Context

Global temperatures are projected to increase and affect forests and wildlife populations. Forest management can potentially mitigate climate-induced changes through promoting carbon sequestration, forest resilience, and facilitated change.

Objectives

We modeled direct and indirect effects of climate change on avian abundance through changes in forest landscapes and assessed impacts on bird abundances of forest management strategies designed to mitigate climate change effects.

Methods

We coupled a Bayesian hierarchical model with a spatially explicit landscape simulation model (LANDIS PRO) to predict avian relative abundance. We considered multiple climate scenarios and forest management scenarios focused on carbon sequestration, forest resilience, and facilitated change over 100 years.

Results

Management had a greater impact on avian abundance (almost 50% change under some scenarios) than climate (<3% change) and only early successional and coniferous forest showed significant change in percent cover across time. The northern bobwhite was the only species that changed in abundance due to climate-induced changes in vegetation. Northern bobwhite, prairie warbler, and blue-winged warbler generally increased in response to warming temperatures but prairie warbler exhibited a non-linear response and began to decline as summer maximum temperatures exceeded 36 °C at the end of the century.

Conclusion

Linking empirical models with process-based landscape change models can be an effective way to predict climate change and management impacts on wildlife, but time frames greater than 100 years may be required to see climate related effects. We suggest that future research carefully consider species-specific effects and interactions between management and climate.

Context

Climate change will have diverse and interacting effects on forests over the next century. One of the most pronounced effects may be a decline in resistance to chronic change and resilience to acute disturbances. The capacity for forests to persist and/or adapt to climate change remains largely unknown, in part because there is not broad agreement how to measure and apply resilience concepts.

Objectives

We assessed the interactions of climate change, resistance, resilience, diversity, and alternative management of northern Great Lake forests.

Methods

We simulated two landscapes (northern Minnesota and northern lower Michigan), three climate futures (current climate, a low emissions trajectory, and a high emissions trajectory), and four management regimes [business as usual, expanded forest reserves, modified silviculture, and climate suitable planting (CSP)]. We simulated each scenario with a forest landscape simulation model. We assessed resistance as the change in species composition over time. We assessed resilience and calculated an index of resilience that incorporated both recovery of pre-fire tree species composition and aboveground biomass within simulated burned areas.

Results

Results indicate a positive relationship between diversity and resistance within low diversity areas. Simulations of the high emission climate future resulted in a decline in both resistance and resilience.

Conclusions

Of the management regimes, the CSP regime resulted in some of the greatest resilience under climate change although our results suggest that differences in forest management are largely outweighed by the effects of climate change. Our results provide a framework for assessing resistance and resilience relevant and valuable to a broad array of ecological systems.

Context

Forest landscapes are increasingly managed for fire resilience, particularly in the western US which has recently experienced drought and widespread, high-severity wildfires. Fuel reduction treatments have been effective where fires coincide with treated areas. Fuel treatments also have the potential to reduce drought-mortality if tree density is uncharacteristically high, and to increase long-term carbon storage by reducing high-severity fire probability.

Objective

Assess whether fuel treatments reduce fire intensity and spread and increase carbon storage under climate change.

Methods

We used a simulation modeling approach that couples a landscape model of forest disturbance and succession with an ecosystem model of carbon dynamics (Century), to quantify the interacting effects of climate change, fuel treatments and wildfire for carbon storage potential in a mixed-conifer forest in the western USA.

Results

Our results suggest that fuel treatments have the potential to ‘bend the C curve’, maintaining carbon resilience despite climate change and climate-related changes to the fire regime. Simulated fuel treatments resulted in reduced fire spread and severity. There was partial compensation of C lost during fuel treatments with increased growth of residual stock due to greater available soil water, as well as a shift in species composition to more drought- and fire-tolerant Pinus jeffreyi at the expense of shade-tolerant, fire-susceptible Abies concolor.

Conclusions

Forest resilience to global change can be achieved through management that reduces drought stress and supports the establishment and dominance of tree species that are more fire- and drought-resistant, however, achieving a net C gain from fuel treatments may take decades.

Context

Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being.

Objective

We addressed how aboveground biomass (AGB) and tree species distribution changed under multiple climate change scenarios (PCM B1, CGCM A2, and GFDL A1FI) in northeastern forests.

Methods

We used the LANDIS PRO forest landscape model to simulate forest succession and tree harvest under current climate and three climate change scenarios from 2000 to 2300. We analyzed the effects of climate change on AGB and tree species distribution.

Results

AGB increased from 2000 to 2120 irrespective of climate scenario, followed by slight decline, but then increased again to 2300. AGB averaged 10 % greater in the CGCM A2 and GFDL A1FI scenarios than the PCM B1 and current climate scenarios. Climate change effects on tree species distribution were not evident from 2000 to 2100 but by 2300 some northern hardwood and conifer species decreased in occurrence and some central hardwood and southern tree species increased in occurrence.

Conclusions

Climate change had positive effects on forest biomass under the two climate scenarios with greatest warming but the patterns in AGB over time were similar among climate scenarios because succession was the primary driver of AGB dynamics. Our approach, which simulated stand dynamics and dispersal, demonstrated that a northward shift in tree species distributions may take 300 or more years.

Context

Interactions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs.

Objectives

We used the mechanistic ecosystem-fire process model FireBGCv2 to model interactions of wildland fire, mountain pine beetle (Dendroctonus ponderosae), and white pine blister rust (Cronartium ribicola) under current and future climates, across three diverse study areas.

Methods

We assessed changes in tree basal area as a measure of landscape response over a 300-year simulation period for the Crown of the Continent in north-central Montana, East Fork of the Bitterroot River in western Montana, and Yellowstone Central Plateau in western Wyoming, USA.

Results

Interacting disturbances reduced overall basal area via increased tree mortality of host species. Wildfire decreased basal area more than beetles or rust, and disturbance interactions modeled under future climate significantly altered landscape basal area as compared with no-disturbance and current climate scenarios. Responses varied among landscapes depending on species composition, sensitivity to fire, and pathogen and beetle suitability and susceptibility.

Conclusions

Understanding disturbance interactions is critical for managing landscapes because forest responses to wildfires, pathogens, and beetle attacks may offset or exacerbate climate influences, with consequences for wildlife, carbon, and biodiversity.

Context

Resilience in fire-prone forests is strongly affected by landscape burn-severity patterns, in part by governing propagule availability around stand-replacing patches in which all or most vegetation is killed. However, little is known about drivers of landscape patterns of stand-replacing fire, or whether such patterns are changing during an era of increased wildfire activity.

Objectives

(a) Identify key direct/indirect drivers of landscape patterns of stand-replacing fire (e.g., size, shape of patches), (b) test for temporal trends in these patterns, and (c) anticipate thresholds beyond which landscape patterns of burn severity may change fundamentally.

Methods

We applied structural equation modeling to satellite burn-severity maps of fires in the US Northern Rocky Mountains (1984–2010) to test for direct and indirect (via influence on fire size and proportion stand-replacing) effects of climate/weather, vegetation, and topography on landscape patterns of stand-replacing fire. We also tested for temporal trends in landscape patterns.

Results

Landscape patterns of stand-replacing fire were strongly controlled by fire size and proportion stand-replacing, which were, in turn, controlled by climate/weather and vegetation/topography, respectively. From 1984 to 2010, the proportion of stand-replacing fire within burn perimeters increased from 0.22 to 0.27. Trends for other landscape metrics were not significant, but may respond to further increases proportion stand-replacing fire.

Conclusions

Fires from 1984 to 2010 exhibited tremendous heterogeneity in landscape patterns of stand-replacing fire, likely promoting resilience in burned areas. If trends continue on the current trajectory, however, fires may produce larger and simpler shaped patches of stand-replacing fire with more burned area far from seed sources.

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

Context

Forests throughout eastern North America continue to recover from broad-scale intensive land use that peaked in the nineteenth century. These forests provide essential goods and services at local to global scales. It is uncertain how recovery dynamics, the processes by which forests respond to past forest land use, will continue to influence future forest conditions. Climate change compounds this uncertainty.

Objectives

We explored how continued forest recovery dynamics affect forest biomass and species composition and how climate change may alter this trajectory.

Methods

Using a spatially explicit landscape simulation model incorporating an ecophysiological model, we simulated forest processes in New England from 2010 to 2110. We compared forest biomass and composition from simulations that used a continuation of the current climate to those from four separate global circulation models forced by a high emission scenario (RCP 8.5).

Results

Simulated forest change in New England was driven by continued recovery dynamics; without the influence of climate change forests accumulated 34 % more biomass and succeed to more shade tolerant species; Climate change resulted in 82 % more biomass but just nominal shifts in community composition. Most tree species increased AGB under climate change.

Conclusions

Continued recovery dynamics will have larger impacts than climate change on forest composition in New England. The large increases in biomass simulated under all climate scenarios suggest that climate regulation provided by the eastern forest carbon sink has potential to continue for at least a century.

Context

Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.

Objectives

We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.

Methods

We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.

Results

Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.

Conclusions

This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.

Context

Due to the spatial heterogeneity of the disturbance regimes and community assemblages along topoclimatic gradients, the response of forest ecosystem to climate change varies at the landscape scale.

Objectives

Our objective was to quantify the possible changes in forest ecosystems and the relative effects of climate warming and fire regime changes in different topographic positions.

Methods

We used a spatially explicit model (LANDIS PRO) combined with a gap model (LINKAGES) to predict the possible response of boreal larch forests to climate and fire regime changes, and examined how this response would vary in different topographic positions.

Results

The result showed that the proportion of landscape occupied by broadleaf species increased under warming climate and frequent fires scenarios. Shifts in species composition were strongly influenced by both climate warming and more frequent fires, while changes in age structure were mainly controlled by shifts in fire regime. These responses varied in the different topographic positions, with forests in valley bottoms being most resilient to climate-fire changes and forests in uplands being more likely to shift their composition from larch-dominant to mixed forests. Such variation in the topographic response may be induced by the heterogeneities of the environmental conditions and fire regime.

Conclusions

Fire disturbance could alter the equilibrium of ecosystems and accelerate the response of forests to climate warming. These effects are largely modulated by topographic variations. Our findings suggest that it is imperative to consider topographic complexities when developing appropriate fire management policies for mitigating the effects of climate change.

Context

No single model can capture the complex species range dynamics under changing climates—hence the need for a combination approach that addresses management concerns.

Objective

A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model—DISTRIB II, a species colonization model—SHIFT, and knowledge-based scoring system—MODFACs, to illustrate a decision support framework.

Methods

Using shortleaf pine (Pinus echinata) and sugar maple (Acer saccharum) as examples, we project suitable habitats under two future climate change scenarios (harsh, Hadley RCP8.5 and mild CCSM RCP4.5 at ~2100) at a resolution of 10 km and assess the colonization likelihood of the projected suitable habitats at a 1 km resolution; and score biological and disturbance factors for interpreting modeled outcomes.

Results

Shortleaf pine shows increased habitat northward by 2100, especially under the harsh scenario of climate change, and with higher possibility of natural migration confined to a narrow region close to the current species range boundary. Sugar maple shows decreased habitat and has negligible possibility of migration within the US due to a large portion of its range being north of the US border. Combination of suitable habitats with colonization likelihoods also allows for identification of potential locations appropriate for assisted migration, should that be deemed feasible.

Conclusion

The combination of these multiple components using diverse approaches leads to tools and products that may help managers make management decisions in the face of a changing climate.

Context

Biodiversity in arid regions is usually concentrated around limited water resources, so natural resource managers have constructed artificial water catchments in many areas to supplement natural waters. Because invasive species may also use these waters, dispersing into previously inaccessible areas, the costs and benefits of artificial waters must be gauged and potential invasion- and climate change-management strategies assayed.

Objectives

We present a network analysis framework to identify waters that likely contribute to the spread of invasive species.

Methods

Using the Sonoran Desert waters network and the American bullfrog (Lithobates catesbeianus)—a known predator, competitor, and carrier of pathogens deadly to other amphibians—as an example, we quantified the structural connectivity of the network to predict regional invasion potential under current and two future scenarios (climate change and management reduction) to identify waters to manage and monitor for invasive species.

Results

We identified important and vulnerable waters based on connectivity metrics under scenarios representing current conditions, projected climate-limited conditions, and conditions based on removal of artificial waters. We identified 122,607 km² of land that could be used as a buffer against invasion and 67,745 km² of land that could be augmented by artificial water placement without facilitating invasive species spread.

Conclusions

Structural connectivity metrics can be used to evaluate alternative management strategies for invasive species and climate mitigation.

Context

Climate change is not occurring over a homogeneous landscape and the quantity and quality of available land cover will likely affect the way species respond to climate change. The influence of land cover on species’ responses to climate change, however, is likely to differ depending on habitat type and composition.

Objectives

Our goal was to investigate responses of forest and grassland breeding birds to over 20 years of climate change across varying gradients of forest and grassland habitat. Specifically, we investigated whether (i) increasing amounts of available land cover modify responses of forest and grassland-dependent birds to changing climate and (ii) the effect of increasing land cover amount differs for forest and grassland birds.

Methods

We used Bayesian spatially-varying intercept models to evaluate species- and community-level responses of 30 forest and 10 grassland birds to climate change across varying amounts of their associated land cover types.

Results

Responses of forest birds to climate change were weak and constant across a gradient of forest cover. Conversely, grassland birds responded strongly to changing climatic conditions. Specifically, increasing temperatures led to higher probabilities of localized extinctions for grassland birds, and this effect was intensified in regions with low amounts of grassland cover.

Conclusions

Within the context of northeastern forests and grasslands, we conclude that forests serve as a possible buffer to the impacts of climate change on birds. Conversely, species occupying open, fragmented grassland areas might be particularly at risk of a changing climate due to the diminished buffering capacity of these ecosystems.

Context

Species are expected to shift their distributions in response to global environmental changes and additional protected areas are needed to encompass the corresponding changes in the distributions of their habitats. Conservation policies are likely to become obsolete unless they integrate the potential impacts of climate and land-use change on biodiversity.

Objectives

We identify conservation priority areas for current and future projected distributions of Iberian bird species. We then investigate the extent to which global change informed priority areas are: (i) covered by existing protected area networks (national protected areas and Natura 2000); (ii) threatened by agricultural or urban land-use changes.

Methods

We use outputs of species distributions models fitted with climatic data as inputs in spatial prioritization tools to identify conservation priority areas for 168 bird species. We use projections of land-use change to then discriminate between threatened and non-threatened priority areas.

Results

19% of the priority areas for birds are covered by national protected areas and 23% are covered by Natura 2000 sites. The spatial mismatch between protected area networks and priority areas for birds is projected to increase with climate change. But there are opportunities to improve the protection of birds under climate change, as half of the priority areas are currently neither protected nor in conflict with urban or agricultural land-uses.

Conclusions

We identify critical areas for bird conservation both under current and climate change conditions, and propose that they could guide the establishment of new conservation areas across the Iberian Peninsula complementing existing protected areas.

Context

The application of regional-level airborne lidar (light detection and ranging) data to characterize habitat patches and model habitat connectivity over large landscapes has not been well explored. Maintaining a connected network of habitat in the presence of anthropogenic disturbances is essential for regional-level conservation planning and the maintenance of biodiversity values.

Objectives

We quantified variation in connectivity following simulated changes in land cover and contrasted outcomes when different conservation priorities were emphasized.

Methods

First, we defined habitat patches using vegetation structural attributes identified via lidar. Second, habitat networks were constructed for different forest types and assessed using network connectivity metrics. And finally, land cover change scenarios were simulated using a series of habitat patch removals, representing the impact of implementing different spatial prioritization schemes.

Results

Networks for different forest structure types produced very different patch distributions. Conservation scenarios based on different schemes led to contrasting changes during land cover change simulations: the scheme prioritizing only habitat area resulted in immediate near-term losses in connectivity, whereas the scheme considering both habitat area and their spatial configurations maintained the overall connectivity most effectively. Adding climate constraints did not diminish or improve overall connectivity.

Conclusions

Both habitat area and habitat configuration should be considered in dynamic modeling of habitat connectivity under changing landscapes. This research provides a framework for integrating forest structure and cover attributes obtained from remote sensing data into network connectivity modeling, and may serve as a prototype for multi-criteria forest management and conservation planning.

Context

Land-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.

Objectives

An innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.

Methods

Founded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.

Results

The dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.

Conclusions

We outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.

Context

Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change.

Objectives

We demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099).

Methods

We produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows.

Results

Climate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change.

Conclusions

In moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.

Context

Integrated conservation decision-making frameworks that help to design or adjust practices that are cognisant of environmental change and adaptation are urgently needed.

Objective

We demonstrate how a landscape vulnerability framework combining sensitivity, adaptive capacity, and exposure to climate change framed along two main axes of concern can help to identify potential strategies for conservation and adaptation decision-making, using a landscape in Madagascar’s spiny forest as a case-study.

Methods

To apply such a vulnerability landscape assessment, we inferred the sensitivity of habitats using temporal and spatial botanical data-sets, including the use of fossil pollen data and vegetation surveys. For understanding adaptive capacity, we analysed existing spatial maps (reflecting anthropogenic stressors) showing the degree of habitat connectivity, matrix quality and protected area coverage for the different habitats in the landscape. Lastly, for understanding exposures, we used climate change predictions in Madagascar, together with a digital elevation model.

Results

The fossil pollen data showed how sensitive arid-adapted species were to past climate changes, especially the conditions between 1000 and 500 cal yr BP. The spatial analysis then helped locate habitats on the two-dimensional axes of concern integrating sensitivity, adaptive capacity and climate change exposure. By identifying resistant, resilient, susceptible, and sensitive habitats to climate change in the landscape under study, we identify very different approaches to integrate conservation and adaptation strategies in contrasting habitats.

Conclusion

This framework, illustrated through a case study, provides easy guidance for identifying potential integrated conservation and adaptation strategies, taking into account aspects of climate vulnerability and conservation capacity.

Context

We address the issue of adapting landscapes for improved insect biodiversity conservation in a changing climate by assessing the importance of additive (main) and synergistic (interaction) effects of land cover and land use with climate.

Objectives

We test the hypotheses that ant richness (species and genus), abundance and diversity would vary according to land cover and land use intensity but that these effects would vary according to climate.

Methods

We used a 1000 m elevation gradient in eastern Australia (as a proxy for a climate gradient) and sampled ant biodiversity along this gradient from sites with variable land cover and land use.

Results

Main effects revealed: higher ant richness (species and genus) and diversity with greater native woody plant canopy cover; and lower species richness with higher cultivation and grazing intensity, bare ground and exotic plant groundcover. Interaction effects revealed: both the positive effects of native plant canopy cover on ant species richness and abundance, and the negative effects of exotic plant groundcover on species richness were greatest at sites with warmer and drier climates.

Conclusions

Impacts of climate change on insect biodiversity may be mitigated to some degree through landscape adaptation by increasing woody native vegetation cover and by reducing land use intensity, the cover of exotic vegetation and of bare ground. Evidence of synergistic effects suggests that landscape adaptation may be most effective in areas which are currently warmer and drier, or are projected to become so as a result of climate change.

Context

Temperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.

Objectives

The goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.

Methods

We conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.

Results

We uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.

Conclusions

Future distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.