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At least 127 records · Page 7Linked to original sources

USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗

USGS2011

The human dimension of fire regimes on Earth

Humans and their ancestors are unique in being a fire‐making species, but ‘natural’ (i.e. independent of humans) fires have an ancient, geological history on Earth. Natural fires have influenced biological evolution and global biogeochemical cycles, making fire integral to the functioning of some biomes. Globally, debate rages about the impact on ecosystems of prehistoric human‐set fires, with views ranging from catastrophic to negligible. Understanding of the diversity of human fire regimes on Earth in the past, present and future remains rudimentary. It remains uncertain how humans have caused a departure from ‘natural’ background levels that vary with climate change. Available evidence shows that modern humans can increase or decrease background levels of natural fire activity by clearing forests, promoting grazing, dispersing plants, altering ignition patterns and actively suppressing fires, thereby causing substantial ecosystem changes and loss of biodiversity. Some of these contemporary fire regimes cause substantial economic disruptions owing to the destruction of infrastructure, degradation of ecosystem services, loss of life, and smoke‐related health effects. These episodic disasters help frame negative public attitudes towards landscape fires, despite the need for burning to sustain some ecosystems. Greenhouse gas‐induced warming and changes in the hydrological cycle may increase the occurrence of large, severe fires, with potentially significant feedbacks to the Earth system. Improved understanding of human fire regimes demands: (1) better data on past and current human influences on fire regimes to enable global comparative analyses, (2) a greater understanding of different cultural traditions of landscape burning and their positive and negative social, economic and ecological effects, and (3) more realistic representations of anthropogenic fire in global vegetation and climate change models. We provide an historical framework to promote understanding of the development and diversification of fire regimes, covering the pre‐human period, human domestication of fire, and the subsequent transition from subsistence agriculture to industrial economies. All of these phases still occur on Earth, providing opportunities for comparative research.

Journal of Biogeography↗

USGS2017

A mosaic-based approach is needed to conserve biodiversity in disturbed freshwater ecosystems

Conserving native biodiversity in the face of human‐ and climate‐related impacts is a challenging and globally important ecological problem that requires an understanding of spatially connected, organismal‐habitat relationships. Globally, a suite of disturbances (e.g., agriculture, urbanization, climate change) degrades habitats and threatens biodiversity. A mosaic approach (in which connected, interacting collections of juxtaposed habitat patches are examined) provides a scientific foundation for addressing many disturbance‐related, ecologically based conservation problems. For example, if specific habitat types disproportionately increase biodiversity, these keystones should be incorporated into research and management plans. Our sampling of fish biodiversity and aquatic habitat along ten 3‐km sites within the Upper Neosho River subdrainage, KS, from June‐August 2013 yielded three generalizable ecological insights. First, specific types of mesohabitat patches (i.e., pool, riffle, run, and glide) were physically distinct and created unique mosaics of mesohabitats that varied across sites. Second, species richness was higher in riffle mesohabitats when mesohabitat size reflected field availability. Furthermore, habitat mosaics that included more riffles had greater habitat diversity and more fish species. Thus, riffles (<5% of sampled area) acted as keystone habitats. Third, additional conceptual development, which we initiate here, can broaden the identification of keystone habitats across ecosystems and further operationalize this concept for research and conservation. Thus, adopting a mosaic approach can increase scientific understanding of organismal‐habitat relationships, maintain natural biodiversity, advance spatial ecology, and facilitate effective conservation of native biodiversity in human‐altered ecosystems.

Kansas↗

USGS2020

Resist-accept-direct (RAD)-A framework for the 21st-century natural resource manager

An assumption of stationarity—i.e. “the idea that natural systems fluctuate within an unchanging envelope of variability” (Milly et al. 2008)—underlies traditional conservation and natural resource management, as evidenced by widespread reliance on ecological baselines to guide protection, restoration, and other management. Although ecological change certainly occurred under the relatively stable conditions of the recent past, the nature of change under intensifying global change is different; it is unidirectional, and rapidly pushing beyond the bounds of historical variability. In the past, a manager could plausibly work to reverse or mitigate many stressors or their impacts to approximate pre-disturbance ecological conditions, but now accelerated warming, changing disturbance regimes, and extreme events associated with climate change reduce that potential. Indeed, even ‘holding the line’ in the face of inexorable human-caused change is ever more difficult and costly. Thus, the convention of using baseline conditions to define goals for today’s resource management is increasingly untenable, presenting practical and philosophical challenges for managers. As formerly familiar ecological conditions continue to change, bringing novelty, surprise, and uncertainty, natural resource managers require a new, shared approach to make conservation decisions. How, for example, should a manager respond to projections of loss of the Joshua tree from much of its current range, or to the emergence of new and different vegetation communities after a large fire event? The RAD (Resist-Accept-Direct) decision framework has emerged over the past decade as a simple tool that captures the entire decision space for responding to ecosystems facing the potential for rapid, irreversible ecological change. It assists managers in making informed, purposeful choices about how to respond to the trajectory of change, and moreover, provides a straightforward approach to support resource managers in collaborating at larger scales across jurisdictions, which today is more urgent than ever.

Natural Resource Report↗

USGS2018

Ecological genomics predicts climate vulnerability in an endangered southwestern songbird

Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher ( Empidonax traillii ), and find the endangered desert southwestern subspecies ( E. t. extimus ) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability – the mismatch between current and predicted future genotype–environment relationships – indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate‐associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype–environment relationships into landscape‐scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups.

Ecology Letters↗

USGS2011

Functional ecology of free-living nitrogen fixation: A contemporary perspective

Nitrogen (N) availability is thought to frequently limit terrestrial ecosystem processes, and explicit consideration of N biogeochemistry, including biological N 2 fixation, is central to understanding ecosystem responses to environmental change. Yet, the importance of free-living N 2 fixation—a process that occurs on a wide variety of substrates, is nearly ubiquitous in terrestrial ecosystems, and may often represent the dominant pathway for acquiring newly available N—is often underappreciated. Here, we draw from studies that investigate free-living N 2 fixation from functional, physiological, genetic, and ecological perspectives. We show that recent research and analytical advances have generated a wealth of new information that provides novel insight into the ecology of N 2 fixation as well as raises new questions and priorities for future work. These priorities include a need to better integrate free-living N 2 fixation into conceptual and analytical evaluations of the N cycle's role in a variety of global change scenarios.

Annual Review of Ecology, Evolution, and Systemati↗

USGS2014

Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum

The Arctic has experienced much greater warming than the global average in recent decades due to polar amplification. Warming has induced ecological changes that have impacted climate carbon-cycle feedbacks, making it important to understand the climate and vegetation controls on carbon (C) dynamics. Here we used the Holocene Thermal Maximum (HTM, 11–9 ka BP, 1 ka BP = 1000 cal yr before present) in Alaska as a case study to examine how ecosystem Cdynamics responded to the past warming climate using an integrated approach of combining paleoecological reconstructions and ecosystem modeling. Our paleoecological synthesis showed expansion of deciduous broadleaf forest (dominated by Populus ) into tundra and the establishment of boreal evergreen needleleaf and mixed forest during the second half of the HTM under a warmer- and wetter-than-before climate, coincident with the occurrence of the highest net primary productivity, cumulative net ecosystem productivity, soil C accumulation and CH 4 emissions. These series of ecological and biogeochemical shifts mirrored the solar insolation and subsequent temperature and precipitation patterns during HTM, indicating the importance of climate controls on C dynamics. Our simulated regional estimate of CH 4 emission rates from Alaska during the HTM ranged from 3.5 to 6.4 Tg CH 4 yr −1 and highest annual NPP of 470 Tg C yr −1 , significantly higher than previously reported modern estimates. Our results show that the differences in static vegetation distribution maps used in simulations of different time slices have greater influence on modeled C dynamics than climatic fields within each time slice, highlighting the importance of incorporating vegetation community dynamics and their responses to climatic conditions in long-term biogeochemical modeling.

Alaska↗

USGS2017

Direct and indirect controls on organic matter decomposition in four coastal wetland communities along a landscape salinity gradient

Coastal wetlands store more carbon than most ecosystems globally. As sea level rises, changes in flooding and salinity will potentially impact ecological functions, such as organic matter decomposition, that influence carbon storage. However, little is known about the mechanisms that control organic matter loss in coastal wetlands at the landscape scale. As sea level rises, how will the shift from fresh to salt-tolerant plant communities impact organic matter decomposition? Do long-term, plant-mediated, effects of sea-level rise differ from direct effects of elevated salinity and flooding? We identified internal and external factors that regulated indirect and direct pathways of sea-level rise impacts, respectively, along a landscape-scale salinity gradient that incorporated changes in wetland type (fresh, oligohaline, mesohaline and polyhaline marshes). We found that indirect and direct impacts of sea-level rise had opposing effects on organic matter decomposition. Salinity had an indirect effect on litter decomposition that was mediated through litter quality. Despite significant variation in environmental conditions along the landscape gradient, the best predictors of above- and below-ground litter decomposition were internal drivers, initial litter nitrogen content and initial litter lignin content respectively. Litter decay constants were greatest in the oligohaline marsh and declined with increasing salinity, and the fraction of litter remaining (asymptote) was greatest in the mesohaline marsh. In contrast, direct effects of salinity and flooding were positive. External drivers, salinity and flooding, stimulated cellulytic activity, which was highest in the polyhaline marsh. Synthesis . Our results indicate that as sea level rises, initial direct effects of salinity will stimulate decay of labile carbon, but over time as plant communities shift from fresh to polyhaline marsh, litter decay will decline, yielding greater potential for long-term carbon storage. These findings highlight the importance of quantifying carbon loss at multiple temporal scales, not only in coastal wetlands but also in other ecosystems where plant-mediated responses to climate change will have significant impacts on carbon cycling.

Journal of Ecology↗

USGS2022

Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat

Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.

Frontiers in Remote Sensing↗

USGS2023

A synergistic future for AI and ecology

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.

Proceedings of the National Academy of Sciences↗

USGS2024

Toward a set of essential biodiversity variables for assessing change in mountains globally

Mountain regions harbor unique and rich biodiversity, forming an important part of our global life support system. This rich biodiversity underpins the ecological intactness and functioning of mountain ecosystems, which are imperative for the provision of key ecosystem services. A considerable amount of data are required to assess ecological intactness and ecosystem functioning and, given the profound anthropogenic pressures many mountain regions are being subjected to, are urgently needed. However, data on mountain biodiversity remain lacking. The essential biodiversity variables (EBVs) framework can help focus efforts related to detecting, investigating, predicting, and managing global biodiversity change, but has not yet been considered in the context of mountains. Here, we review key biological processes and physical phenomena that strongly influence mountain biodiversity and ecosystems and elucidate their associations with potential mountain EBVs. We identify seven EBVs of highest relevance for tracking and understanding the most critical drivers and responses of mountain biodiversity change. If they are implemented, the selected EBVs will contribute useful information to inform management and policy interventions seeking to halt mountain biodiversity loss and maintain functional mountain ecosystems.

BioScience↗

USGS2021

Translational invasion ecology: Bridging research and practice to address one of the greatest threats to biodiversity

Effective natural resource management and policy is contingent on information generated by research. Conversely, the applicability of research depends on whether it is responsive to the needs and constraints of resource managers and policy makers. However, many scientific fields including invasion ecology suffer from a disconnect between research and practice. Despite strong socio-political imperatives, evidenced by extensive funding dedicated to addressing invasive species, the pairing of invasion ecology with stakeholder needs to support effective management and policy is lacking. As a potential solution, we propose translational invasion ecology (TIE). As an extension of translational ecology, as a framework to increase collaboration among scientists, practitioners, and policy makers to reduce negative impacts of invasive species. As an extension of translational ecology, TIE is an approach that embodies an intentional and inclusive process in which researchers, stakeholders, and decision makers collaborate to develop and implement ecological research via joint consideration of the ecological, sociological, economic, and/or political contexts in order to improve invasive species management. TIE ideally results in improved outcomes as well as shared benefits between researchers and managers. We delineate the steps of our proposed TIE approach and describe successful examples of ongoing TIE projects from the US and internationally. We suggest practical ways to begin incorporating TIE into research and management practices, including supporting boundary-spanning organizations and activities, expanding networks, sharing translational experiences, and measuring outcomes. We find that there is a need for strengthened boundary spanning, as well as funding and recognition for advancing translational approaches. As climate change and globalization exacerbate invasive species impacts, TIE provides a promising approach to generate actionable ecological research while improving outcomes of invasive species management and policy decisions.

Biological Invasions↗

USGS2024

Imperiled Great Basin terminal lakes: Synthesizing ecological and hydrological science gaps and research needs for waterbird conservation

Terminal lakes are declining globally because of human water demands, drought, and climate change. Through literature synthesis and feedback from the resource and conservation community, we review the state of research for terminal lakes in the Great Basin of the United States, which support millions of waterbirds annually, to prioritize ecological and hydrologic information needs. From an ecological perspective, research priorities include measuring the underlying differences in waterbird resource selection and distribution, migratory connectivity, abiotic factors that interact with prey densities to affect prey availability, and waterbird fitness or demography. Integrated links between water availability, water quality, and food webs are lacking in the literature. Scarce water availability data hinder the current knowledge of water extraction and evapotranspiration rates. Research that can address these priorities would help advance our understanding of how the Great Basin terminal lakes function as an interrelated system and support conservation efforts to reverse the decline of these critical lakes.

California, Nevada, Oregon, Utah↗

USGS2014

Accounting for imperfect detection and survey bias in statistical analysis of presence-only data

Aim During the past decade ecologists have attempted to estimate the parameters of species distribution models by combining locations of species presence observed in opportunistic surveys with spatially referenced covariates of occurrence. Several statistical models have been proposed for the analysis of presence-only data, but these models have largely ignored the effects of imperfect detection and survey bias. In this paper I describe a model-based approach for the analysis of presence-only data that accounts for errors in the detection of individuals and for biased selection of survey locations. Innovation I develop a hierarchical, statistical model that allows presence-only data to be analysed in conjunction with data acquired independently in planned surveys. One component of the model specifies the spatial distribution of individuals within a bounded, geographic region as a realization of a spatial point process. A second component of the model specifies two kinds of observations, the detection of individuals encountered during opportunistic surveys and the detection of individuals encountered during planned surveys. Main conclusions Using mathematical proof and simulation-based comparisons, I demonstrate that biases induced by errors in detection or biased selection of survey locations can be reduced or eliminated by using the hierarchical model to analyse presence-only data in conjunction with counts observed in planned surveys. I show that a relatively small number of high-quality data (from planned surveys) can be used to leverage the information in presence-only observations, which usually have broad spatial coverage but may not be informative of both occurrence and detectability of individuals. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. In addition, since the point-process model is formulated at the level of an individual, it can be extended to account for biological interactions between individuals and temporal changes in their spatial distributions.

Global Ecology and Biogeography↗

USGS2013

Coral reef resilience through biodiversity

Irrefutable evidence of coral reef degradation worldwide and increasing pressure from rising seawater temperatures and ocean acidification associated with climate change have led to a focus on reef resilience and a call to “manage” coral reefs for resilience. Ideally, global action to reduce emission of carbon dioxide and other greenhouse gases will be accompanied by local action. Effective management requires reduction of local stressors, identification of the characteristics of resilient reefs, and design of marine protected area networks that include potentially resilient reefs. Future research is needed on how stressors interact, on how climate change will affect corals, fish, and other reef organisms as well as overall biodiversity, and on basic ecological processes such as connectivity. Not all reef species and reefs will respond similarly to local and global stressors. Because reef-building corals and other organisms have some potential to adapt to environmental changes, coral reefs will likely persist in spite of the unprecedented combination of stressors currently affecting them. The biodiversity of coral reefs is the basis for their remarkable beauty and for the benefits they provide to society. The extraordinary complexity of these ecosystems makes it both more difficult to predict their future and more likely they will have a future.

ISRN Oceanography↗

USGS2004

Exploitation dynamics of small fish stocks like Arctic cisco

Potential impacts to the Arctic cisco population fall into both demographic and behavioral categories. Possible demographic impacts include stock recruitment effects, limited escapement into marine habitats, and variable age-class reproductive success. Potential behavioral impacts involve migratory patterns, variable life histories, and strategies for seasonal feeding. Arctic cisco stocks are highly susceptible to over-exploitation due to our limited basic knowledge of the highly variable Arctic environment and the role they play in this dynamic ecosystem. Our knowledge of potential demographic changes is very limited, and it is necessary to determine the abundance and recruitment of the hypothesized Mackenzie River source population, the extent of the coastal migratory corridor, growth patterns, and coastal upwelling and mixing effects on population dynamics for this species. Information needed to answer some of the demographic questions includes basic evolutionary history and molecular genetics of Arctic cisco (for instance, are there contributions to the Arctic cisco stock from the Yukon?), what is the effective population size (i.e., breeding population size), and potential links to changes in climate. The basic behavioral questions include migratory and variable life history questions. For instance, the extent of movement back and forth between freshwater and the sea, age-specific differences in food web dynamics, and nearshore brackish and high salinity habitats are topics that should be studied. Life history data should be gathered to understand the variation in age at reproduction, salinity tolerance, scale and duration of the freshwater stage, survival, and adult migration. Both molecular and ecological tools should be integrated to manage the Arctic cisco stock(s), such as understanding global climate changes on patterns of harvest and recruitment, and the genetics of population structure and colonization. Perhaps other populations are contributing to the population within the Colville River other than only the Mackenzie River population. This needs further exploration. By examining otolith microchemistry, unique transitions from freshwater to sea can be identified for these stocks. This may shed light on why some fish arrive at the mouth of the Colville River, while others don’t.

Conference Paper↗

USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗

USGS2003

Modeled climate-induced glacier change in Glacier National Park, 1850-2100

The glaciers in the Blackfoot–Jackson Glacier Basin of Glacier National Park, Montana, decreased in area from 21.6 square kilometers (km 2 ) in 1850 to 7.4 km 2 in 1979. Over this same period global temperatures increased by 0.45°C (± 0.15°C). We analyzed the climatic causes and ecological consequences of glacier retreat by creating spatially explicit models of the creation and ablation of glaciers and of the response of vegetation to climate change. We determined the melt rate and spatial distribution of glaciers under two possible future climate scenarios, one based on carbon dioxide–induced global warming and the other on a linear temperature extrapolation. Under the former scenario, all glaciers in the basin will disappear by the year 2030, despite predicted increases in precipitation; under the latter, melting is slower. Using a second model, we analyzed vegetation responses to variations in soil moisture and increasing temperature in a complex alpine landscape and predicted where plant communities are likely to be located as conditions change.

Montana↗