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At least 55 records · Page 3Linked to original sources
USGS2014

A multi-indicator framework for mapping cultural ecosystem services: The case of freshwater recreational fishing

Despite recent interest, ecosystem services are not yet fully incorporated into private and public decisions about natural resource management. Cultural ecosystem services (CES) are among the most challenging of services to include because they comprise complex ecological and social properties and processes that make them difficult to measure, map or monetize. Like others, CES are vulnerable to landscape changes and unsustainable use. To date, the sustainability of services has not been adequately addressed and few studies have considered measures of service capacity and demand simultaneously. To facilitate sustainability assessments and management of CES, our study objectives were to (1) develop a spatially explicit framework for mapping the capacity of ecosystems to provide freshwater recreational fishing, an important cultural service, (2) map societal demand for freshwater recreational fishing based on license data and identify areas of potential overuse, and (3) demonstrate how maps of relative capacity and relative demand could be interfaced to estimate sustainability of a CES. We mapped freshwater recreational fishing capacity at the 12-digit hydrologic unit-scale in North Carolina and Virginia using a multi-indicator service framework incorporating biophysical and social landscape metrics and mapped demand based on fishing license data. Mapping of capacity revealed a gradual decrease in capacity eastward from the mountains to the coastal plain and that fishing demand was greatest in urban areas. When comparing standardized relative measures of capacity and demand for freshwater recreational fishing, we found that ranks of capacity exceeded ranks of demand in most hydrologic units, except in 17% of North Carolina and 5% of Virginia. Our GIS-based approach to view freshwater recreational fishing through an ecosystem service lens will enable scientists and managers to examine (1) biophysical and social factors that foster or diminish cultural ecosystem services delivery, (2) demand for cultural ecosystem services relative to their capacity, and (3) ecological pressures like potential overuse that affect service sustainability. Ultimately, we expect such analyses to inform decision-making for freshwater recreational fisheries and other cultural ecosystem services.

Ecological Indicators↗
USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗
USGS2023

Holocene vegetation dynamics of circum-Arctic permafrost peatlands

Vegetation shifts in circum-Arctic permafrost peatlands drive feedbacks with important consequences for peatland carbon budgets and the extent of permafrost thaw under changing climate. Recent shrub expansion across Arctic tundra environments has led to an increase in above-ground biomass, but the long-term spatiotemporal dynamics of shrub and tree growth in circum-Arctic peatlands remain unquantified. We investigate changes in peatland vegetation composition during the Holocene using previously-published plant macrofossil records from 76 sites across the circum-Arctic permafrost zone. In particular, we assess evidence for peatland shrubification at the continental scale. We identify increasing abundance of woody vegetation in circum-Arctic peatlands from ∼8000 years BP to present, coinciding with declining herbaceous vegetation and widespread Sphagnum expansion. Ecosystem shifts varied between regions and present-day permafrost zones, with late-Holocene shrubification most pronounced where permafrost coverage is presently discontinuous and sporadic. After ∼600 years BP, we find a proliferation of non-Sphagnum mosses in Fennoscandia and across the present-day continuous permafrost zone; and rapid expansion of Sphagnum in regions of discontinuous and isolated permafrost as expected following widespread fen-bog succession, which coincided with declining woody vegetation in eastern and western Canada. Since ∼200 years BP, both shrub expansion and decline were identified at different sites across the pan-Arctic, highlighting the complex ecological responses of circum-Arctic peatlands to post-industrial climate warming and permafrost degradation. Our results suggest that shrubification of circum-Arctic peatlands has primarily occurred alongside surface drying, resulting from Holocene climate shifts, autogenic peat accumulation, and permafrost aggradation. Future shrubification of circum-Arctic peatlands under 21st century climate change will likely be spatially heterogeneous, and be most prevalent where dry microforms persist.

Quaternary Science Reviews↗
USGS2018

Population trends in Vermivora warblers are linked to strong migratory connectivity

Migratory species can experience limiting factors at different locations and during different periods of their annual cycle. In migratory birds, these factors may even occur in different hemispheres. Therefore, identifying the distribution of populations throughout their annual cycle (i.e., migratory connectivity) can reveal the complex ecological and evolutionary relationships that link species and ecosystems across the globe and illuminate where and how limiting factors influence population trends. A growing body of literature continues to identify species that exhibit weak connectivity wherein individuals from distinct breeding areas co-occur during the nonbreeding period. A detailed account of a broadly distributed species exhibiting strong migratory connectivity in which nonbreeding isolation of populations is associated with differential population trends remains undescribed. Here, we present a range-wide assessment of the nonbreeding distribution and migratory connectivity of two broadly dispersed Nearctic-Neotropical migratory songbirds. We used geolocators to track the movements of 70 Vermivora warblers from sites spanning their breeding distribution in eastern North America and identified links between breeding populations and nonbreeding areas. Unlike blue-winged warblers ( Vermivora cyanoptera ), breeding populations of golden-winged warblers ( Vermivora chrysoptera ) exhibited strong migratory connectivity, which was associated with historical trends in breeding populations: stable for populations that winter in Central America and declining for those that winter in northern South America.

Proceedings of the National Academy of Sciences of↗
USGS2022

Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin.

Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.

Amazon River basin↗
USGS2009

The assembly, collapse and restoration of food webs

Darwin chose the metaphor of a 'tangled bank' to conclude the 'Origin of species'. Two centuries after Darwin's birth, we are still untangling the complex ecological networks he has pondered. In particular, studies of food webs provide important insights into how natural ecosystems function (Pascual & Dunne 2005). Although the nonlinear interactions between many species creates challenges of scale, resolution of data and significant computational constraints, the last 10 years have seen significant advances built on the earlier classic studies of Cohen, May, Pimm, Polis, Lawton and Yodzis (May 1974; Cohen 1978; Pimm 1982; Briand & Cohen 1984, 1987; Yodzis 1989; Cohen et al. 1990; Pimm et al. 1991; Yodzis & Innes 1992; Yodzis 1998). These gains stem from advances in computing power and the collation of more comprehensive data from a broader array of empirical food webs.

Philosophical Transactions of the Royal Society B:↗
USGS2020

Effects of snowpack, temperature, and disease on the demography of a wild population of amphibians

Understanding the demographic consequences of interactions among pathogens, hosts, and weather conditions is critical in determining how amphibian populations respond to disease and in identifying site-specific conservation actions that can be developed to bolster persistence of amphibian populations. We investigated population dynamics in Boreal Toads ( Anaxyrus boreas ) relative to abiotic (fall temperatures and snowpack) and biotic (the abundance of another anuran host and disease) characteristics of the local environment in Wyoming, USA. We used capture–recapture data and a multistate model where state was treated as a hidden Markov process to incorporate disease state uncertainty and assess our a priori hypotheses. Our results indicated that snowpack during the coldest week of winter is more influential to toad survival, disease transition probabilities, and the population-level prevalence of the amphibian chytrid fungus ( Batrachochytrium dendrobatidis ) in the spring, than temperatures in the fall or the presence of another host. As hypothesized, apparent survival at low (i.e., <25 cm) snowpack (0.22; confidence interval [CI] = 0.15–0.31) was lower than apparent survival at high snowpack (90.65; CI = 0.50–0.78). Our findings highlight the potential for local environmental factors, like snowpack, to influence disease and host persistence, and demonstrate the ecological complexity of disease effects on population demography in natural environments. This work further emphasizes the need for improved understanding of how climate change may influence the relationships among pathogens, hosts, and their environment for wild animal populations challenged by disease.

Wyoming↗
USGS2015

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup ( Aythya ) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Ecological Applications↗
USGS2017

Methods for measuring bird-mediated seed rain: Insights from a Hawaiian mesic forest

Amount and diversity of bird-dispersed seed rain play important roles in determining forest composition, yet neither is easy to quantify. The complex ecological processes that influence seed movement make the best approach highly context specific. Although recent advances in seed rain theory emphasize quantifying source-specific seed shadows, many ecological questions can be addressed u sing a less mechanistic approach that requires fewer assumptions. Using seed rain rates from 0.38 m 2 hoop traps sampled twice monthly over the course of a year, we show that number of traps required to identify changes in seed rain varies across seed species and forest type. Detecting a 50% increase in amount of seed rain required from 65 to >300 traps, while detecting a 200% increase generally required ≤⃒50 traps. Trap size and ecological context dictate the number of seeds found in each trap, but the coefficient of variation (CV) across traps in a given ecological context can help inform future studies about number of traps needed to detect change. To better understand factors influencing variation around estimates of seed rain, we simulated both clustered and evenly distributed patterns of fecal deposition using three different levels of seed aggregation (number of seeds in each fecal deposit). When patterns of fecal deposition were clustered, rather than evenly dispersed across the study area, they required >1.5 times the number of traps to identify a 100% increase in seed rain. Similarly, we found that low seed aggregation required >1.5 times the number of traps to detect a 100% change than when aggregation was medium or high. At low aggregations, fewer seed rain traps contained seeds (low, 33 ± 5%; medium, 23 ± 4%; high, 24 ± 5%), resulting in more variation across traps than medium and high aggregations. We also illustrate the importance of training observers to discern between morphologically similar seeds from different species and provide resources to help identify bird-dispersed seeds commonly found within midelevation mesic Hawaiian forests.

Hawaii↗
USGS2001

The environment and human health; USGS science for solutions

Emerging infectious diseases, ground-water contamination, trace-metal poisoning...environmental threats to public health the world over require new solutions. Because of an increased awareness of the issues, greater cooperation among scientific and policy agencies, and powerful new tools and techniques to conduct research, there is new hope that complex ecological health problems can be solved. U.S. Geological Survey scientists are forming partnerships with experts in the public health and biomedical research communities to conduct rigorous scientific inquiries into the health effects of ecological processes.

Fact Sheet↗
USGS2008

Florida Integrated Science Center (FISC) Coral Reef Research

Coral reefs provide important ecosystem services such as shoreline protection and the support of lucrative industries including fisheries and tourism. Such ecosystem services are being compromised as reefs decline due to coral disease, climate change, overfishing, and pollution. There is a need for focused, integrated science to understand the complex ecological interactions and effects of these many stressors and to provide information that will effectively guide policies and best management practices to preserve and restore these important resources. The U.S. Geological Survey Florida Integrated Science Center (USGS-FISC) is conducting a coordinated Coral Reef Research Project beginning in 2009. Specific research topics are aimed at addressing priorities identified in the 'Strategic Science for Coral Ecosystems 2007-2011' document (U.S. Geological Survey, 2007). Planned research will include a blend of historical, monitoring, and process studies aimed at improving our understanding of the development, current status and function, and likely future changes in coral ecosystems. Topics such as habitat characterization and distribution, coral disease, and trends in biogenic calcification are major themes of understanding reef structure, ecological integrity, and responses to global change.

Fact Sheet↗
USGS2017

Skagit River coho salmon life history model—Users’ guide

Natural resource management is conducted in the context of multiple anthropogenic stressors and is further challenged owing to changing climate. Experiments to determine the effects of climate change on complex ecological systems are nearly impossible. However, using a simulation model to synthesize current understanding of key ecological processes through the life cycle of a fish population can provide a platform for exploring potential effects of and management responses to changing conditions. Potential climate-change scenarios can be imposed, responses can be observed, and the effectiveness of potential actions can be evaluated. This approach is limited owing to future conditions likely deviating in range and timing from conditions used to create the model so that the model is expected to become obsolete. In the meantime, however, the modeling process explicitly states assumptions, clarifies information gaps, and provides a means to better understand which relationships are robust and which are vulnerable to changing climate by observing whether and why model output diverges from actual observations through time. The purpose of the model described herein is to provide such a decision-support tool regarding coho ( Oncorhynchus kisutch ) salmon for the Sauk-Suiattle Indian Tribe of Washington State. The Skagit coho salmon model is implemented in a system dynamics format and has three primary stocks—(1) predicted smolts, (2) realized smolts, and (3) escapement. “Predicted smolts” are the number of smolts expected based on the number of spawners in any year and the Ricker production curve. Pink salmon ( Oncorhynchus gorbuscha ) return to the Skagit River in odd years, and when they overlap with juvenile rearing coho salmon, coho smolt production is substantially higher than in non-pink years. Therefore, the model uses alternative Ricker equations to predict smolts depending on whether their juvenile year was a pink or non-pink year. The stock “realized smolts” is calculated based on the expected effect of streamflow conditions to alter the productivity predicted by the Ricker curve. Adverse conditions include scouring flow events that occur when redds are present; high-flow events during winter on juveniles, which can cause fish displacement and adverse water turbidity; and extremely low flows in summer. The stock “escapement” represents the fish remaining after accounting for ocean mortality and harvest. Ocean mortality has been linked with indices of ocean conditions, which are related to ocean biological productivity. Ocean survival also may have a density-dependent component such that lower survival is associated with higher numbers of smolts. The model allows the user to change certain model parameters and inputs, and choose among alternative predictors for certain modeled relations.

Washington↗
USGS2021

Structured decision making and optimal bird monitoring in the northern Gulf of Mexico

The avian conservation community struggles to design and implement large scale, long-term coordinated bird monitoring programs within the northern Gulf of Mexico due to the complexity of the conservation enterprise in the region; this complexity arises from the diverse stakeholders, multiple jurisdictions, complex ecological processes, myriad habitats, and over 500 species of birds using the region for at least some part of their annual cycle. In addition, long-term monitoring over large spatial scales is difficult because of the need for monitoring data to both (1) evaluate management and restoration outcomes, and (2) provide reliable information about the status and trends of bird populations over time. To address these challenges, the Gulf of Mexico Avian Monitoring Network developed a problem statement: “How can a cost-effective monitoring strategy for the Gulf Coast bird community and ecosystem be developed that evaluates ongoing conservation activities and chronic and acute threats; maximizes learning; and is flexible and holistic enough to detect novel ecological threats and evaluate new and emerging conservation activities?” A structured decision-making framework was then used to articulate and quantify stakeholder values related to the problem statement. One use of the stakeholder values was to develop a regional, strategic plan for bird monitoring, which is presented elsewhere. A formal and complete decision support tool for conservation investments in monitoring and research guided by the stakeholder values is presented in this report. The technical aspects of the stakeholder value model and a portfolio analysis that could be used to guide decision making when allocating resources for monitoring activities is described. Whereas the decision analysis presented here could be useful to any decision maker faced with difficult choices about resource allocation, it is designed for decision makers who request monitoring study proposals and then determine which combination of proposals to fund. The portfolio decision support tool is designed to help funding agencies and organizations identify resource allocation strategies to maximize stated objectives. To begin the decision analysis, an objectives hierarchy and quantitative performance metrics from the values of the Gulf of Mexico bird conservation community were created by a panel of regional stakeholders. Each fundamental objective and sub-objective in the hierarchy is composed of several performance metrics. To test the decision support tool, the authors evaluated a combination of monitoring study proposals written for the region and simulated proposals. Each proposal was scored against the performance metrics and used multi-attribute utility theory to combine the multiple objectives into a measure of total monitoring benefit. The total monitoring benefit and costs of each proposal were then used in a constrained optimization routine to identify optimal monitoring portfolios, that is, a combination of activities that maximizes monitoring benefits while meeting cost and other constraints of interest to stakeholders. A graphical solution based on the concept of Pareto efficiency, which is useful in situations when cost constraints and exact budgets are not known, is also provided. Finally, an evaluation of the sensitivity of the decision-making framework to the weights assigned to objectives by stakeholders is included. This decision support tool allows decision makers to identify an optimal suite of monitoring proposals with a transparent portfolio analysis that includes user-defined constraints (such as costs).

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2001

Lessons learned from long-term ecosystem research and monitoring in alpine and subalpine basins of the Colorado Rocky Mountains, USA

Long-term ecosystem research and monitoring was begun in the Loch Vale watershed of Rocky Mountain National Park in 1983, after extensive survey work to identify the best location. Then, as now, our scientific objectives were to understand natural biogeochemical cycles and variability, so that we could differentiate ecosystem changes from human-caused disturbances, such as atmospheric deposition of pollutants and climate change. We have learned many lessons, often through our mistakes, that are worth passing on. Clear scientific objectives, even for long-term monitoring, are essential. Standardized methods, including rigorous quality assurance procedures should be adhered to from the beginning of the program. All data, even those collected routinely for background records, should be scrutinized and summarized at least once a year. Freely share basic information such as weather, hydrologic, chemical, and descriptive records with other researchers who can build upon your efforts. Use many tools when asking complex ecological questions, in order to minimize bias toward specific results. Publish frequently; long-term studies do not imply there are no interim conclusions or interesting findings. Interpret findings frequently to policy makers and citizens; increased understanding of the environment and human-caused changes may improve natural resource management, and build support for ecological research. And finally, be persistent. Long-term ecological research can be frustrating and difficult to maintain, yet is often the best way to observe and understand ecological change on a meaningful time scale.

Colorado↗
USGS2010

Stage structure alters how complexity affects stability of ecological networks

Resolving how complexity affects stability of natural communities is of key importance for predicting the consequences of biodiversity loss. Central to previous stability analysis has been the assumption that the resources of a consumer are substitutable. However, during their development, most species change diets; for instance, adults often use different resources than larvae or juveniles. Here, we show that such ontogenetic niche shifts are common in real ecological networks and that consideration of these shifts can alter which species are predicted to be at risk of extinction. Furthermore, niche shifts reduce and can even reverse the otherwise stabilizing effect of complexity. This pattern arises because species with several specialized life stages appear to be generalists at the species level but act as sequential specialists that are hypersensitive to resource loss. These results suggest that natural communities are more vulnerable to biodiversity loss than indicated by previous analyses.

Ecology Letters↗
USGS2005

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Science↗
USGS2015

Assessing the likely effectiveness of multispecies management for imperiled desert fishes with niche overlap analysis

A critical decision in species conservation is whether to target individual species or a complex of ecologically similar species. Management of multispecies complexes is likely to be most effective when species share similar distributions, threats, and response to threats. We used niche overlap analysis to assess ecological similarity of 3 sensitive desert fish species currently managed as an ecological complex. We measured the amount of shared distribution of multiple habitat and life history parameters between each pair of species. Habitat use and multiple life history parameters, including maximum body length, spawning temperature, and longevity, differed significantly among the 3 species. The differences in habitat use and life history parameters among the species suggest they are likely to respond differently to similar threats and that most management actions will not benefit all 3 species equally. Habitat restoration, frequency of stream dewatering, non-native species control, and management efforts in tributaries versus main stem rivers are all likely to impact each of the species differently. Our results demonstrate that niche overlap analysis provides a powerful tool for assessing the likely effectiveness of multispecies versus single-species conservation plans.

Conservation Biology↗
USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗