 432: 610–614.

Wildfire in a Warming World: Part 2

(click here to download a pdf of this complete article or a one-page synopsis)

By Jennifer Hushaw & Si Balch

In Part I, we discussed the recent rise in U.S. wildfire, the evidence suggesting climate is a major driver of that increase, and the reality that future increases in temperature and drought frequency (in some regions) will lead to greater fire potential, especially in moisture-limited ecosystems. There is no question that wildfire risk has changed (and will continue to change) research-update-boxas a result of on-going climate change. Importantly, the anticipated shifts in fire will have big implications for commercial forests and conservation lands alike, as well as implications for the climate system itself because wildfire acts as a positive feedback that accelerates terrestrial carbon emissions. Severe disturbance caused by novel fire regimes may also hasten the species shifts expected with climate change, making fire an important driver of ecosystem change in both the near- and long-term.

In Part II, we describe the latest research on future changes in fire frequency, extent, and/or severity, as well as discussing management strategies and outlining some useful information sources.

Overview of Changing Fire Risk


Fire potential and the length of the fire season are projected to increase in many regions. These changes will be driven by earlier snowmelt, warmer temperatures (particularly summer), drought stress, and changes in soil water content (Keane et al 2015; Waring and Coops 2016; Young et al 2016) associated with climate change.

In the continental U.S., the potential for very large fires (>12,355 acres) is strongly linked to meteorological and climatological conditions. Recent research indicates that the potential for very large fires will increase in historically fire-prone regions as a result of climate change, while other regions will experience an earlier start or an overall extension of the fire season as atmospheric conditions become conducive earlier in the year and persist later (Barbero et al 2015) – see details in The North American Outlook (below).

Drier fuels will also increase fire potential because fuel moisture is highly sensitive to temperature. For example, a recent analysis in Canada found that for each additional degree of warming, a 5 to 15% increase in precipitation is required to maintain fuel moisture, depending on the type of fuel in question (i.e. fine surface fuels, duff layers, or deep organic soils) (Flannigan et al 2016). In the absence of a sufficient precipitation increase, these fuels begin to dry out and move closer to critical thresholds for fire ignition and spread. In fact, Canada is expected to have more days of extreme fire weather because future precipitation will be insufficient to compensate for the drying associated with warmer temperatures – this is true even for future scenarios with the greatest precipitation increase (i.e. 40%) (Flannigan et al 2016).

Some of these changes will be non-linear, leading to dramatic increases in fire frequency or severity in some regions once critical thresholds are crossed. A great example can be found in the boreal forest and tundra ecosystems of Alaska where there are distinct temperature and moisture thresholds[1] for fire occurrence that will likely be crossed by the end of this century, significantly increasing the probability of wildfire and potentially leading to novel fire regimes in those areas (Young et al 2016).


Climate-induced changes in vegetation (including type, density, large scale die-off, etc.) and forest pests will also influence fire risk by affecting fuel loads.

As we discussed in a previous bulletin, climate change will affect the population dynamics and spread of many forest pests and diseases, including mountain pine beetle. Mountain pine beetle outbreaks can, in turn, alter the quantity and characteristics of both live and dead fuels by changing the amount of fuel in the forest canopy, the base height of the canopy, the amount of surface fuel, and other aspects of forest biomass. In this way, they can influence fire probability, severity, and rate of spread, as well as the potential for crown fire (Hicke et al 2012).

Climate change will also have direct effects on vegetation and forest biomass through long-term shifts in species distribution and forest composition, as well as small- and large-scale mortality events brought on by drought and other extremes. In Part I, we detailed how drought and beetle-induced mortality in western U.S. conifers is already contributing to an increase in fire. These mortality events and longer-term vegetation changes can flip an ecosystem from being fuel- to moisture-limited (or vice-versa), changing what controls fire activity in a given region (as discussed in Part I).

In some cases, the changing fire regime itself will cause vegetation communities to shift or flip from a moisture- to fuel-limited ecosystem. For example, the fire return interval in the greater Yellowstone ecosystem is predicted to decrease (i.e. more frequent fire) to the point that some forested areas will no longer be able to regenerate by mid-century and will instead convert to a new dominant vegetation type that shifts the region into a fuel-limited fire regime (Westerling et al 2011).

“The bottom line is that we expect more fire in a warmer world.”  (Flannigan et al 2016)


Modelling Future Wildfire


Globally, fire probability is expected to increase in the mid- to high-latitudes and decrease in the tropics, with these changes becoming more pronounced later in the century. In the near term (i.e. 2010-2039), the most consistent increases will occur in places with an already somewhat warm climate, but there are also major uncertainties in the next few decades. There is more confidence in projections for the end of the century (i.e. 2070-2099) when climate models have a higher level of agreement in their projections because the magnitude of climate change will be even greater, with some locations experiencing an average change in fire probability up to +0.25 (Figure 1; Moritz et al 2012).

Flannigan et al (2009) also suggest that a general increase in area burned and fire occurrence is likely, based on their review of close to 50 studies conducted between 1991 and 2009 on future fire activity around the world. Although these studies focused on different fire activity metrics, time frames, and locations, more than three-quarters of the analyses pointed to an increase in fire activity. In particular, they noted that fire seasons are lengthening in temperate and boreal regions and this trend should continue in a warming world.


Most of the research conducted to date in North America points toward a future increase in wildfire, with longer fire seasons and greater fire potential due to more conducive atmospheric conditions in a number of regions (Barbero et al 2015; Wang et al 2015; Liu et al 2013; Young et al 2016).

For example, in a study mentioned above, researchers from the University of Idaho, the US Forest Service, and the Canadian Forest Service modelled future potential for “very large fires” in different ecoregions due to climate change and they found the potential for very large fires will increase in the continental U.S. The largest absolute increases were predicted for the intermountain West and Northern California, while the largest relative changes were predicted in the northern tier of the country where the potential for very large fires has historically been quite low (Figure 2). In addition, their analysis suggests the southern U.S. will have an earlier fire season in the future, while the northern regions will experience an overall lengthening of the fire season, with an extension of potential burn days at both ends of the season. These changes are driven by anticipated increases in fire danger and temperature, as well as decreases in precipitation and relative humidity during the fire season (Barbero et al 2015).

figure2Another study by Liu et al (2013) used results from a downscaled climate model to evaluate how fire potential will change by mid-century (2041–2070), as measured by the Keetch–Byram Drought Index (a commonly used index designed specifically for fire potential assessment). They predict an increase in fire potential in the Southwest, Rocky Mountains, northern Great Plains, Southeast, and Pacific coast due to warming trends, in addition to longer fire seasons in many regions.

Looking farther north, the research also suggests increases in fire potential across high-latitude regions. Specifically, the annual number of fire spread days in Canada is expected to increase anywhere from 35–400% by 2050, with large absolute increases in the Boreal Plains of Alberta and Saskatchewan and the greatest relative change in coastal and temperate forests (Wang et al 2015). Similarly dramatic increases in fire activity are predicted for areas of Alaska with historically low flammability in the tundra and tundra-forest boundary areas, with “up to a fourfold increase in the 30-yr probability of fire occurrence by 2100” (Young et al 2016).

Fire potential is not the only metric we might be concerned about, however. There are also questions about how fire severity may change as a result of climate change. figure3Although fire severity will increase in some cases, as we have seen in the western U.S. with high fuel loads and exceptional drought conditions, future conditions may also decrease fire severity. When some researchers incorporated climate-induced changes in vegetation type, fuel load, and fire frequency, rather than climatic changes alone, they found that a widespread reduction in fire severity was likely for large portions of the western U.S. (Figure 3; Parks et al 2016). This is because future increases in fire frequency and water deficits will reduce vegetation productivity, the amount of regeneration, and the amount of biomass accumulation on the landscape—all of which contribute to decreased fuel loads that will no longer support high-severity fires (Parks et al 2016).

Management Considerations  


When considering how to address these wildfire regime shifts, one approach is to “manage for the extremes,” rather than the average fire event or return interval in a given region, because it is the extremes that determine the necessary capacity of fire management organizations and, although these extremes cannot be as easily predicted, they can have serious consequences (Wang et al 2015; Irland 2013).


In terms of forest management, fuels reduction via pre-commercial or commercial thinning operations and prescribed fire is an obvious strategy for dealing with increased fire potential. That said, fuels reduction is better suited for some forest types than others, namely fuel-limited forest communities (Steel et al 2015), e.g. yellow pine and mixed conifer forests in California or piñyon-juniper woodland and lower montane forests (dominated by ponderosa pine) in the Rocky Mountain region. In systems where the fire regime is primarily moisture- or climate-limited, a reduction in fuels will not be as effective at reducing fire hazard because fuel is not the limiting factor.


An argument can also be made for taking a more passive approach that “lets nature take its course,” where the fire regime is allowed to change and it ultimately shifts the dominant vegetation type to something new (as discussed above). In this case, the natural disturbance regime eventually transitions plant communities into a state of equilibrium with the new climate (Parks et al 2016). This approach may ultimately be more appropriate and cost-effective in locations where conditions are expected to become more arid and fire frequency is projected to increase dramatically, compared with resisting change through on-going, active fire suppression efforts. Although not appropriate for most commercial operations, the passive approach may be a consideration for lands with a management focus on maintaining resilient transitional habitat for wildlife in a changing climate.


Of course, it is worth noting that these anticipated changes in wildfire are happening in the larger context of land use change (more development in the wildland urban interface, greater forest fragmentation), fuel accumulation (due to historic fire suppression efforts, landowner reluctance to harvest, and/or insufficient budgets for fuel treatments), and infrastructure/industry changes (lack of “fire wise” development in some regions, loss of institutional firefighting operations with ownership change).

Things to Do

A number of common practices can help land managers prepare for fire risk, which will be important to emphasize (or implement) in the face of increased fire potential. These include:

  1. Put all foresters and other field personnel through the state forestry department’s basic fire training school.
  2. Have the state forest service phone numbers and radio contact on everyone’s cell phone.
  3. Equip everyone’s truck with Indian tanks and fire rakes.
  4. Know who has bulldozers, where they are, and how to reach their owners.
  5. Identify water sources for pumping.
  6. Identify water sources for water bombers.
  7. Identify landing zones for helicopters.
  8. Think about how to communicate with abutting home owners about fire risk. This interface of houses and trees is an increasingly dangerous situation for both the forest owner and home owner.
  9. Utilize the resources below to find up-to-date information on potential fire risk.

Additional Resources

  • A program that produces landscape-scale geospatial products for planning, management, and operations, including maps and databases that describe vegetation, fuel, and fire regimes. Website provides data, reports, tools, maps, etc.
  • Source: USDA Forest Service & US Department of Interior
National Interagency Coordination Center
  • NICC coordinates interagency wildland firefighting resources. They also dispatch Incident Management Teams and resources as necessary when fires exceed the capacity of local or regional firefighting agencies. Website provides Incident Information with daily updates on large fires and Predictive Services, such as weather, fire fuels danger, outlooks, etc., as well as other resources for wildland fire and incident management decision-making.
  • Source: Multi-agency organization, including: BIA, BLM, USFS, USFWS, NASF, & NPS
FRAMES (Fire Research and Management Exchange System)
  • A searchable online portal for fire-related information, including documents, tools, data, online trainings, discussion forums, announcements, and research, as well as links to numerous other fire-related websites and portals for regionally-specific sites and resources.
  • University of Idaho; USFS Rocky Mountain Research Station
Joint Fire Science Program (JFSP)
Geographic Area Coordination Centers
  • Web-portal for incident information, logistics, predictive services (e.g. information about weather, fuels and fire danger), and administrative resources for wildland fire agencies.
  • Source: Geographic Area Coordinating Group (GACG) – interagency; made up of Fire Directors from each of the area Federal and State land management agencies
  • Portal to numerous websites and resources related to wildfire risk and detection, including many listed in this table and others.
  • Source: Multi-agency, including: FEMA, EPA, Dept. of Interior, Dept. of Commerce, NOAA, DOE, USDA, and Army Corps of Engineers
  • Educational resources on wildfire prevention and “firewise” practices for homeowners and professionals, including state-specific information for New England and adjacent Canadian provinces.
  • Source: Northeast Forest Fire Protection Commission’s Prevention and Education Working Team
Wildfire Risk Assessment Portals
  • Several states/regions have these websites, which include web-mapping applications showing fire risk and assessment, as well as information on historic fire occurrence and information for developing community wildfire protection plans.
  • Source(s): State forest service, state forester, universities, etc
Active Fire Mapping Program
  • Provides near real-time, satellite-based detection and characterization of wildland fire conditions in a geospatial context for the continental United States, Alaska, Hawaii and Canada.
  •   *soon moving to new URL:
  • Source: USDA Forest Service Remote Sensing Applications Center
Historic Wildfire Occurrence Data
  • This data product contains a spatial database of wildfires that occurred in the United States from 1992 to 2013, generated for the national Fire Program Analysis (FPA) system. The wildfire records were acquired from the reporting systems of federal, state, and local fire organizations.
  • USDA Forest Service
Global Maps of Fire Risk
  • This on-line map viewer of satellite-derived global vegetation health products, includes one for fire risk that is updated continuously. You can also go back and see archived maps from previous dates.
  • (choose “Fire Risk” under the Data Type dropdown menu)
  • Source: Center for Satellite Applications and Research (STAR) – the science arm of the NOAA Satellite and Information Service
National Fire Protection Association
  • Source for national fire codes and standards, public education, and research on fire risk and prevention.



[1] Young et al (2016) identified two thresholds for fire occurrence, based on historic data: average July temperatures above 13.4⁰C and annual moisture availability (i.e. precipitation minus evapotranspiration) below 150mm.

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Abatzoglou, J.T. and Williams, A.P. 2016. Impact of anthropogenic climate change on wildfire across western US forests. PNAS. 113(42): 11770–11775.

Barbero, R., Abatzoglou, J.T., Larkin, N.K., Kolden, C.A., Stocks, B. 2015. Climate change presents increased potential for very large fires in contiguous United States. International Journal of Wildland Fire. 24(7) 892-899.

Flannigan, M.D., Krawchuk, M.A., de Groot, W.J., Wotton, B.M., Gowman, L.M. 2009. Implications of changing climate for global wildland fire. International Journal of Wildland Fire. 18: 483-507.  

Flannigan, M.D., Wotton, B.M., Marshall, G.A., de Groot, W.J., Johnston, J., Jurko, N., Cantin, A.S. 2016. Fuel moisture sensitivity to temperature and precipitation: climate change implications. Climatic Change. 134:59-71.

Hicke, J.A., Johnson, M.C., Hayes, J.L., Preisler, H.K. 2012. Effects of bark beetle-caused tree mortality on wildfire. Forest Ecology and Management. 271: 81-90.

Irland, L.C. 2013. Extreme value analysis of forest fires from New York to Nova Scotia, 1950-2010. Forest  Ecology and Management. 294: 150-157.

Keane, R.E., Loehman, R., Clark, J., Smithwick, E.A.H., Miller, C. 2015. Chapter 8: Exploring Interactions Among Multiple Disturbance Agents in Forest Landscapes: Simulating Effects of Fire, Beetles, and Disease Under Climate Change in Simulation Modeling of Forest Landscape Disturbances. A.H. Perera et al. (eds.) Springer International Publishing. Switzerland.

Liu, Y., Goodrick, S.L., Stanturf, J.A. 2013. Future U.S. wildfire potential trends projected using a dynamically downscaled climate change scenario. Forest Ecology and Management. 294: 120-135.

Moritz, M.A., Parisien, M-A., Batllori, E., Krawchuk, M.A., Van Dorn, J., Ganz, D.J., Hayhoe, K. 2012. Climate change and disruptions to global fire activity. Ecosphere. 3(6):49.

Parks, S.A., Miller, C., Abatzoglou, J.T., Holsinger, L.M., Parisien, M., Dobrowski, S.Z. 2016. How will climate change affect wildland fire severity in the western US? Environmental Research Letters. 11: 035002.

Steel, Z.L., Safford, H.D., Viers, J.H. 2015. The fire frequency-severity relationship and the legacy of fire suppression in California forests. Ecosphere. 6(1): Article 8, 23pp.

Wang, X., Thompson, D.K., Marshall, G.A., Tynstra, C., Carr, R., Flannigan, M.D. 2015. Increasing frequency of extreme fire weather in Canada with climate change. Climatic Change. 130: 573-586.

Waring, R.H. and Coops, N.C. 2016. Predicting large wildfires across western North America by modeling seasonal variation in soil water balance. Climatic Change. 135: 325-339.

Westerling, A.L., Tumer, M.G., Smithwick, E.A.H., Romme, W.H., Ryan, M.G. 2011. Continued warming could transform Greater Yellowstone fire regimes by mid-21st century. PNAS. 108(32): 13165-13170.

Young, A.M., Higuera, P.E., Duffy, P.A., Hu, F.S. 2016. Climatic thresholds shape northern high-latitude fire regimes and imply vulnerability to future climate change. Ecography. 39: 001-012.

Wildfire in a Warming World: Part 1

(click here to download a pdf of the full article or a one-page synopsis)

By Jennifer Hushaw

Wildfire has been a hot topic in the media lately, with California ablaze due to a combination of dangerous fire weather, on-going drought, and scores of drought- and beetle-killed trees. Most recently, the Blue Cut Fire (pictured above) burned 37,000 acres and the Soberanes Fire, which began in late July, is still uncontained and has already burned over 105,600 acres. Of course, severe wildfires are certainly nothing new—take the Great Fire of 1910 that burned 3 million acres or the Miramichi Fire in New Brunswick that burned over 3.8 million acres in 1825—but climate change is creating new cause for concern. In fact, the 2014 U.S. National Climate Assessment says climate change-related fire is increasing the vulnerability of U.S. forests to ecosystem change and tree mortality.

In Part I of this two-part piece, we examine recent trends in fire activity, untangle the role of climate change, and outline the most important aspects of climate that drive fire patterns on the landscape.

The Global Picturefigure1

Climate change is expected  to increased wildfire activity in certain regions (IPCC AR5), but, so far, there is little evidence of an increase in area burned or an increase in fire severity for many parts of world, and even some evidence suggesting that, overall, there is less fire on the landscape now than centuries ago (Doerr & Santín 2016).

A 2013 study by researchers at the University of Maryland, the University of California, and VU University in Amsterdam showed this variability in fire trends across different regions (Giglio et al 2013). They examined global and regional trends in the monthly area burned from 1996 to mid-2012 using information from the fourth generation of the Global Fire Emissions Database (GFED) and they found different, and sometimes opposite, trends depending on the region, as well as a slight decrease in global area burned over the last 16 years (see Figure 1). The study did not analyze what caused these trends, but researchers did offer some insight into the source of year-to-year variability observed in each region. The level of variability relates to ignition and rainfall—regions with fairly consistent fire activity tend to have widespread and routine human-induced burning (mostly for land maintenance) and similar rainfall from year-to-year (e.g. southern and northern Africa), whereas regions with high variability have more sporadic fire ignition (by humans or otherwise) and more variability in the amount of rain from year-to-year (e.g. Equatorial Asia, where fire activity is closely tied to El Niño events) (Giglio et al 2013).

Wildfire in the U.S.

In contrast to the global picture, we have seen increasing media reports of large wildfires and more discussion of the ballooning cost of fire control efforts in the United States in recent years. This is especially true when conflagrations break out at the intersection of forests and developed lands, also known as the Wildland Urban Interface (WUI). Given the greater cost of suppression efforts and increased risk of damage to lives and property in these areas, some have suggested that the perceived increase in wildfire may simply be due to increased attention. However, as we will discuss below, there is ample evidence that large portions of the U.S. have indeed experienced more fire.

Most studies of wildfire trends in the U.S. are focused on the western part of the country and they have detected an overall increase in fire activity over recent decades. For example, there is evidence that the number of large fires (> 1,000 acres) and/or total area burned per year increased in many parts of the western U.S. from 1984-2011 (Figure 2; Dennison et al 2014).


Another research team detected a similar trend since 1970, with a noticeable increase in western forest fire activity beginning around the mid-1980’s (see Figure 3, below), including more frequent large fires (> 1,000 acres), fires that burned longer, and longer wildfire seasons (Westerling et al 2006; Westerling 2016).


Additionally, there is evidence that the number of very large fires (> ~12,400 acres) has also been increasing over the last 30 years, particularly across parts of the southeastern and southwestern U.S. (Barbero et al 2014).

These observations square with another recent study (Jolly et al 2015), which showed that conditions have become more conducive to fire in many parts of the world. Researchers used historic climate data from 1979 to 2013 to calculate the length of the fire weather season over the last 35 years, based on several common fire danger indices used in the U.S., Canada, and Australia. They found that, globally, the length of the average fire weather season increased by almost 19% and the amount of land area affected by long fire weather seasons doubled. Their results coincided with evidence of recent trends in the U.S. For example, in 2012, about 47% of the vegetated area of the U.S. experienced a longer-than-normal fire weather season according to their estimates and that resulted in a “near-record setting ~3.8MHa [9.4 million acres] of burned area” (Jolly et al 2015).

Although, even in the U.S., not all regions are experiencing more wildfire. The Northeast, for example, is known for some historic mega-fires, but now has an annual average area burned of only 0.04% of forest area and fire histories show a decline for the last 60 years in both the area burned and the size of fires (Irland 2013). This decline is likely due to better detection, regulation, and control methods since the 1950’s, but it also means more fuel has accumulated on the landscape (Irland 2013). Importantly, extreme fire behavior can still occur in regions with very infrequent fire and, in fact, almost every part of the Northeast has experienced extreme fire years or unusually large fires since that decline began in the 1950’s (Irland 2013).

A Climate Change Connection?

A number of factors have contributed to the recent increase in U.S. wildfires, including higher fuel loads from historic fire suppression and large-scale forest mortality due to bark beetle outbreaks, but an important question is: To what extent, if any, has climate change contributed to these observed trends? Evidence suggests it has played a role. The Intergovernmental Panel on Climate Change (IPCC) noted that climate change has already had a major impact on wildfire activity in North America, some parts of Europe (specifically Portugal and Greece), and Africa in recent years (IPCC AR5 SPM, Figure SPM.4). In fact, fire is one of the key climate change-related risks they list for North America and Europe and that risk is projected to increase as we move farther into this century (IPCC AR5 SPM, Figure SPM.8). The 2014 U.S. National Climate Assessment also identified a link between climate change and fire, noting that “Climate change is contributing to an increase in wildfires across the U.S. West.” They point specifically to hotter and drier weather and earlier snowmelt, which has increased the length of the fire season and amount of acreage burned (NCA 2014).

Numerous studies suggest changes in climate are largely responsible for observed wildfire trends in the U.S. (Littell et al 2009; Jolly et al 2015; Westerling et al 2006; Westerling 2016; Attiwill & Binkley 2013) and there is evidence for this connection in both modeling and observational studies. For example, Barbero et al (2014) developed models that successfully replicated historic fire patterns across the continental U.S. using ONLY climate variables, which indicates climate is the major mechanism driving fire activity. Another study found that climate was a significant driver of fire activity in the western U.S. from 1916 to 2003—explaining an average of 39% of the variability in area burned—and there was an even stronger linkage in the most recent decades from 1977 to 2003, where climate explained an average of 64% of the area burned (Littell et al 2009). A third example, mentioned earlier, is research from Dennison et al (2014) that found similar wildfire trends across a variety of western U.S. ecoregions with different vegetation types, fire seasons, fuel types, and fire frequencies (see Figure 2), but similar increases in severe drought. This suggests prevailing climatic conditions, rather than site-specific dynamics, are responsible. Evidence suggests climate change will only continue to play a bigger role in shaping fire trends, as we move from global fire regimes that were driven by precipitation during the pre-industrial period and by human ignition and suppression during the 18th century, into a new temperature-driven global fire regime (Pechony & Shindell 2010).

Climate & Fire: Take Homes for Forest Managers

Climate Drives Fire Activity

While there are many factors that determine where, when, and how wildfires burn, climate is well-recognized as one of the primary controls on fire activity (Dennison et al 2014). At the simplest level, it influences the availability and flammability of fuels, but fire requires three components—biomass to burn, the right atmospheric conditions, and ignition—and climate affects all of these components “in complex ways and over multiple timescales” (Moritz et al 2012). In the short-term, climate controls ignition and propagation, while in the long term it affects fuels by influencing primary productivity and vegetation (Urbieta et al 2015).

Time scale Matters

The diagram in Figure 4 (below) outlines how different aspects of climate control fire at different scales. For example, in some North American regions, fire regimes are closely related to natural modes of climate variability, such as the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and the Atlantic Multidecadal Oscillation (AMO) (Whitlock et al 2010; Fauria & Johnson 2008)—see our previous bulletin on Global Temperature Trends for an explanation of how the ENSO/PDO system influences fire regimes worldwide. We are accustomed to thinking about the drivers of fire at shorter timescales (i.e. at the level of individual fires—seasonal-to-annual—and how they propagate—hourly-to-annual) because fire management and response systems typically operate at those scales, but the influence of decade-to-decade climate fluctuations and the long-term warming trend  are no less important. Changes in average climate, variability, and long-term trends can shift the fire regime in a given region and, since climate conditions are projected to continue changing for the foreseeable future, it is reasonable for forest managers to expect and prepare for deviations from the historic fire regime in their area.


Drought & Fire Risk

More immediate fire-climate impacts will most likely come through drought, which also played a role in the record-breaking 2015 U.S. fire season. Drought is projected to increase in both frequency and severity in many regions and it is known to directly affect fire severity, extent, and frequency (Littell et al 2016). The uncertainty of future precipitation patterns, as discussed in an earlier bulletin, presents a challenge because there are very few regions of the world where we have confidence in predictions of future drought. That said, warmer temperatures alone can increase the intensity of individual drought events (and associated fire risk) by increasing potential evapotranspiration (as discussed previously)—a factor that has been implicated in the severity of the recent California drought (Diffenbaugh et al 2015).

What’s Limiting: Fuel or Moisture?

The impact of climate change on fire activity will largely depend on whether an ecosystem tends to be more fuel-limited or climate-limited (Littell et al 2009; Steel et al 2015; Whitlock et al 2010). In the former, fire is limited by the amount of fuel available and these are often drier, more sparsely vegetated areas that experience frequent, lower-severity wildfires. In contrast, fire in climate-limited systems is controlled by fuel flammability and these are generally more moist systems with significant biomass that experience infrequent, more severe wildfires. For example, more precipitation can actually increase fire risk in fuel-limited ecosystems by increasing the quantity of fine fuels (Dennison et al 2014), compared to climate-limited ecosystems like the boreal forest where moisture rather than fuel accumulation is the primary determinant of fire behavior and more precipitation would typically decrease fire risk (Fauria & Johnson 2008). Factors like human intervention can flip a system from one end of the spectrum to another. For example, researchers studying 130 years of fire history in a Spanish province in the Mediterranean found that rural depopulation and farm abandonment increased fuels and shifted the fire regime in that region from fuel-limited to climate-limited, leading fire activity to become more drought-driven (Pausas & Fernandez-Munoz 2012). Fire activity in these climate-limited ecosystems is sensitive to changes in temperature, so warming may especially increase fire risk in these systems.

Coming up…

In Part II, we outline what the latest research suggests in terms of future fire frequency, extent, and/or severity and we discuss the changing context of more fire in the WUI, rising costs, and changing organizational structures, as well as providing useful resources for more information.

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Attiwill, P., Binkley, D. 2013. Editorial: Exploring the mega-fire reality: A ‘Forest Ecology and Management’ conference. Forest Ecology and Management. 294: 1-3.

Barbero, R., Abatzoglou, J.T., Steel, E.A., Larkin, N.K. 2014. Modeling very large-fire occurrences over the continental United States from weather and climate forcing. Environ. Res. Lett. 9: 11pp.

Dennison, P.E., Brewer, S.C., Arnold, J.D., Moritz, M.A. 2014. Large wildfire trends in the western United States, 1984-2011. Geophys. Res. Lett. 41: 2928-2933.

Diffenbaugh, N.S. Swain, D.L., Touma, D. 2015. Anthropogenic warming has increased drought risk in California. PNAS. 112(13): 3931-3936.

Doerr, S.H. and Santín, C. 2016. Global trends in wildfire and its impacts: perceptions versus realities in a changing world. Phil. Trans. R. Soc. B. 371: 20150345.

Fauria, M.M. and Johnson, E.A. 2008. Climate and wildfires in the North American boreal forest. Phil. Trans. R. Soc. B. 363: 2317-2329.

Giglio, L., Randerson, J.T., van der Werf, G.R. 2013. Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). Journal of Geophysical Research: Biogeosciences. 118: 317-328.

IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.

Irland, L.C. 2013. Extreme value analysis of forest fires from New York to Nova Scotia, 1950-2010. Forest  Ecology and Management. 294: 150-157.

Jolly, W.M., Cochrane, M.A., Freeborn, P.H., Holden, Z.A., Brown, T.J., Williamson, G.J., Bowman, D.M.J.S. Climate-induced variations in global wildfire danger from 1979 to 2013. Nature Communications. 6: 7537. DOI: 10.1038/ncomms8537.

Littell, J.S., McKenzie, D., Peterson, D.L., Westerling, A.L. 2009. Climate and wildfire area burned in western U.S. ecoprovinces, 1916-2003. Ecological Applications. 19(4): 1003-1021.

Littell, J.S., Peterson, D.L., Riley, K.L., Liu, Y., Luce, C.H. 2016. A review of the relationships between drought and forest fire in the United States. Global Change Biology. 22: 2353-2369.

Melillo, Jerry M., Terese (T.C.) Richmond, and Gary W. Yohe, Eds., 2014: Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 841 pp. doi:10.7930/J0Z31WJ2.

Moritz, M.A., Parisien, M-A., Batllori, E., Krawchuk, M.A., Van Dorn, J., Ganz, D.J., Hayhoe, K. 2012. Climate change and disruptions to global fire activity. Ecosphere. 3(6):49.

Pausas, J.G., Fernández-Muñoz, S. 2012. Fire regime changes in the Western Mediterranean Basin: from fuel-limited to drought-driven fire regime. Climatic Change. 110: 215-226.

Pechony, O., Shindell, D.T. 2010. Driving forces of global wildfires over the past millennium and the forthcoming century. PNAS. 107(45): 19167-19170.

Steel, Z.L., Safford, H.D., Viers, J.H. 2015. The fire frequency-severity relationship and the legacy of fire suppression in California forests. Ecosphere. 6(1): Article 8, 23pp.

Urbieta, I.R., Zavala, G., Bedia, J., Gutiérrez, J.M., San Miguel-Ayanz, J., Camia, A., Keeley, J.E., Moreno, J.M. 2015. Fire activity as a function of fire-weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA. Environ. Res. Lett. 10:114013.

Westerling, A.L. 2016. Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring. Phil. Trans. R. Soc. B. 371: 20150178.

Westerling, A.L., Hidalgo, H.G., Cayan, D.R., Swetnam, T.W. 2006. Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity. Science. 313: 940-943.

Whitlock, C., Higuera, P.E., McWethy, D.B., Briles, C.E. 2010. Paleoecological Perspectives on Fire Ecology: Revisiting the Fire-Regime Concept. The Open Ecology Journal. 3: 6-23.

Resiliency Assessment Framework

(click here to download a pdf of this complete article)

By Eric Walberg


Optimizing forest management to account for the risks and opportunities posed by climate change is a challenge on many fronts. Limitations in the precision of climate models, uncertainties about natural system response, and the need to integrate climate concerns with other aspects of forest management are all complicating factors.

To better position CSLN members to respond to these risks and opportunities Manomet is proposing the development of a monitoring and management system that we are calling the Resiliency Assessment Framework (RAF). The RAF will track changing regional climate and forest conditions and allow CSLN members to evaluate conditions on their lands in light of the changing regional context. This approach is intended to support the inclusion of climate concerns in forest management plans by providing an opportunity to link management decision points to the data inputs from the RAF.

The RAF will be an optional component of the CSLN and will be intentionally structured to minimize additional work load and maximize utility in improving forest management. While many research questions associated with climate change and forest response might be addressed by this type of monitoring framework, our goal is a system that will maximize forest health and productivity.

Proposed Program Structure

The RAF will consist of three major components:

  • climate-science-center-regionsAssessment and Tracking of Changing Regional Context: Manomet will develop a synopsis of climate change and forest response trends and projections for each of the six regions associated with the U.S. Climate Science Centers.
  • Local Monitoring and Evaluation: Participating CSLN members will establish or augment an existing monitoring program to document changing forest conditions on the lands that they manage and support comparison of local and regional forest conditions.
  • Climate Component for Forest Management Plans: Participating CSLN members will develop a climate change component in their forest management plans that links to the monitoring data generated by the RAF.

The majority of the regional data will come from public sources and will be based on research that is already underway or just being started. The frequency and extent of data collection on local forest conditions will be at the discretion of participating CSLN members.

Initial Development, Testing and Evaluation in New England

Initial development of the RAF will take place as a pilot effort in New England over the next year. Manomet will begin the process by developing a regional trends and projections report for the Northeast region and by working with participating CSLN members with land holdings in New England to develop and test local monitoring protocols and draft climate components for forest management plans. Assuming that the pilot phase is successful, the RAF will be expanded region by region in following years.

Questions the RAF Will Address

The two overarching questions that the RAF is intended to address are:

  • How are climate conditions changing by region and site?
  • How are forest conditions changing in response?

Through the pilot phase of the project Manomet will work with CSLN members to develop a set of specific research questions. As previously stated, the intent is to strike a balance between level of effort and utility in improving forest management. Examples of the type of specific questions that might be posed include:

  • Is a warming climate increasing growth rates for particular tree species?
    • Possible regional climate metrics: change in length of growing season, change in average annual temperature, range of seasonal temperatures
    • Possible regional forest metrics: FIA forest growth rates by species
    • Possible local forest metrics: growth rates by species
  • How is the frequency and severity of drought changing and are there discernable forest impacts?
    • Possible regional climate metrics: PDSI (Palmer Drought Severity Index), SPI (Standardized Precipitation Index), soil moisture, VPD (Vapor Pressure Deficit)
    • Possible regional forest metrics: Remote sensing of forest health and mortality, FIA forest health metrics, FIA tree mortality data, canopy water content
    • Possible local forest metrics: tree crown condition, tree mortality
  • How is temperature variability changing and is there a discernable forest response?
    • Possible regional climate metrics: frequency of freeze/thaw events, range of seasonal temperatures, frequency of false springs
    • Possible regional forest metrics: Remote sensing of frost damage following leaf out, FIA forest health metrics, FIA forest growth rates
    • Possible local forest metrics: tree crown condition, growth rates
  • Are storm events changing in frequency and intensity and what is the forest response?
    • Possible regional climate metrics: maximum wind speed, frequency of threshold wind exceedance, persistence of storm systems
    • Possible regional forest metrics: FIA forest health metrics, FIA tree mortality data, wind throw
    • Possible local forest metrics: tree crown condition, wind throw

Obvious challenges exist in differentiating climate impacts from the many other factors that influence forest health and productivity. However, as climate change progresses it is likely that climate-related factors will become more prominent forest stressors and will therefore be more readily identifiable. For example, recent studies of the impact of “hot drought” on forests in the western U.S. have identified a climate change component in the excessive heat that has exacerbated tree mortality. The RAF can potentially serve as an early warning system and hopefully will provide insight on emerging factors in forest health and changing competitiveness of particular tree species.

Measures of Success

Key measures of success for the RAF include the following considerations:

  • Does implementation of the RAF result in forest management insight would not occur in its absence?
  • Is the RAF worth the investment of time and energy?
  • Does the RAF improve understanding of how climate change is impacting forests?
  • Does the RAF provide a mechanism for engagement and education on climate change?
  • Over the long term, does the RAF result in improved forest health and resiliency?

Once the pilot phase is underway it will be possible to identify more specific measures of success associated with specific research questions.

The next step in this process will be a survey of CSLN members to get a better idea of what you are currently doing in the way of forest monitoring and to take a first cut at identifying priority research questions. The survey results will be discussed at the October 26, 2016 CSLN member gathering in Boston.

Climate Change & Forest Productivity

By Jennifer Hushaw

Considerable attention has been paid to understanding how climate change may alter the abundance and distribution of tree species, as discussed in our previous bulletin on modeling future forests, but an equally important consideration is how climate change may alter productivity. Research suggests climate change has the potential to affect not just where, but how well our forests grow. This bulletin highlights recent work by researchers at Virginia Tech, University of Maine, the US Forest Service, and others that estimates how productivity may shift as a result of changing climate.

Productivity & Site Index

One measure of potential forest productivity is site index—defined as the average total height (in meters) that dominant and co-dominant trees attain at a specified base age in even-aged stands. Of course, this is based on the assumption that forests are even-aged and consist of a single species, which can be problematic in regions dominated by uneven-aged, mixed species stands, such as the eastern US. However, it is a commonly used metric that provides some utility. Researchers have responded to these known limitations by attempting to predict observed site index using site attributes like climate, topography, and soil characteristics.

Study Overview

In a recent study published in the Canadian Journal of Forest Research (Jiang et al. 2015), researchers created models to predict site index (base age 50) for 20 eastern tree species (as well as hardwoods and conifers generally*) based on 15 soil and 37 climate variables. The models successfully predicted current site index values observed through USFS Forest Inventory and Analysis (FIA) data, which provides confidence in their ability to accurately represent on-the-ground conditions. Then they were re-run with future, rather than contemporary, climate data to estimate how site index would change under projected future conditions.

They utilized vegetation and site index data from the FIA program, contemporary (1961 to 1990) and future (2030, 2060, and 2090) climate data from the USFS Rocky Mountain Research Station representing four different future emissions scenarios, and soils data from the USDA Soil Survey Geographic (SSURGO) database.

The models were developed using a statistical technique (Random Forests—a classification and regression tree analysis) that has been shown to be very adept at analyzing these types of research questions and datasets. With the analysis they employed, they were also able to calculate confidence intervals to determine if the predicted changes in site index were significant or not.


Researchers used all climate and soil variables to generate the following maps (to ensure maximum predictive accuracy) and they found that site index may increase or decrease in the future, depending on the species and the geographic region in question. Site index models were generated for individual species, as well as two broad species groups (hardwood and conifer), but only the species-group results were reported.


Key Findings

Current site index:
  • There was more variation in observed site index for conifers than hardwoods across the eastern US.
  • The models that performed best at predicting site index included BOTH climate and soils data.
  • Models that used only climate data to predict site index performed better than those using soils alone.
  • Variables that were useful for predicting site index included:
    • Soil pH
    • Effective soil depth (especially for conifers)
    • Total available soil water capacity
    • Ratio of summer precipitation to total precipitation
    • Summer-winter temperature differential
    • Growing-season precipitation (April—September)
  • For conifers, current site index showed a pattern of increasing from north to south.
  • For hardwoods, current site index showed a pattern of increasing from north and west to southeast.
Future Site Index:
  • For conifers, there was a significant increase in average site index (+0.5 – +2.4m) over the 21st
  • For hardwoods, there was a significant decrease in average site index (up to -1.7m) over the 21st
  • Several regions showed contrasting results depending on the climate change scenario.
  • Variables that were important for determining future changes in site index were related to:
    • The ratio of growing-degree-days to summer precipitation
    • The start and length of the frost-free season
    • Average and accumulated growing-season temperatures
    • Changes in moisture index or summer temperatures in combination with changes in midwinter ambient temperatures
  • Under the lowest emissions scenario, more FIA plots showed a significant increase in site index and fewer showed a significant decrease, whereas the higher emissions scenarios consistently showed the opposite result—suggesting that there may be some overall benefit for forest productivity under moderate warming that disappears under higher levels of warming.


This study is an example of the research being done to better understand how changing climate conditions will alter forest productivity. A key take-home is how different the forest response can be depending on the rate and level of warming, which is also a key area of uncertainty. This highlights the important ramifications of different climate trajectories and suggests that forest managers may want to keep their eye on those trends over time. In some cases, it may be beneficial to shift the species mix toward those projected to experience an increase in site index. However, these results should also be considered in conjunction with other research related to potential productivity changes, such as growth increases due to CO2 fertilization or decreases due to extreme heat events. We will continue to monitor new and emerging research on this topic going forward.


Note: For those interested in a similar analysis for western US tree species, please see a paper by Weiskittel et al (2011) entitled Linking climate, gross primary productivity, and site index across forests of the western United States.

* Species comprising the hardwood and conifer species groups in this analysis:

Hardwood Conifer
White oak Loblolly Pine
Yellow poplar Shortleaf Pine
Quaking aspen Eastern white pine
Northern red oak Balsam fir
Sugar maple Red pine
Red maple Slash pine
Black oak Black spruce
White ash Tamarack (native)
Green ash N. white cedar
Sweetgum Virginia pine


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Jiang, H., Radtke, P.J., Weiskittel, A.R., Coulston, J.W., Guertin, P.J. 2015. Climate- and soil-based models of site productivity in eastern US tree species. Can. J. For. Res. 45: 325-342.

Weiskittel, A.R., Crookston, N.L., Radtke, P.J. 2011. Linking climate, gross primary productivity, and site index across forests of the western United States. Can. J. For. Res. 41: 1710-1721.



Carbon Markets and Forests: What Does the Future Hold?

(click here to download a pdf of this complete article)

By Eric Walberg


Global efforts to reduce carbon emissions are ramping up and carbon markets will play an increasingly important role in limiting warming to the 2 degree C ceiling established by the Paris Climate Agreement.  I participated in the largest annual North American carbon market conference in San Diego, CA, May 4-6, 2016. The California Cap and Trade system formed the backdrop for many of the sessions, but the conference drew international participants and presentations covered a range of global topics. Recurrent themes included the impact of the Paris Climate Accord, the future of the California carbon market, linkages between the California Cap and Trade system and other sub-national programs, the future of the Clean Power Plan, and possible inclusion of Reducing Emissions from Deforestation and Forest Degradation (REDD) projects in the California market.

What are the opportunities and ramifications for the forestry sector? What role will forests play in meeting the national commitments associated with the Paris agreement? This month’s bulletin is an exploration of those questions as informed by the presentations and discussions at the conference.

Key Themes from the Conference


The ramifications of the December 2015 Paris Climate Agreement were discussed in several of the sessions. The general consensus is that the Agreement sends a positive signal for global expansion of carbon pricing, regulations, compliance markets, and voluntary markets in efforts to limit warming to the 2 degree C goal. The Paris Agreement establishes a bare bones framework for the creation of new international carbon markets and cooperative approaches to reducing greenhouse gas emissions.  The high-level framing in Article 6 of the Agreement (see hyperlink pg. 23) must be fleshed out before the nature of the resulting markets and cooperative agreements becomes clear.  It is too early to know what opportunities for the forestry sector might result.

A related topic in these discussions was the tremendous need for additional capital to finance the conversion to a green economy. Additional regulation and/or establishment of a price on carbon were two methods discussed to drive capital towards needed solutions. Green bonds are also seen as a growth area with some early indications of investor preference for green bonds driving higher prices in the secondary market.  China is poised to have a major impact as they establish a national cap and trade system in 2017 and become a major issuer of green bonds. Market commentators estimate that China’s green bond market could be worth $230 billion in the next five years.


The California Cap and Trade system appears to have addressed many of the fundamental flaws of earlier systems. A price floor in the offset market has created demand and stability. Rigorous project review on the part of the California Air Resources Board has created investor confidence, but has also created significant hurdles for offset project developers. Thus far, the bulk of the emission reductions in California have been driven by actions within capped sectors (to reduce emissions), rather than through purchase of offset credits from non-capped sectors such as forestry. The California system continues to function as a laboratory of innovation and will influence international efforts to fulfill the Paris Agreement.

The initial enabling legislation (AB32) established the program through 2020 and efforts to extend the cap and trade framework are underway in the California legislature. The general sense from the conference discussions is that that program will be extended, but will likely be modified in the process. The program also faces a lawsuit by the California Chamber of Commerce (CCC). A state judge rejected the assertion by the CCC that the program is an illegal tax, but an appeal is pending.


Forest offset projects account for the majority of offset projects approved in the California Cap and Trade system so far. Three categories of forest offset projects are possible: (1) afforestation, (2) avoided conversion, and (3) improved forest management. Thus far, the majority of the approved projects are in the improved forest management category. Several sessions touched on the notion of “charismatic” carbon credits—projects that bring co-benefits such as flood control and water quality protection. It is not clear if this is a factor in the prevalence of forest offset projects in the compliance market.

One of the sessions included an in-depth discussion of areas of risk associated with forest offset projects and how parties attempt to allocate that risk in contract negotiations. The five areas of risk were: (1) the possibility of credit invalidation, (2) failure to deliver a successful project, (3) reversal of a project, (4) land restrictions associated with projects, and (5) price*.

  • Invalidation of a project is a risk during the first eight years of a project and could result from a material misstatement (greater than 5%) of the carbon sequestration value of a project, failure to comply with all relevant environmental, health and safety laws, or double dipping (selling the same offsets into multiple programs).
  • Project delivery failure could be associated with multiple causes such as insolvency, failure to meet statutory deadlines, negligence, etc.
  • Reversal could be due to unintentional causes such as fire or wind storm, or intentional causes such as negligence or willful intent. In the event of an unintentional reversal the credits are covered by a buffer pool maintained by the California Air Resources Board. In the case of intentional reversal the owner is responsible for replacing the credits.
  • Land restrictions are primarily to meet the carbon sequestration goals associated with the contract. Harvesting is permitted as long as carbon sequestration goals are met. The land can be transferred but subsequent owners must assume all carbon responsibilities. A second category of land restrictions are those associated with compliance with the previously mentioned environmental, health and safety laws.
  • Price concerns include both the market value of the credits and the contractual allocation of risk and financial reward among all of the parties involved in assembling an offset project.

*Source: From a presentation entitled: “The Art of the Deal: Legal Considerations with Carbon Projects” by Erika Anderson of Anderson Law on May 4, 2016 at the Navigating the American Carbon World conference in San Diego, California.


The California Cap and Trade system is a hub for a growing network of sub-national entities that are linking their markets. The Western Climate Initiative (WCI) was launched in 2007 to evaluate and implement policies to tackle climate change. Membership of the WCI includes California, Washington, Oregon, Arizona, New Mexico, Montana, Utah, British Columbia, Manitoba, Ontario, and Québec. Building on the WCI, California and Québec completed an agreement in 2013 linking their programs. Ontario has indicated that they will be next to link their program.

In a parallel effort, California began engaging on REDD through the creation of the Governors’ Climate and Forest Task Force in 2008. This subnational government initiative is a network and forum focused on forest conservation, climate mitigation, and exploring linkage between REDD programs and the California Cap and Trade system. This process resulted in development of a 2010 Memorandum of Understanding between California, Acre, Brazil, and Chiapas, Mexico to assess the details associated with program linkage. Technical and policy recommendations were developed by a team of experts and delivered to all three of the partners in 2013. It is not yet clear when this process might result in formal linkage of REDD projects with the California market or exactly what form that linkage would take.

Challenges and Opportunities for the Forestry Sector

As signatory nations strive to meet the emission reduction goals associated with the Paris Agreement it is certain that afforestation, forest protection, and enhanced forest management will be key features of national programs. Given the prominent role that forest offset projects play in the California Cap and Trade system it is reasonable to assume that forest offsets will be included in other markets. Regulatory change and/or establishment of a price on carbon will likely increase the value of the climate regulation services provided by forests. The following are my thoughts on the challenges and opportunities for the forestry sector based on the conference discussions.

  • Participation in the California offset market: Barring a successful legal challenge to the program or significant regulatory change, the opportunity for forest offset projects in the California market will continue to be the most tangible and immediate opportunity for the forestry sector in the compliance market. Opportunities for offset projects will continue to exist in the voluntary market, but it is not likely that prices will rival those offered in the compliance market.
  • REDD offset market: Early indications are that, if and when REDD projects enter the California market, the only project categories that will be approved are afforestation and reforestation. It is possible that enhanced forest management projects will eventually be included pending a successful pilot period with afforestation and reforestation projects.
  • Possible inclusion of biomass energy and/or forest offsets in programs that develop in response to the Clean Power Plan: Given the legal challenges to the CPP it is difficult to know if the draft regulatory language will survive intact. If the existing framework does move forward it appears that the use of biomass energy will be available to states as one element of transition to renewable energy portfolios. The details of the carbon accounting and economics associated with biomass under the CPP are not known at this point. It does not appear likely that forest offset projects will be accepted by EPA as a substitute for reducing emissions from existing power generation facilities, but it is possible that carbon markets that develop in response to the CPP could include forest offsets in a broader context.
  • Regional Greenhouse Gas Initiative (RGGI) forest offsets: A 2014 reduction in the RGGI emissions cap by 45% resulted in renewed interest in the market and allowance prices have increased from $2.80 in March of 2013 to $7.05 in December of 2015, with a drop to $5.25 in March of 2016. These prices have not been high enough to foster demand for offset projects but that could change in the future if allowance prices rise.
  • Competitive advantage for wood building materials: Regulatory change and carbon pricing will likely increase the expense of competing materials with a larger carbon footprint, such as concrete and steel.
  • Increased efforts to reduce deforestation in the tropics: These efforts may reduce opportunities for commercial forestry operations in the tropics and could result in increased demand for forest products from temperate zones.
  • REDD and related projects: New commercial opportunities may emerge for sustainable forestry and agroforestry as a component of REDD projects and other efforts to comply with the Paris Agreement.

Manomet will continue to monitor developments in the policy realm and carbon markets and will report back to Climate Smart Land Network members on an as needed basis.

Modeling Future Forests

(click here to download a pdf of the full article or a one-page synopsis)

By Jennifer Hushaw

Understanding how forests responded to past changes in the Earth’s climate has been a long-standing area of research, but in recent years there has also been growing interest in anticipating how modern climate change may lead to shifts in tree species abundance and distribution. Of course, climate is just one of many factors that determine why trees grow where they grow, including soils, competition, land-use history, and synergistic relationships with other species, e.g. seed dispersers. Partly as a result of this complexity, there is a lot of uncertainty in the results of vegetation models that estimate future habitat suitability or distribution of tree species.

Two things we can say for sure are that (1) tree species will respond independently to changing conditions, so we may see novel species associations and forest types in some locations in the future and (2) there will be significant time lags in forest response (see box, right).

In this bulletin, we briefly review several modeling efforts and how they compare, as well as highlighting potential limitations and best practices for utilizing the results.

Vegetation Models: An Overview

The vegetation models used to assess potential tree species shifts can be broadly sorted into two categories on either end of a spectrum, from empirical (i.e. statistical) to process-based (i.e. mechanistic) models.

Empirical models quantify statistical relationships between species occurrence data, such as plot data from the US Forest Service Forest Inventory and Analysis (FIA), and relevant environmental variables, such as soils and climate, then use those correlations to project into the future. These are often referred to as species distribution models, niche models or bioclimatic envelope models.

Example: DISTRIB, the core model used in development of the Climate Change Tree Atlas (see table below), uses a statistical approach known as regression tree analysis to define the ecological niche of a species based on (1) a series of climate, soil, elevation, and landuse predictor variables and (2) data from FIA about the relative abundance of a species in the overstory. More specifically, it utilizes a relatively new ensemble data-mining technique called Random Forests, which has some improvements that are designed to avoid “overfitting” the data. For more detail on the technique read this paper by Prasad et al 2006. Based on these results, the model has been used to map where the habitat (in terms of climate conditions, soil characteristics, etc.) is suitable for a particular species now and in the year 2100. This tells us something about how likely a species is to persist in particular area.

Note: In the future, the Climate Change Tree Atlas will use DISTRIB in conjunction with a simulation model called SHIFT to go beyond predictions of future suitable habitat and estimate actual species movement in terms of the likelihood of colonization.

Process-based models are generally more complex because they simulate the actual underlying processes, such as disturbance, growth, and regeneration. Forest gap models, ecosystem models, forest landscape models, and dynamic global vegetation models (DGVMs) fall under this category.

Example: LANDIS PRO is a spatially explicit forest landscape model that simulates processes at the species- (e.g. growth, seedling establishment, mortality), stand- (e.g. competition, stand development), and landscape-scale (e.g. disturbance from fire, insects, harvest, etc.). By “growing” the forests in this way, LANDIS can be used to compare species in the future under a climate change and no climate change scenario. This tells us something about how likely a species is to become established in a particular area.

These categories are not mutually exclusive and there are an increasing number of hybrid approaches used in research. Nor is one approach necessarily better than another—each has its strengths and weaknesses depending on scale, data availability, and the particular research question. A helpful summary of key differences is below:

For more detailed information on this topic, we recommend visiting the Landscape Analysis section of the US Forest Service Climate Change Resource Center website.

Table 1 in this paper by Littell et al (2011) also has a useful comparison of the strengths and weaknesses of different types of empirical and process models, for reference.

Model Comparison

The table below compares several modeling efforts that estimate changes in habitat suitability or distribution for U.S. tree species under future climate change. Model names are hyperlinks that take you to the project website where you can view results, including maps (in some cases), for different species. This table is intended to help forest managers quickly navigate to existing projections of species shift and weigh the merits and characteristics of each approach.

Comparing the results from different models reveals whether they generally agree (lending greater confidence) or disagree on the outlook for particular species. Some of this work is being carried out by the US Forest Service through their on-going series of Vulnerability Assessments (see final row in the table below) and the CSLN will alert Network members to similar comparative efforts as they arise.

Best Practices

Models incorporate imperfect information and are a simplified version of reality, but by understanding these imperfections, we can use models to decrease the uncertainty associated with the future.” ~ Littell et al 2011

  • Remember there will be significant time lags.
  • Consider projections for individual species, rather than forest types.
  • Use models to help reduce uncertainty about the future by identifying potential surprises and vulnerabilities1, potential magnitude of effects, and insight into mechanisms.2
  • Use more than one type of model (wherever possible) to assess likely vegetation shifts1—we can have greater confidence where different models agree.
  • Understand the assumptions in a given model and the implications of those assumptions.1
  • Use MODFACs, a decision support framework that scores adaptability for different tree species, in conjunction with models to determine whether a species is likely to fare better or worse than modeled projections.
  • Mistake maps of habitat suitability for depictions of where a tree species will actually be growing at that point in the future.
  • Use model projections as exact predictions of what will happen with future forest shifts.

1 Littell et al 2011    2 Kerns & Peterson 2014

Click the image to open a pdf of the model comparison table (with live hyperlinks):



Underestimating Adaptability

As we noted in a previous bulletin, there are some limitations associated with modeling efforts that rely on statistical relationships between environmental variables and current species distributions derived from FIA data (i.e. the realized niche), since that represents only a portion of the possible conditions under which a species could grow (i.e. the fundamental niche). Revisit part of our July 2015 bulletin on uncertainty and forest response for a brief explanation of how the absence of data on the fundamental niche can lead to underestimating the potential adaptability of some tree species. This is not to say that forests aren’t vulnerable in other ways, such as increasing damage from exotic pests and extreme weather, but they may be more adaptable in terms of temperature tolerance than some results suggest.

Take-Home Message

As an initial step, we recommend CSLN members spend a little time perusing the results of the modeling efforts listed above, to get a sense for the general outlook for species that dominate their economic or management concerns. Noting where (and if) the models agree can highlight potential areas of vulnerability (or opportunity) to be explored further. Members who have an interest in digging-in on projections for a particular species, can contact the CSLN staff for additional assistance.

All the modeling efforts agree on at least one thing—conditions are going to change. Most tree species will begin to experience novel climate conditions in some portion of their range and, in some cases, that may lead to local extirpation. Ultimately, the uncertainty is in knowing exactly where and when these species distribution shifts will happen. Generally, we expect species range expansion at the leading edge, in northern and higher elevations, and range contraction at the trailing edge, in southern and low-altitudinal limits. In particular, look for initial forest composition changes at range margins because it is regeneration success or failure there that will determine whether a species persists or migrates.


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Adams, H.D., Williams, A.P., Chonggang, X., Rauscher, S.A., Jiang, X., McDowell, N.G. 2013. Empirical and process-based approaches to climate-induced forest mortality models. Frontiers in Plant Science. 4 (438):5pp.

Iverson, L.; McKenzie, D. (February, 2014). Climate Change and Species Distribution. U.S. Department of Agriculture, Forest Service, Climate Change Resource Center.

Kerns, B.; Peterson, D.W. (May, 2014). An Overview of Vegetation Models for Climate Change Impacts. U.S. Department of Agriculture, Forest Service, Climate Change Resource Center.

Littell, J.S., McKenzie, D., Kerns, B.K., Cushman, S., Shaw, C.G. 2011. Managing uncertainty in climate-driven ecological models to inform adaptation to climate change. Ecosphere. 2(9): 102.

Loarie, S.R., Duffy, P.B., Hamilton, H., Asner, G.P., Field, C.B., Ackerly, D.D. 2009. The velocity of climate change. Nature. 462:1052-1055.

Pearson, R.G. 2006. Climate change and the migration capacity of species. Trends in Ecology and Evolution. 21(3):111-113.