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USGS2019

Sediment classification and the characterization, identification, and mapping of geologic substrates for the glaciated Gulf of Maine seabed and other terrains, providing a physical framework for ecological research and seabed management

A geologic substrate is a surface (or volume) of sediment or rock where physical, chemical, and biological processes occur, such as the movement and deposition of sediment, the formation of bedforms, and the attachment, burrowing, feeding, reproduction, and sheltering of organisms. Seabed mapping surveys in the Stellwagen Bank region off Boston, Massachusetts, from 1993 to 2004 have led to the development of a methodology for characterizing, identifying, and mapping geologic substrates. The resulting high-resolution interpretive maps (1:25,000) show the distribution of substrates in a glaciated terrain of banks and basins in water depths of 30 to 185 meters. Data sources used to characterize substrates are multibeam sonar bathymetric and backscatter imagery to document seabed topography and patterns of sediment and rock distribution, grain-size analyses of sediment samples to determine substrate composition, and video and photographic imagery of the seabed to aid in the interpretation of multibeam sonar imagery and to provide information on substrate layering and mobility, seabed structures, and sediments and nonsediment materials that cannot be physically sampled. Sediment composition is a major property of many seabed substrates. Sediment grains belong to a continuum of grain-diameter sizes previously classified into grades (for example, fine sand, medium sand) and into aggregates (mud, sand, gravel). The definition of grade and aggregate boundaries in a classification is arbitrary, and a useful classification is limited to as few classes as are needed to effectively organize and apply information. For the purpose of mapping substrates, sediment grades and aggregates were simplified and re-classified into eight composite grades based on grain-size content, mode of transport, and ecological role. Five composite grades are identified using grain-size analysis and three are identified using video and photographic imagery of the seabed. Naturally occurring sediments contain various amounts of the aggregates mud, sand, and gravel. The separation of naturally occurring sediments into sediment classes, based on grain-size analysis, requires that limits be set on the amount of mud, sand, and gravel each class contains. Fifteen previously identified basic sediment classes provided interpretive information on sediment transport by emphasizing gravel content (a low 0.01-weight-percent threshold) and on winnowing processes based on the sand-to-mud ratio. The present study recognizes 20 basic sediment classes that are combinations of aggregates in which the lower limits for recognition of mud and sand are 10 weight percent and of gravel, 25 weight percent. These sediment classes can be made more specific by listing their content of the composite grades fine-grained sand (3 and 4 phi), which is transported in suspension, and coarse-grained sand (0, 1, and 2 phi), which is transported as bedload. Additional sediment classes and nonsediment classes that cannot be sampled are recognized on the basis of visual analysis of seabed video and photographic imagery and include pebble, cobble, and boulder gravel, rock outcrops, and shell beds, among others. Substrates are not classified because their properties are too varied for a classification to be concise and useful. Rather, substrates are characterized and identified by sediment grain-size composition (the sediment class); the distribution, in millimeters, of grain diameters in the sediment; the presence of nonsediments (for example, rock outcrops); substrate mobility based on the presence of sediment ripples; substrate layering (for example, a partial veneer of sand on gravel); and seabed structures. These properties have interpretive value by providing information about sedimentary processes acting on a substrate and about its ecological function. A geologic substrate, when it is associated with one or more species, is an important element of a habitat. This methodology was developed to map a glaciated terrain characterized by geologic substrates that typify a wide range of erosional and depositional sedimentary environments, and it likely will be useful for mapping substrates in other terrains. Substrate maps provide the physical framework required for identifying sediment transport processes, validating sediment transport models, studying the ecology of species and communities, and managing marine resources and seabed usage.

Massachusetts↗

USGS2022

A novel application of hierarchical modelling to decouple sampling artifacts from socio-ecological effects on poaching intensity

Poaching is a global driver of wildlife population decline, including inside protected areas (PAs). Reducing poaching requires an understanding of its cryptic drivers and accurately quantifying poaching scales and intensity. There is little quantification of how poaching is affected by law enforcement intensity (e.g., ranger stations) versus economic factors (e.g., unemployment), while simultaneously accounting for imperfect detection. Using extensive data of poaching events (i.e., seizures) and censuses of nine ungulate species across the PAs and unprotected lands of Iran from 2010 to 2018, we developed a single-visit hierarchical (N-mixture) model to accurately estimate annual poaching of Iranian ungulates and to differentiate between social and ecological effects on annual poaching intensity. We found that poaching detectability increased with numbers of ranger stations. A recent surge in poaching (2013–2018) coincides with rising unemployment rate. We estimated that 19,727 ungulates (95% confidence interval 11,178–36,195) were poached across the country during 2010–2018. Poaching intensity was positively related to unemployment rate, road density, and ungulate abundance. Our simulations demonstrated that the Poisson and Negative binomial N-mixture models had adequate performance when the conditions of Sólymos et al. (2012) were satisfied, in particular, when at least one covariate is unique to both the detection and abundance parts of the model. Overall, we suggest that single-visit models offer unique insights into understanding the link between poaching intensity, economic conditions, and law enforcement in large-scale landscapes while accounting for imperfect detection of poaching events.

Biological Conservation↗

USGS2017

A new parameterization for integrated population models to document amphibian reintroductions

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog ( Rana pretiosa ) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010–2011 to 0.86 in 2012–2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

Ecological Applications↗

USGS2009

Evaluation of trap capture in a geographically closed population of brown treesnakes on Guam

1. Open population mark-recapture analysis of unbounded populations accommodates some types of closure violations (e.g. emigration, immigration). In contrast, closed population analysis of such populations readily allows estimation of capture heterogeneity and behavioural response, but requires crucial assumptions about closure (e.g. no permanent emigration) that are suspect and rarely tested empirically. 2. In 2003, we erected a double-sided barrier to prevent movement of snakes in or out of a 5-ha semi-forested study site in northern Guam. This geographically closed population of >100 snakes was monitored using a series of transects for visual searches and a 13 ?? 13 trapping array, with the aim of marking all snakes within the site. Forty-five marked snakes were also supplemented into the resident population to quantify the efficacy of our sampling methods. We used the program mark to analyse trap captures (101 occasions), referenced to census data from visual surveys, and quantified heterogeneity, behavioural response, and size bias in trappability. Analytical inclusion of untrapped individuals greatly improved precision in the estimation of some covariate effects. 3. A novel discovery was that trap captures for individual snakes consisted of asynchronous bouts of high capture probability lasting about 7 days (ephemeral behavioural effect). There was modest behavioural response (trap happiness) and significant latent (unexplained) heterogeneity, with small influences on capture success of date, gender, residency status (translocated or not), and body condition. 4. Trapping was shown to be an effective tool for eradicating large brown treesnakes Boiga irregularis (>900 mm snout-vent length, SVL). 5. Synthesis and applications. Mark-recapture modelling is commonly used by ecological managers to estimate populations. However, existing models involve making assumptions about either closure violations or response to capture. Physical closure of our population on a landscape scale allowed us to determine the relative importance of covariates influencing capture probability (body size, trappability periods, and latent heterogeneity). This information was used to develop models in which different segments of the population could be assigned different probabilities of capture, and suggests that modelling of open populations should incorporate easily measured, but potentially overlooked, parameters such as body size or condition. ?? 2008 The Authors.

Journal of Applied Ecology↗

USGS2013

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗

USGS2018

Using partial aggregation in spatial capture recapture

Spatial capture–recapture (SCR) models are commonly used for analysing data collected using noninvasive genetic sampling (NGS). Opportunistic NGS often leads to detections that do not occur at discrete detector locations. Therefore, spatial aggregation of individual detections into fixed detectors (e.g., centre of grid cells) is an option to increase computing speed of SCR analyses. However, it may reduce precision and accuracy of parameter estimations. Using simulations, we explored the impact that spatial aggregation of detections has on a trade‐off between computing time and parameter precision and bias, under a range of biological conditions. We used three different observation models: the commonly used Poisson and Bernoulli models, as well as a novel way to partially aggregate detections (Partially Aggregated Binary model [PAB]) to reduce the loss of information after aggregating binary detections. The PAB model divides detectors into K subdetectors and models the frequency of subdetectors with more than one detection as a binomial response with a sample size of K. Finally, we demonstrate the consequences of aggregation and the use of the PAB model using NGS data from the monitoring of wolverine ( Gulo gulo ) in Norway. Spatial aggregation of detections, while reducing computation time, does indeed incur costs in terms of reduced precision and accuracy, especially for the parameters of the detection function. SCR models estimated abundance with a low bias (<10%) even at high degree of aggregation, but only for the Poisson and PAB models. Overall, the cost of aggregation is mitigated when using the Poisson and PAB models. At the same level of aggregation, the PAB observation model out‐performs the Bernoulli model in terms of accuracy of estimates, while offering the benefits of a binary observation model (less assumptions about the underlying ecological process) over the count‐based model. We recommend that detector spacing after aggregation does not exceed 1.5 times the scale‐parameter of the detection function in order to limit bias. We recommend the use of the PAB observation model when performing spatial aggregation of binary data as it can mitigate the cost of aggregation, compared to the Bernoulli model.

Methods in Ecology and Evolution↗

USGS2004

Relationships between bald eagle productivity and dynamics of fish populations and fisheries in the Wisconsin waters of Lake Superior, 1983-1999

Bald eagle ( Haliaeetus leucocephalus ) abundance declined in the 1950s and 1960s along the Wisconsin waters of Lake Superior, and were nearly absent along Wisconsin's Lake Superior shoreline. The population began to increase again between 1980 and 1983, and since then bald eagles nesting on islands along Wisconsin's Lake Superior shoreline (i.e., Apostle Islands ) reproduced at a lower rate than have those nesting along the mainland shoreline of the lake and inland. Recent research indicated that bioaccumulation of toxic chemicals in the aquatic food chain no longer limits bald eagle reproduction there, and that productivity at island nests was lower than at mainland nests and inland nests as the result of low food availability. Management agencies have sought models that accurately predict productivity and explain ecological relationships, but no satisfactory models had previously been developed. Modeling was conducted here to determine which factors best explained productivity variability. The Ricker stock-recruitment model derived from only the bivariate breeding pair and productivity data explained only 1% of the variability in productivity data. The functional relationship that explained the greatest amount of productivity variation (83%) included the number of breeding pairs, burbot ( Lota lota ) biomass, longnose sucker ( Catostomus catostomus ) biomass, and commercial harvest of nontarget fishes. Model results were interpreted to mean that productivity was positively affected by populations of burbot and longnose sucker, which are important prey items, and by commercial fishermen feeding nontarget fish to bald eagles. Harvest of nontarget fishes by tribal fishermen and burbot and longnose sucker populations have not tended to change during the entire study period, although the burbot population has declined since 1991. Therefore, bald eagle productivity is not predicted to increase unless burbot, longnose sucker, or other preferred prey of bald eagles increases in the Apostle Islands.

Wisconsin↗

USGS2024

Thermal and hydrological limitations on modeling carbon dynamics at wetland sites of discontinuous and continuous permafrost extent

Accurate representation of cryohydrological processes is fundamental for biosphere models, particularly at high-latitudes, given their influence on carbon and permafrost dynamics in carbon-rich peatlands and wetlands. This study analyzes site-level simulations in moist and wet drainage conditions in continuous or discontinuous permafrost regions, using a terrestrial ecosystem model DVM-DOS-TEM. Functional benchmarking was conducted against eddy covariance flux alongside soil temperature, moisture, and thaw depth observations. Thermal and hydrological analysis reveals parameter sensitivity and uncertainty concerning carbon cycling and permafrost dynamics. Flux representation is markedly consistent at sites characterized by continuous permafrost with less seasonal variation, owing to longer soil freezing duration. Sites in discontinuous permafrost, exhibiting active permafrost degradation and talik formation, pose considerable challenges in accurately depicting thaw depth. Underprediction of soil moisture across all sites has more pronounced effects on boreal wetlands characterized by thick organic layers up to 1 m. These results illustrate the limitations of terrestrial ecosystem models to represent environmental and ecological dynamics in wetlands. Attempts to adjust model hydrology have yielded marginal improvements in thaw depth prediction, but revealed large effects of abrupt phase changes for poorly drained sites on discontinuous permafrost. Our analysis suggests the importance of gradual phase change representation, particularly in ice-rich wetlands with thick organic layers, which will be crucial when evaluating the permafrost carbon-climate feedback in model projections.

Alaska↗

USGS2015

Caveats for correlative species distribution modeling

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

Ecological Informatics↗

USGS2015

Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River

Knowledge of the diversity and ecological function of the microbial consortia of James River in Virginia, USA, is essential to developing a more complete understanding of the ecology of this model river system. Metagenomic analysis of James River's planktonic microbial community was performed for the first time using an unamplified genomic library and a 16S rDNA amplicon library prepared and sequenced by Ion PGM and MiSeq, respectively. From the 0.46-Gb WGS library (GenBank:SRR1146621; MG-RAST:4532156.3), 4 × 10 6 reads revealed >3 × 10 6 genes, 240 families of prokaryotes, and 155 families of eukaryotes. From the 0.68-Gb 16S library (GenBank:SRR2124995; MG-RAST:4631271.3; EMB:2184), 4 × 10 6 reads revealed 259 families of eubacteria. Results of the WGS and 16S analyses were highly consistent and indicated that more than half of the bacterial sequences were Proteobacteria , predominantly Comamonadaceae . The most numerous genera in this group were Acidovorax (including iron oxidizers, nitrotolulene degraders, and plant pathogens), which accounted for 10 % of assigned bacterial reads. Polaromonas were another 6 % of all bacterial reads, with many assignments to groups capable of degrading polycyclic aromatic hydrocarbons. Albidiferax (iron reducers) and Variovorax (biodegraders of a variety of natural biogenic compounds as well as anthropogenic contaminants such as polycyclic aromatic hydrocarbons and endocrine disruptors) each accounted for an additional 3 % of bacterial reads. Comparison of these data to other publically-available aquatic metagenomes revealed that this stretch of James River is highly similar to the upper Mississippi River, and that these river systems are more similar to aquaculture and sludge ecosystems than they are to lakes or to a pristine section of the upper Amazon River. Taken together, these analyses exposed previously unknown aspects of microbial biodiversity, documented the ecological responses of microbes to urban effects, and revealed the noteworthy presence of 22 human-pathogenic bacterial genera (e.g., Enterobacteriaceae , pathogenic Pseudomonadaceae , and ‘ Vibrionales' ) and 6 pathogenic eukaryotic genera (e.g., Trypanosomatidae and Vahlkampfiidae). This information about pathogen diversity may be used to promote human epidemiological studies, enhance existing water quality monitoring efforts, and increase awareness of the possible health risks associated with recreational use of James River.

Virginia↗

USGS2015

Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado

Great Sand Dunes National Park and Preserve and the neighboring Baca National Wildlife Refuge constitute an extraordinary setting that offers a variety of opportunities for outdoor recreation and natural resource preservation in the San Luis Valley of Colorado. Adjacent to these federal lands, the Nature Conservancy (TNC) manages the historic Medano Ranch. The total land area of these three conservation properties is roughly 121,500 hectares (ha). It is a remote and rugged area in which resource managers must balance the protection of natural resources with recreation and neighboring land uses. The management of wild ungulates in this setting presents challenges, as wild ungulates move freely across public and private landscapes. The San Luis Valley was historically used for irrigated agriculture and ranching. Historically, livestock, including sheep ( Ovis aries ) and cattle ( Bos taurus ), were grazed throughout the valley. The former Luis Marie “Baca” Ranch, which makes up the northern part of Great Sand Dunes National Park (hereafter “Park”) and all of the Baca National Wildlife Refuge (hereafter “Refuge”), was actively grazed by cattle until 2004. Bison ( Bison bison ), elk ( Cervus elaphus ), mule deer ( Odocoileus hemionus ), and pronghorn ( Antilocapra americana ) were native to the area until about the 1840s, when bison, elk, and pronghorn were extirpated. Elk and pronghorn likely moved back into the area from surrounding populations to the north and south, and mule deer populations have varied through time. A population of 4,400 elk currently inhabits the area. The current bison population was established in 1986 for meat production. In 1999 TNC purchased the ranch and established a bison conservation herd, and eventually subcontracted management to a private rancher in 2005. A population of bison ranging in size from 1,200–2,000 ranges freely within the 16,100 ha Medano Ranch. Ungulate populations in the valley are regulated by hunting, with the exception of bison, which are rounded up and culled annually to maintain population levels. In an effort to create and form the basis of a multi-agency ungulate management plan for the region, the Park sought the development of an elk and bison ecological carrying capacity model to provide guidance to resource managers.

Colorado↗

USGS2014

Transdisciplinary application of the cross-scale resilience model

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlying discontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/ anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems.

Sustainability↗

USGS2009

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Conference Paper↗

USGS2011

Estimating the Cumulative Ecological Effect of Local Scale Landscape Changes in South Florida

Ecosystem restoration in south Florida is a state and national priority centered on the Everglades wetlands. However, urban development pressures affect the restoration potential and remaining habitat functions of the natural undeveloped areas. Land use (LU) planning often focuses at the local level, but a better understanding of the cumulative effects of small projects at the landscape level is needed to support ecosystem restoration and preservation. The South Florida Ecosystem Portfolio Model (SFL EPM) is a regional LU planning tool developed to help stakeholders visualize LU scenario evaluation and improve communication about regional effects of LU decisions. One component of the SFL EPM is ecological value (EV), which is evaluated through modeled ecological criteria related to ecosystem services using metrics for (1) biodiversity potential, (2) threatened and endangered species, (3) rare and unique habitats, (4) landscape pattern and fragmentation, (5) water quality buffer potential, and (6) ecological restoration potential. In this article, we demonstrate the calculation of EV using two case studies: (1) assessing altered EV in the Biscayne Gateway area by comparing 2004 LU to potential LU in 2025 and 2050, and (2) the cumulative impact of adding limestone mines south of Miami. Our analyses spatially convey changing regional EV resulting from conversion of local natural and agricultural areas to urban, industrial, or extractive use. Different simulated local LU scenarios may result in different alterations in calculated regional EV. These case studies demonstrate methods that may facilitate evaluation of potential future LU patterns and incorporate EV into decision making.

Florida↗

USGS2014

New permafrost is forming around shrinking Arctic lakes, but will it last?

Widespread lake shrinkage in cold regions has been linked to climate warming and permafrost thaw. Permafrost aggradation, however, has been observed within the margins of recently receded lakes, in seeming contradiction of climate warming. Here permafrost aggradation dynamics are examined at Twelvemile Lake, a retreating lake in interior Alaska. Observations reveal patches of recently formed permafrost within the dried lake margin, colocated with discrete bands of willow shrub. We test ecological succession, which alters shading, infiltration, and heat transport, as the driver of aggradation using numerical simulation of variably saturated groundwater flow and heat transport with phase change (i.e., freeze-thaw). Simulations support permafrost development under current climatic conditions, but only when net effects of vegetation on soil conditions are incorporated, thus pointing to the role of ecological succession. Furthermore, model results indicate that permafrost aggradation is transitory with further climate warming, as new permafrost thaws within seven decades.

Alaska↗

USGS2006

Carnivore re-colonisation: Reality, possibility and a non-equilibrium century for grizzly bears in the southern Yellowstone ecosystem

Most large native carnivores have experienced range contractions due to conflicts with humans, although neither rates of spatial collapse nor expansion have been well characterised. In North America, the grizzly bear (Ursus arctos) once ranged from Mexico northward to Alaska, however its range in the continental USA has been reduced by 95-98%. Under the U. S. Endangered Species Act, the Yellowstone grizzly bear population has re-colonised habitats outside Yellowstone National Park. We analysed historical and current records, including data on radio-collared bears, (1) to evaluate changes in grizzly bear distribution in the southern Greater Yellowstone Ecosystem (GYE) over a 100-year period, (2) to utilise historical rates of re-colonisation to project future expansion trends and (3) to evaluate the reality of future expansion based on human limitations and land use. Analysis of distribution in 20-year increments reflects range reduction from south to north (1900-1940) and expansion to the south (1940-2000). Expansion was exponential and the area occupied by grizzly bears doubled approximately every 20 years. A complementary analysis of bear occurrence in Grand Teton National Park also suggests an unprecedented period of rapid expansion during the last 20-30 years. The grizzly bear population currently has re-occupied about 50% of the southern GYE. Based on assumptions of continued protection and ecological stasis, our model suggests total occupancy in 25 years. Alternatively, extrapolation of linear expansion rates from the period prior to protection suggests total occupancy could take > 100 years. Analyses of historical trends can be useful as a restoration tool because they enable a framework and timeline to be constructed to pre-emptively address the social challenges affecting future carnivore recovery. ?? 2004 The Zoological Society of London.

Idaho, Montana, Wyoming↗

USGS2015

Adapting California’s ecosystems to a changing climate

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). They illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

BioScience↗

USGS2022

What common-garden experiments tell us about climate responses in plants

Common garden experiments are indoor or outdoor plantings of species or populations collected from multiple distinct geographic locations, grown together under shared conditions. These experiments examine a range of questions for theory and application using a variety of methods for analysis. The eight papers of this special feature comprise a cross section of contemporary approaches, summarized and synthesized here by what they tell us about the relationships between climate-related trait spectra and fitness optima. Four of the eight papers are based on field experiments in prairie, desert, Mediterranean and boreal biomes. Representative of many common garden experiments, these experiments reveal consistent evidence of traits varying with population climate provenance, but evidence of a tradeoff between growth and tolerance traits or of consistent fitness optimization at home is scant, in contrast to trait theory. Two synthesis papers highlight dominant patterns of trait divergence, including for an exotic invasive species. One theoretical paper warned that unknown kinship relationships between populations can result in the misidentification of adaptive trait divergence. A third synthesis paper formulated novel and ambitious goals for common-garden studies through including measurement of response variables at multiple levels of biological organization. The featured papers discuss multiple avenues for improving common garden studies. Genomic analysis, together with the quantification of kinship relationships, will continue to reveal the influence of environmental drivers on gene selection. Measuring a more complete set of fitness traits, especially for traits related to regeneration, will permit the development of projection models to explicitly link trait spectra, climate patterns and fitness consequences. More standardized data reporting will additionally improve abilities to synthesize findings across experiments. Testing population performance in competition with other species will produce more robust fitness comparisons between genotypes, especially for slower-growing genotypes in higher-resource environments. Adding gardens in and beyond climatic edge locations will furthermore strengthen the understanding of population failure and species exclusion. Finally, there is unrealized potential in adding ecosystem-level observations to common-garden studies that will enhance integrative analysis across scales of biological organization and scientific domains. Synthesis . With novel, creative designs, data integration and synthesis, common garden experiments will continue to advance the understanding of trait ensembles interacting with climate across scales of biological organization, provide pivotal data for global change models and guide ecological applications such as restoration of habitats for rare and climate sensitive species.

Journal of Ecology↗