• Energy Research

These data were compiled to provide gridded estimates of environmental suitability for pinyon-juniper species in western North America. These gridded suitability projections provide estimates of suitability under current climate conditions and future climate conditions and allow for visualization of suitability change across each species’ entire range. These data consist of gridded projected suitability values for three pinyon and six juniper tree species across western North America. Objective(s) of our study were to estimate suitability for these tree species under current and future climate conditions to compare potential for distribution shifts under climate change. These data represent a relationship between tree occurrences on the landscape and the climatic and soil conditions in which they occur. These data were created from species distribution models that used occurrence data publicly available online. These underlying occurrence data used to fit our models was gathered from USFS Forest Inventory and Analysis program, BLM's Assessment, Inventory and Monitoring program, the Global Biodiversity Information Facility and SEINet, a shared collection of western herbarium data records. Occurrence data were combined with environmental predictor data to fit species distribution models that then estimate landscape suitability under current and future climate conditions. These data can be used to assess how tree species' suitability may change under future climate conditions.

AbstractPinyon–juniper (PJ) woodlands are an important component of dryland ecosystems across the US West and are potentially susceptible to ecological transformation. However, predicting woodland futures is complicated by species‐specific strategies for persisting and reproducing under drought conditions, uncertainty in future climate, and limitations to inferring demographic rates from forest inventory data. Here, we leverage new demographic models to quantify how climate change is expected to alter population demographics in five PJ tree species in the US West and place our results in the context of a climate adaptation framework to resist, accept, or direct ecological transformation. Two of five study species, Pinus edulis and Juniperus monosperma, are projected to experience population declines, driven by both rising mortality and decreasing recruitment rates. These declines are reasonably consistent across various climate futures, and the magnitude of uncertainty in population growth due to future climate is less than uncertainty due to how demographic rates will respond to changing climate. We assess the effectiveness of management to reduce tree density and mitigate competition, and use the results to classify southwest woodlands into areas where transformation is (a) unlikely and can be passively resisted, (b) likely but may be resisted by active management, and (c) likely unavoidable, requiring managers to accept or direct the trajectory. Population declines are projected to promote ecological transformation in the warmer and drier PJ communities of the southwest, encompassing 37.1%–81.1% of our sites, depending on future climate scenarios. Less than 20% of sites expected to transform away from PJ have potential to retain existing tree composition by density reduction. Our results inform where this adaptation strategy could successfully resist ecological transformation in coming decades and allow for a portfolio design approach across the geographic range of PJ woodlands.

AbstractThe combination of climate change and altered disturbance regimes is directly and indirectly affecting plant communities by mediating competitive interactions, resulting in shifts in species composition and abundance. Dryland plant communities, defined by low soil water availability and highly variable climatic regimes, are particularly vulnerable to climatic changes that exceed their historical range of variability. Individual‐based simulation models can be important tools to quantify the impacts of climate change, altered disturbance regimes, and their interaction on demographic and community‐level responses because they represent competitive interactions between individuals and individual responses to fluctuating environmental conditions. Here, we introduce STEPWAT2, an individual plant‐based simulation model for exploring the joint influence of climate change and disturbance regimes on dryland ecohydrology and plant community composition. STEPWAT2 utilizes a process‐based soil water model (SOILWAT2) to simulate available soil water in multiple soil layers, which plant individuals compete for based on the temporal matching of water and active root distributions with depth. This representation of resource utilization makes STEPWAT2 particularly useful for understanding how changes in soil moisture and altered disturbance regimes will concurrently impact demographic and community‐level responses in drylands. Our goals are threefold: (1) to describe the core modules and functions within STEPWAT2 (model description), (2) to validate STEPWAT2 model output using field data from big sagebrush plant communities (model validation), and (3) to highlight the usefulness of STEPWAT2 as a modeling framework for examining the impacts of climate change and disturbance regimes on dryland plant communities under future conditions (model application). To address goals 2 and 3, we focus on 15 sites that span the spatial extent of big sagebrush plant communities in the western United States. For goal 3, we quantify how climate change, fire, and grazing can interact to influence plant functional type biomass and composition. We use big sagebrush‐dominated plant communities to demonstrate the functionality of STEPWAT2, as these communities are among the most widespread dryland ecosystems in North America.

AbstractRegeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush (Artemisia tridentata) after disturbances including fire‐invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long‐lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range‐wide big sagebrush regeneration responses in natural vegetation (process‐based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression‐based model). The process‐based model suggested substantial geographic variation in long‐term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression‐based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long‐term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re‐creating conditions of uninvaded, unburned natural big sagebrush vegetation for post‐fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire‐invasive annual grass cycle.

AbstractChanges 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.

Significance Do forests in cold or dry climate zones distribute more resources in roots to enhance uptake of water and nutrients, which are scarce in such climates? Despite its importance to forest ecology and global carbon cycle modeling, this question is unanswered at present. To answer this question, we compiled and analyzed a large dataset (>6,200 forests, 61 countries) and determined that the proportion of total forest biomass in roots is greater and in foliage is smaller in increasingly cold climates. Surprisingly, allocation to roots or foliage was unrelated to aridity. These findings allow, for the first time to our knowledge, biogeographically explicit mapping of global root carbon pools, which will be useful for assessing climate change impacts on forest carbon dynamics and sequestration.

Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. We provide GeoTIFFs of biome-wide projections of future sagebrush ecological integrity (as described in Holdrege et al., 2024) under two representative concentration pathways (RCP4.5 and RCP8.5) and time-periods (2031-2060 and 2071-2100) and we provide these projections for multiple model assumptions. Additionally, this data set provides accompanying projections of three of the components of sagebrush ecological integrity, which are the Q (‘quality’, see Doherty et al., 2022) scores for sagebrush, perennial forbs and grasses, and annual forbs and grasses. Additional GeoTIFFs included provide current (2017-2020) Q scores and sagebrush ecological integrity, as well as projected changes in the extent of Core Sagebrush Areas, Growth Opportunity Areas, and Other Rangeland Areas. References: Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022–1081, 38 p., https://doi.org/10.3133/ofr20221081.

AbstractPlant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentataNutt.) plant communities that span 76 million ha in the western United States. We used an individual‐based plant simulation model that represents intra‐ and inter‐specific competition for water availability, which is represented by a process‐based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine‐scale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of −20% to +27%), declines in perennial C3grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C4grasses. The largest declines in big sagebrush, perennial C3grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture‐limited versus temperature‐limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.

AbstractAs global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2concentrations. 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 likeAcer saccharum,Quercus rubra, andPicea glaucawill 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.