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Jane R. Foster

Publications and source records attributed to Jane R. Foster.

5 recordsLinked to original sources

Does habitat or climate change drive species range shifts?

A primary prediction of climate change ecology is that species will track their climate niche poleward and upslope. However, studies have shown species responding in surprising ways. In this study, we aim to understand the impact of global change on species ranges by considering both climate and habitat changes. Using occupancy analysis of acoustic survey data in the mountains of the northeastern United States, we tested specific predictions of range responses to warming (shifting upslope), precipitation change (shifting downslope), and forest composition change (shifting downslope). We found that American red squirrels Tamiasciurus hudsonicus , key nodes in northern North American food webs, are not tracking increasing temperatures upslope, despite substantial warming in recent decades. Structural equation modeling indicates that red squirrel abundance is primarily influenced by red-spruce forest cover, which has shifted downslope with recovery from historical logging and acid deposition. Accounting for the multiple dimensions of global change will enable better predictions and more effective conservation strategies.

Connecticut, Maine, Massachusetts, New Hampshire,

Habitat use as indicator of adaptive capacity to climate change

Aim Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose ( Alces alces ), a charismatic species of conservation and public interest. Location The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusionsOur results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation.

New York, Vermont, New Hampshire, Massachusetts

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Minnesota, Wisconsin

Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO 2 and thereby slow rising CO 2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum , Quercus rubra , and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.

Minnesota

Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality

Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.

Minnesota