Geology topics

Helen Sofaer

Publications and source records attributed to Helen Sofaer.

10 recordsLinked to original sources

USGS2020

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report↗

USGS2019

The area under the precision‐recall curve as a performance metric for rare binary events

Species distribution models are used to study biogeographic patterns and guide decision‐making. The variable quality of these models makes it critical to assess whether a model's outputs are suitable for the intended use, but commonly used evaluation approaches are inappropriate for many ecological contexts. In particular, unrealistically high performance assessments have been associated with models for rare species and predictions over large geographic extents. We evaluated the area under the precision‐recall curve (AUC‐PR) as a performance metric for rare binary events, focusing on the assessment of species distribution models. Precision is the probability that a species is present given a predicted presence, while recall (more commonly called sensitivity) is the probability the model predicts presence in locations where the species has been observed. We simulated species at three levels of prevalence, compared AUC‐PR and the area under the receiver operating characteristic curve (AUC‐ROC) when the geographic extent of predictions was increased and assessed how well each metric reflected a model's utility to guide surveys for new populations. AUC‐PR was robust to species rarity and, unlike AUC‐ROC, not affected by an increasing geographic extent. The major advantages of AUC‐PR arise because it does not incorporate correctly predicted absences and is therefore less prone to exaggerate model performance for unbalanced datasets. AUC‐PR and precision were useful indicators of a model's utility for guiding surveys. We show that AUC‐PR has important advantages for evaluating models of rare species, and its benefits in the context of unbalanced binary responses will make it applicable for other ecological studies. By not considering the true negative quadrant of the confusion matrix, AUC‐PR ameliorates issues that arise when the geographic extent is increased beyond the species’ range or when a large number of background points are used when absence information is unavailable. However, no single metric captures all aspects of performance nor provides an absolute index that can be compared across datasets. Our results indicate AUC‐PR and precision can provide useful and intuitive metrics for evaluating a model's utility for guiding sampling, and can complement other metrics to help delineate a model's appropriate use.

Methods in Ecology and Evolution↗

USGS2019

Integrating landscape simulation models with economic and decision tools for invasive species control

In managing invasive species, land managers and policy makers need information to help allocate scarce resources as efficiently and effectively as possible. Decisions regarding treatment methods, locations, effort, and timing can be informed by the integration of landscape simulation models with economic tools. State and transition simulation models align with conceptual models of ecosystem change often used by practitioners and have been used to characterize the potential consequences of invasions. Outputs of these simulations are typically summarized to describe landscape changes (e.g., infested area), which may provide sufficient information for mangers to make informed decisions. However, it is sometimes helpful or necessary to go a step further to consider the social and economic values associated with treating (or not treating) invasions. Here, we describe when and how to integrate state and transition simulation models with economic and decision tools to aid in the control of emerging and established populations of invasive species. The paper provides an overview of three types of questions that can be addressed: 1) how big is the problem? 2) which management strategy is most appropriate? and 3) what are key sources of uncertainty? For each question, we describe aspects that can be addressed by landscape simulation models alone, and outstanding questions that can be evaluated by integrating economic and decision tools. Through a series of example applications from the literature, we reinforce how the integration of these tools, and the interdisciplinary perspective such an integration requires, can increase relevance and utility of modeling efforts for resource managers and decision makers.

Management of Biological Invasions↗

USGS2018

The relationship between invader abundance and impact

The impacts of invasive species generally increase with their abundance, but the form of invader abundance–impact relationships remain poorly described. We highlight the utility of abundance–impact curves for three questions. First, abundance–impact relationships can clarify whether prevention and management should focus on the species likely to become abundant or those likely to cause large impacts per individual. Second, comparing abundance–impact relationships between native and exotic species can reveal any systematic differences in their effects on ecological systems. Third, identifying any thresholds in the relationship between invader impact and abundance can be used to select management targets and design invasive species control strategies. With increasing extent and resolution of datasets of invasive organisms worldwide, we now have the opportunity to explore in detail the form and context dependence of the abundance–impact relationship. Doing so provides opportunities to improve the prediction of invader impact, to better understand the differences between exotic and resident organisms, and to scale the impacts of invasive species from localities to ranges.

Ecosphere↗

USGS2018

Misleading prioritizations from modelling range shifts under climate change

Aim Conservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change. Location Conterminous U.S.A. Time period 1977–2014. Major taxa studied Passerine birds. Methods We estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c . 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size. Results Species distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species. Main conclusions Models failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.

Global Ecology and Biogeography↗

USGS2017

Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.

Prairie Pothole Region↗

USGS2017

Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants

Aim The distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns. Location Global. Time period Museum records, generally from the 1800s up to 2015. Major taxa studied Plant species exotic to the United States. Methods We used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries. Results Accounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias. Main conclusions Our work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.

Global Ecology and Biogeography↗

USGS2017

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Global Change Biology↗

USGS2016

Projected wetland densities under climate change: Habitat loss but little geographic shift in conservation strategy

Climate change poses major challenges for conservation and management because it alters the area, quality, and spatial distribution of habitat for natural populations. To assess species’ vulnerability to climate change and target ongoing conservation investments, researchers and managers often consider the effects of projected changes in climate and land use on future habitat availability and quality and the uncertainty associated with these projections. Here, we draw on tools from hydrology and climate science to project the impact of climate change on the density of wetlands in the Prairie Pothole Region of the USA, a critical area for breeding waterfowl and other wetland-dependent species. We evaluate the potential for a trade-off in the value of conservation investments under current and future climatic conditions and consider the joint effects of climate and land use. We use an integrated set of hydrological and climatological projections that provide physically based measures of water balance under historical and projected future climatic conditions. In addition, we use historical projections derived from ten general circulation models (GCMs) as a baseline from which to assess climate change impacts, rather than historical climate data. This method isolates the impact of greenhouse gas emissions and ensures that modeling errors are incorporated into the baseline rather than attributed to climate change. Our work shows that, on average, densities of wetlands (here defined as wetland basins holding water) are projected to decline across the U.S. Prairie Pothole Region, but that GCMs differ in both the magnitude and the direction of projected impacts. However, we found little evidence for a shift in the locations expected to provide the highest wetland densities under current vs. projected climatic conditions. This result was robust to the inclusion of projected changes in land use under climate change. We suggest that targeting conservation towards wetland complexes containing both small and relatively large wetland basins, which is an ongoing conservation strategy, may also act to hedge against uncertainty in the effects of climate change.

Montana, North Dakota, South Dakota↗

USGS2016

The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?

Comparative studies of populations occupying different environments can provide insights into the ecological conditions affecting differences in parental strategies, including the relative contributions of males and females. Male and female parental strategies reflect the interplay between ecological conditions, the contributions of the social mate, and the needs of offspring. Climate is expected to underlie geographic variation in incubation and brooding behavior, and can thereby affect both the absolute and relative contributions of each sex to other aspects of parental care such as offspring provisioning. However, geographic variation in brooding behavior has received much less attention than variation in incubation attentiveness or provisioning rates. We compared parental behavior during the nestling period in populations of orange-crowned warblers Oreothlypis celata near the northern (64°N) and southern (33°N) boundaries of the breeding range. In Alaska, we found that males were responsible for the majority of food delivery whereas the sexes contributed equally to provisioning in California. Higher male provisioning in Alaska appeared to facilitate a higher proportion of time females spent brooding the nestlings. Surprisingly, differences in brooding between populations could not be explained by variation in ambient temperature, which was similar between populations during the nestling period. While these results represent a single population contrast, they suggest additional hypotheses for the ecological correlates and evolutionary drivers of geographic variation in brooding behavior, and the factors that shape the contributions of each sex.

Journal of Avian Biology↗