Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

Distributional Response of the Rare and Endangered Tree Species Abies chensiensis to Climate Change in East Asia

Globally, increasing temperatures due to climate change have severely affected natural ecosystems in several regions of the world; however, the impact on the alpine plant may be particularly profound, further raising the risk of extinction for rare and endangered alpine plants. To identify how alpine species have responded to past climate change and to predict the potential geographic distribution of species under future climate change, we investigated the distribution records of A. chensiensis, an endangered alpine plant in the Qinling Mountains listed in the Red List. In this study, the optimized MaxEnt model was used to analyse the key environmental variables related to the distribution of A. chensiensis based on 93 wild distribution records and six environmental variables. The potential distribution areas of A. chensiensis in the last interglacial (LIG), the last glacial maximum (LGM), the current period, and the 2050s and 2070s were simulated. Our results showed that temperature is critical to the distribution of A. chensiensis, with the mean temperature of the coldest quarter being the most important climatic factor affecting the distribution of this species. In addition, ecological niche modeling analysis showed that the A. chensiensis distribution area in the last interglacial experiencing population expansion and, during the last glacial maximum occurring, a population contraction. Under the emission scenarios in the 2050s and 2070s, the suitable distribution area would contract significantly, and the migration routes of the centroids tended to migrate toward the southern high-altitude mountains, suggesting a strong response from the A. chensiensis distribution to climate change. Collectively, the results of this study provide a comprehensive and multidimensional perspective on the geographic distribution pattern and history of population dynamics for the endemic, rare, and endangered species, A. chensiensis, and it underscores the significant impact of geological and climatic changes on the geographic pattern of alpine species populations.

Niche divergence at the intraspecific level in an endemic rare peony (Paeonia rockii): A phylogenetic, climatic and environmental survey

Ecological factors have received increasing attention as drivers of speciation but also in the maintenance of postspeciation divergence. However, the relative significance of the responses of species to climate oscillations for driving niche divergence or conservatism in the evolution of many species that pass through diverse environments and limited geographical boundaries remains poorly understood. Paeonia rockii (one of the ancient species of Paeonia) comprising two subspecies called Paeonia rockii subsp. rockii and Paeonia rockii subsp. taibaishanica is an endemic, rare, and endangered medicinal plant in China. In this study, we integrated whole chloroplast genomes, and ecological factors to obtain insights into ecological speciation and species divergence in this endemic rare peony. RAxML analysis indicated that the topological trees recovered from three different data sets were identical, where P. rockii subsp. rockii and P. rockii subsp. taibaishanica clustered together, and molecular dating analyses suggested that the two subspecies diverged 0.83 million years ago. In addition, ecological niche modeling showed that the predicted suitable distribution areas for P. rockii subsp. rockii and P. rockii subsp. taibaishanica differed considerably, although the predicted core distribution areas were similar, where the population contracted in the last interglacial and expanded in the last glacial maximum. Under the emissions scenarios for the 2050s and 2070s, the suitable distribution areas were predicted to contract significantly, where the migration routes of the two subspecies tended to migrate toward high latitudes and elevations, thereby suggesting strong responses of the distributions of the two subspecies to climate change. These findings combined with the phylogeographic relationships provide comprehensive insights into niche variation and differentiation in this endemic rare peony, and they highlight the importance of geological and climatic changes for species divergence and changes in the population geographic patterns of rare and endangered medicinal plants in East Asia.

The consequences of climate change for dryland biogeochemistry

Drylands, which cover > 40% of Earth's terrestrial surface, are dominant drivers of global biogeochemical cycling and home to more than one third of the global human population. Climate projections predict warming, drought frequency and severity, and evaporative demand will increase in drylands at faster rates than global means. As a consequence of extreme temperatures and high biological dependency on limited water availability, drylands are predicted to be exceptionally sensitive to climate change and, indeed, significant climate impacts are already being observed. However, our understanding and ability to forecast climate change effects on dryland biogeochemistry and ecosystem functions lag behind many mesic systems. To improve our capacity to forecast ecosystem change, we propose focusing on the controls and consequences of two key characteristics affecting dryland biogeochemistry: (1) high spatial and temporal heterogeneity in environmental conditions and (2) generalized resource scarcity. In addition to climate change, drylands are experiencing accelerating land-use change. Building our understanding of dryland biogeochemistry in both intact and disturbed systems will better equip us to address the interacting effects of climate change and landscape degradation. Responding to these challenges will require a diverse, globally distributed and interdisciplinary community of dryland experts united towards better understanding these vast and important ecosystems.

Bridging implementation gaps to connect large ecological datasets and complex models

Merging robust statistical methods with complex simulation models is a frontier for improving ecological inference and forecasting. However, bringing these tools together is not always straightforward. Matching data with model output, determining starting conditions, and addressing high dimensionality are some of the complexities that arise when attempting to incorporate ecological field data with mechanistic models directly using sophisticated statistical methods. To illustrate these complexities and pragmatic paths forward, we present an analysis using tree-ring basal area reconstructions in Denali National Park (DNPP) to constrain successional trajectories of two spruce species (Picea mariana and Picea glauca) simulated by a forest gap model, University of Virginia Forest Model Enhanced-UVAFME. Through this process, we provide preliminary ecological inference about the long-term competitive dynamics between slow-growing P. mariana and relatively faster-growing P. glauca. Incorporating tree-ring data into UVAFME allowed us to estimate a bias correction for stand age with improved parameter estimates. We found that higher parameter values for P. mariana minimum growth under stress and P. glauca maximum growth rate were key to improving simulations of coexistence, agreeing with recent research that faster-growing P. glauca may outcompete P. mariana under climate change scenarios. The implementation challenges we highlight are a crucial part of the conversation for how to bring models together with data to improve ecological inference and forecasting.

Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients

Plant 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 tridentata Nutt.) 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 C₃ grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C₄ grasses. The largest declines in big sagebrush, perennial C₃ grass 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.

Dalziell E, Trudgen MS, Bateman AM, Erickson TE. Global change impacts on arid zone ecosystems: Seedling establishment processes are threatened by temperature and water stress

Recruitment for many arid-zone plant species is expected to be impacted by the projected increase in soil temperature and prolonged droughts associated with global climate change. As seed dormancy is considered a strategy to avoid unfavorable conditions, understanding the mechanisms underpinning vulnerability to these factors is critical for plant recruitment in intact communities, as well as for restoration efforts in arid ecosystems. This study determined the effects of temperature and water stress on recruitment processes in six grass species in the genus Triodia R.Br. from the Australian arid zone. Experiments in controlled environments were conducted on dormant and less-dormant seeds at constant temperatures of 25°C, 30°C, 35°C, and 40°C, under well-watered (Ψsoil = -0.15 MPa) and water-limited (Ψsoil = -0.35 MPa) conditions. Success at three key recruitment stages-seed germination, emergence, and survival-and final seed viability of ungerminated seeds was assessed. For all species, less-dormant seeds germinated to higher proportions under all conditions; however, subsequent seedling emergence and survival were higher in the more dormant seed treatment. An increase in temperature (35-40°C) under water-limited conditions caused 95%-100% recruitment failure, regardless of the dormancy state. Ungerminated seeds maintained viability in dry soil; however, when exposed to warm (30-40°C) and well-watered conditions, loss of viability was greater from the less-dormant seeds across all species. This work demonstrates that the transition from seed to established seedling is highly vulnerable to microclimatic constraints and represents a critical filter for plant recruitment in the arid zone. As we demonstrate temperature and water stress-driven mortality between seeds and established seedlings, understanding how these factors influence recruitment in other arid-zone species should be a high priority consideration for management actions to mitigate the impacts of global change on ecosystem resilience. The knowledge gained from these outcomes must be actively incorporated into restoration initiatives.

Forecasting semi-arid biome shifts in the Anthropocene

Shrub encroachment, forest decline and wildfires have caused large-scale changes in semi-arid vegetation over the past 50 years. Climate is a primary determinant of plant growth in semi-arid ecosystems, yet it remains difficult to forecast large-scale vegetation shifts (i.e. biome shifts) in response to climate change. We highlight recent advances from four conceptual perspectives that are improving forecasts of semi-arid biome shifts. Moving from small to large scales, first, tree-level models that simulate the carbon costs of drought-induced plant hydraulic failure are improving predictions of delayed-mortality responses to drought. Second, tracer-informed water flow models are improving predictions of species coexistence as a function of climate. Third, new applications of ecohydrological models are beginning to simulate small-scale water movement processes at large scales. Fourth, remotely-sensed measurements of plant traits such as relative canopy moisture are providing early-warning signals that predict forest mortality more than a year in advance. We suggest that a community of researchers using modeling approaches (e.g. machine learning) that can integrate these perspectives will rapidly improve forecasts of semi-arid biome shifts. Better forecasts can be expected to help prevent catastrophic changes in vegetation states by identifying improved monitoring approaches and by prioritizing high-risk areas for management.

Integrating anthropogenic factors into regional-scale species distribution models-A novel application in the imperiled sagebrush biome

Species distribution models (SDMs) that rely on regional-scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local-scale anthropogenic variables, including wildfire history, land-use change, invasive species, and ecological restoration practices can override regional-scale variables to drive patterns of species distribution. Incorporating these human-induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human-induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field-sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI: -6.9%, 0.6%) when one fire occurs and cover decreases by 44.7% (95% CI: -47.9%, -41.3%) if at least one fire occurred over the 36 year period of record. Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land-use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species.

Soil and stand structure explain shrub mortality patterns following global change-type drought and extreme precipitation

The probability of extreme weather events is increasing, with the potential for widespread impacts to plants, plant communities, and ecosystems. Reports of drought-related tree mortality are becoming more frequent, and there is increasing evidence that drought accompanied by high temperatures is especially detrimental. Simultaneously, extreme large precipitation events have become more frequent over the past century. Water-limited ecosystems may be more vulnerable to these extreme events than other ecosystems, especially when pushed outside of their historical range of variability. However, drought-related mortality of shrubs-an important component of dryland vegetation-remains understudied relative to tree mortality. In 2014, a landscape-scale die-off of the widespread shrub, big sagebrush (Artemisia tridentata Nutt.), was reported in southwest Wyoming, following extreme hot and dry conditions in 2012 and extremely high precipitation in September of 2013. Here we examine how severe drought, extreme precipitation, soil texture and salinity, and shrub-stand characteristics contributed to this die-off event. At 98 plots within and around the die-off, we quantified big sagebrush mortality, characterized soil texture and salinity, and simulated soil-water conditions from 1916 to 2016 using an ecosystem water-balance model. We found that the extreme weather conditions alone did not explain patterns of big sagebrush mortality and did not result in extreme (historically unprecedented) soil-water conditions during the drought. Instead, plots with chronically dry soil conditions experienced greatest mortality following the global change-type (hot) drought in 2012. Furthermore, mortality was greater in locations with high potential run-on and low potential run-off where saturated soil conditions were simulated in September 2013, suggesting that extreme precipitation also played an important role in the die-off in these locations. In locations where drought alone contributed to mortality, stem density negatively impacted big sagebrush. In locations that may have been affected by both drought and saturation, however, mortality was greatest where stem density was lowest, suggesting that these locations may have already been less favorable to big sagebrush. Paradoxically, vulnerability to both extreme events (drought and saturation) was associated with finer-textured soils, and our results highlight the importance of soils in determining local variation of the vulnerability of dryland plants to extreme events.

Climate change, snow mold and the Bromus tectorum invasion: mixed evidence for release from cold weather pathogens

Climate change is reducing the depth and duration of winter snowpack, leading to dramatic changes in the soil environment with potentially important ecological consequences. Previous experiments in the Intermountain West of North America indicated that loss of snowpack increases survival and population growth rates of the invasive annual grass Bromus tectorum; however, the underlying mechanism is unknown. We hypothesized that reduced snowpack might promote B. tectorum population growth by decreasing damage from snow molds, a group of subnivean fungal pathogens. To test this hypothesis, we conducted greenhouse and field experiments to investigate the interaction between early snowmelt and either fungicide addition or snow mold infection of B. tectorum. The greenhouse experiment confirmed that the snow mold Microdochium nivale can cause mortality of B. tectorum seedlings. In the field experiment, early snowmelt and fungicide application both increased B. tectorum survival, but their effects did not interact, and snow mold inoculation had no effect on survival. We did find interactive effects of snowmelt and fungal treatments on B. tectorum seed production: with ambient snowpack, M. nivale inoculation reduced seed production and fungicide increased it, whereas in the early snowmelt treatment seed production was high regardless of fungal treatment. However, treatment effects on seed production did not translate directly to overall population growth, which did not respond to the snow melt by fungal treatment interaction. Based on our mixed results, the hypothesis that reduced snowpack may increase B. tectorum fitness by limiting the effects of plant pathogens deserves further investigation.

Adaptive variation, including local adaptation, requires decades to become evident in common gardens

Population-level adaptation to spatial variation in factors such as climate and soils is critical for climate-vulnerability assessments, restoration seeding, and other ecological applications in species management, and the underlying information is typically based on common-garden studies that are short duration. Here, we show >20 yr were required for adaptive differences to emerge among 13 populations of a widespread shrub (sagebrush, Artemisia tridentata ssp wyomingensis) collected from around the western United States and planted into common gardens. Additionally, >10 yr were required for greater survival of local populations, that is, local adaptation, to become evident. Variation in survival was best explained by the combination of populations' home ecoregion combined with grouping of minimum temperature and aridity. Additional reductions in survival were explained by ungrouped (i.e., continuous) measures of garden-to-population-origin separation in geographic distance (5% decrease in survival per 100 km increase in separation; R²  = 0.22) and especially in minimum temperature in younger plants (-4% per + °C difference, R²  = 0.56 vs. 0.29 in the 14th vs. 27th post-planting years, respectively). Longer-term common garden studies are needed. While we await them, uncertainty in adaptive variation resulting from short-term observations could be quantitatively estimated and reported with seed-transfer guidelines to reduce risks of introducing maladapted provenances in restoration.

Adapting management to a changing world: Warm temperatures, dry soil, and interannual variability limit restoration success of a dominant woody shrub in temperate drylands

Restoration and rehabilitation of native vegetation in dryland ecosystems, which encompass over 40% of terrestrial ecosystems, is a common challenge that continues to grow as wildfire and biological invasions transform dryland plant communities. The difficulty in part stems from low and variable precipitation, combined with limited understanding about how weather conditions influence restoration outcomes, and increasing recognition that one-time seeding approaches can fail if they do not occur during appropriate plant establishment conditions. The sagebrush biome, which once covered over 620,000 km² of western North America, is a prime example of a pressing dryland restoration challenge for which restoration success has been variable. We analyzed field data on Artemisia tridentata (big sagebrush) restoration collected at 771 plots in 177 wildfire sites across its western range, and used process-based ecohydrological modeling to identify factors leading to its establishment. Our results indicate big sagebrush occurrence is most strongly associated with relatively cool temperatures and wet soils in the first spring after seeding. In particular, the amount of winter snowpack, but not total precipitation, helped explain the availability of spring soil moisture and restoration success. We also find considerable interannual variability in the probability of sagebrush establishment. Adaptive management strategies that target seeding during cool, wet years or mitigate effects of variability through repeated seeding may improve the likelihood of successful restoration in dryland ecosystems. Given consistent projections of increasing temperatures, declining snowpack, and increasing weather variability throughout midlatitude drylands, weather-centric adaptive management approaches to restoration will be increasingly important for dryland restoration success.

The response of big sagebrush (Artemisia tridentata) to interannual climate variation changes across its range

Understanding how annual climate variation affects population growth rates across a species' range may help us anticipate the effects of climate change on species distribution and abundance. We predict that populations in warmer or wetter parts of a species' range should respond negatively to periods of above average temperature or precipitation, respectively, whereas populations in colder or drier areas should respond positively to periods of above average temperature or precipitation. To test this, we estimated the population sensitivity of a common shrub species, big sagebrush (Artemisia tridentata), to annual climate variation across its range. Our analysis includes 8,175 observations of year-to-year change in sagebrush cover or production from 131 monitoring sites in western North America. We coupled these observations with seasonal weather data for each site and analyzed the effects of spring through fall temperatures and fall through spring accumulated precipitation on annual changes in sagebrush abundance. Sensitivity to annual temperature variation supported our hypothesis: years with above average temperatures were beneficial to sagebrush in colder locations and detrimental to sagebrush in hotter locations. In contrast, sensitivity to precipitation did not change significantly across the distribution of sagebrush. This pattern of responses suggests that regional abundance of this species may be more limited by temperature than by precipitation. We also found important differences in how the ecologically distinct subspecies of sagebrush responded to the effects of precipitation and temperature. Our model predicts that a short-term temperature increase could produce an increase in sagebrush cover at the cold edge of its range and a decrease in cover at the warm edge of its range. This prediction is qualitatively consistent with predictions from species distribution models for sagebrush based on spatial occurrence data, but it provides new mechanistic insight and helps estimate how much and how fast sagebrush cover may change within its range.