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USGS2019

The past and future roles of competition and habitat in the range‐wide occupancy dynamics of Northern Spotted Owls

Slow ecological processes challenge conservation. Short‐term variability can obscure the importance of slower processes that may ultimately determine the state of a system. Furthermore, management actions with slow responses can be hard to justify. One response to slow processes is to explicitly concentrate analysis on state dynamics. Here, we focus on identifying drivers of Northern Spotted Owl ( Strix occidentalis caurina ) territorial occupancy dynamics across 11 study areas spanning their geographic range and forecasting response to potential management actions. Competition with Barred Owls ( Strix varia ) has increased Spotted Owl territory extinction probabilities across all study areas and driven recent declines in Spotted Owl populations. Without management intervention, the Northern Spotted Owl subspecies will be extirpated from parts of its current range within decades. In the short term, Barred Owl removal can be effective. Over longer time spans, however, maintaining or improving habitat conditions can help promote the persistence of northern spotted owl populations. In most study areas, habitat effects on expected Northern Spotted Owl territorial occupancy are actually greater than the effects of competition from Barred Owls. This study suggests how intensive management actions (removal of a competitor) with rapid results can complement a slower management action (i.e., promoting forest succession).

Ecological Applications↗

USGS2011

Range-wide assessment of livestock grazing across the sagebrush biome

Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and synthesize recommendations from federal and university rangeland science experts about how BLM might prioritize collection of different types of livestock grazing-related natural resource data. 4. Investigate whether range-wide datasets (Objective 1) could be used in conjunction with remotely sensed imagery to identify across broad scales (a) allotments potentially not meeting BLM Land Health Standards (LHS) and (b) allotments in which unmet standards might be attributable to livestock grazing. Objective 1: We identified four datasets that potentially could be used for analyses of livestock grazing effects on sagebrush ecosystems. First, we obtained the most current spatial data (typically up to 2007, 2008, or 2009) for all BLM allotments and compiled data into a coarse, topologically enforced dataset that delineated grazing allotment boundaries. Second, we obtained LHS evaluation data (as of 2007) for all allotments across all districts and regions; these data included date of most recent evaluation, BLM determinations of whether region-specific standards were met, and whether BLM deemed livestock to have contributed to any unmet standards. Third, we examined grazing records of three types: Actual Use (permittee-reported), Billed Use (BLM-reported), and Permitted Use (legally authorized). Finally, we explored the possibility of using existing Natural Resources Conservation Service (NRCS) Ecological Site Description (ESD) data to make up-to-date estimates of production and forage availability on BLM allotments. Objective 2: We investigated the availability of BLM livestock grazing-related monitoring data and the status of LHS across 310 randomly selected allotments in 13 BLM field offices. We found that, relative to other data types, the most commonly available monitoring data were Actual Use numbers (permittee-reported livestock numbers and season-of-use), followed by Photo Point, forage Utilization, and finally, Vegetation Trend measurement data. Data availability and frequency of data collection varied across allotments and field offices. Analysis of the BLM's LHS data indicated 67 percent of allotments analyzed were meeting standards. For those not meeting standards, livestock were considered the causal factor in 45 percent of cases (about 15 percent of all allotments). Objective 3: We sought input from 42 university and federal rangeland science experts about how best to prioritize rangeland monitoring activities associated with ascertaining livestock impacts on vegetation resources. When we presented a hypothetical scenario to these scientists and asked them to prioritize monitoring activities, the most common response was to measure ground and vegetation cover, a variable that in many cases (10 of 13 field offices sampled) BLM had already identified as a monitoring priority. Experts identified several other traditional (for example, photo points) and emerging approaches (for example, high-resolution aerial photography) to monitoring. Objective 4: We used spatial allotment data (described in Objective 1) and remotely sensed vegetation data (sagebrush cover, herbaceous vegetation cover, litter and bare soil) to assess differences in allotment LHS status ("Not met" vs. "Met"; if "Not met" - livestock-caused vs. not). We then developed logistic regression models, using vegetation variables to predict LHS status of BLM allotments in sagebrush steppe habitats in Wyoming and portions of Montana and Colorado. In general, we found that more consistent data collection at the local level might improve suitability of data for broad-scale analyses of livestock impacts. As is, data collection methodologies varied across field offices and States, and we did not find any local-level monitoring data (Actual Use, Utilization, Vegetation Trend) that had been collected consistently enough over time or space for range-wide analyses. Moreover, continued and improved emphasis on monitoring also may aid local management decisions, particularly with respect to effects of livestock grazing. Rangeland science experts identified ground cover as a high monitoring priority for assessing range condition and emphasized the importance of tracking livestock numbers and grazing dates. Ultimately, the most effective monitoring program may entail both increased data collection effort and the integration of alternative monitoring approaches (for example, remote sensing or monitoring teams). In the course of our study, we identified three additional datasets that could potentially be used for range-wide analyses: spatial allotment boundary data for all BLM allotments range-wide, LHS evaluations of BLM allotments, and livestock use data (livestock numbers and grazing dates). It may be possible to use these spatial datasets to help prioritize monitoring activities over the extensive land areas managed by BLM. We present an example of how we used spatial allotment boundary data and LHS data to test whether remotely sensed vegetation characteristics could be used to predict which allotments met or did not meet LHS. This approach may be further improved by the results of current efforts by BLM to test whether more intensive (higher resolution) LHS assessments more accurately describe land health status. Standardized data collection in more ecologically meaningful land units may improve our ability to use local-level data for broad-scale analyses.

Open-File Report↗

USGS2011

Catfish science: Status and trends in the 21st century

Catfish science, the study of the fish order Siluriformes, is a diverse and expanding field in terms of advances and breadth of topics. We compiled literature from primary fisheries journals as an index of interest and advances in catfish science to examine temporal trends in the field. The number of catfish scientific publications varied over the past century with strong peaks during 1975–1979 and 2005–2010, which may be the result of interactive scientific and societal influences. Catfish biology was the predominant publication topic until the late 1990s, when ecology, techniques, and management publications became more prevalent. Articles on catfish ecology were most numerous in both the first and second international catfish symposia, but publications on techniques and conservation were more numerous in the second catfish symposium than the first. We summarize the state of knowledge, recent advances, and areas for future attention among topics in catfish science, including sampling and aging techniques, population dynamics, ecology, fisheries management, species diversity, nonnative catfish, and human dimensions, with an emphasis on the gains in this second symposium. Areas that we expect to be pursued in the future are development of new techniques and validation of existing methods; expansion of research to less-studied catfish species; broadening temporal, spatial, and organizational scales; interdisciplinary approaches; and research on societal views and constituent demands. Meeting these challenges will require scientists to span beyond their professional comfort zones to effectively reach higher standards. We look forward to the coming decade and the many advances in the conservation, ecology, and management of catfish that will be shared.

Conference Paper↗

USGS2022

Evaluating sources of bias in pedigree-based estimates of breeding population size

Applications of genetic-based estimates of population size are expanding, especially for species for which traditional demographic estimation methods are intractable due to the rarity of adult encounters. Estimates of breeding population size ( N S ) are particularly amenable to genetic-based approaches as the parameter can be estimated using pedigrees reconstructed from genetic data gathered from discrete juvenile cohorts, therefore eliminating the need to sample adults in the population. However, a critical evaluation of how genotyping and sampling effort influence bias in pedigree reconstruction, and how these biases subsequently influence estimates of N S , is needed to evaluate the efficacy of the approach under a range of scenarios. We simulated a model system to understand the interactive effects of genotyping and sampling effort on error in genetic pedigrees reconstructed from the program COLONY . We then evaluated how errors in pedigree reconstruction influenced bias and precision in estimates of N S using three different rarefaction estimators. Results indicated that pedigree error can be minimal when adequate genetic data are available, such as when juvenile sample sizes are large and/or individuals are genotyped at many informative loci. However, even in cases for which data are limited, using results of the simulation analysis to understand the magnitude and sources of bias in reconstructed pedigrees can still be informative when estimating N S . We applied results of the simulation analysis to evaluate Nˆ S for a population of federally endangered Atlantic sturgeon ( Acipenser oxyrinchus oxyrinchus ) in the Delaware River, USA. Our results indicated that N S is likely to be three orders of magnitude lower compared with historic breeding population sizes, which is a considerable advancement in our understanding of the population status of Atlantic sturgeon in the Delaware River. Our analyses are broadly applicable in the design and interpretation of studies seeking to estimate N S and can help to guide conservation decisions when ecological uncertainty is high. The utility of these results is expected to grow as rapid advances in genetic technologies increase the popularity of genetic population monitoring and estimation.

Delaware, New Jersey, Pennsylvania↗

USGS2021

eDNA metabarcoding outperforms traditional fisheries sampling and reveals fine-scale heterogeneity in a temperate freshwater lake

Understanding biodiversity in aquatic systems is critical to ecological research and conservation efforts, but accurately measuring species richness using traditional methods can be challenging. Environmental DNA (eDNA) metabarcoding, which uses high-throughput sequencing and universal primers to amplify DNA from multiple species present in an environmental sample, has shown great promise for augmenting results from traditional sampling to characterize fish communities in aquatic systems. Few studies, however, have compared exhaustive traditional sampling with eDNA metabarcoding of corresponding water samples at a small spatial scale. We intensively sampled Boardman Lake (1.4 km 2 ) in Michigan, USA, from May to June in 2019 using gill and fyke nets and paired each net set with lake water samples collected in triplicate. We analyzed water samples using eDNA metabarcoding with 12S and 16S fish-specific primers and compared estimates of fish diversity among methods. In total, we set 60 nets and analyzed 180 1 L lake water samples. We captured a total of 12 fish species in our traditional gear and detected 40 taxa in the eDNA water samples, which included all the species observed in nets. The 12S and 16S assays detected a comparable number of taxa, but taxonomic resolution varied between the two genes. In our traditional gear, there was a clear difference in the species selectivity between the two net types, and there were several species commonly detected in the eDNA samples that were not captured in nets. Finally, we detected spatial heterogeneity in fish community composition across relatively small scales in Boardman Lake with eDNA metabarcoding, but not with traditional sampling. Our results demonstrated that eDNA metabarcoding was substantially more efficient than traditional gear for estimating community composition, highlighting the utility of eDNA metabarcoding for assessing species diversity and informing management and conservation.

Michigan↗

USGS2018

Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi , which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which maximizes the use of available resources. Increased implementation of approaches that consider detection error promote ecological advancements and conservation and management decisions that are better informed.

Oklahoma↗

USGS2021

The influence of floral resources and microclimate on pollinator visitation in an agro-ecosystem

As agriculture expands to meet the needs of a growing global population, natural ecosystems are threatened by deforestation and habitat fragmentation. Tropical agroforestry systems offer a sustainable alternative to traditional agriculture by providing food for production while also supporting biodiversity and ecosystem services. Previous studies have shown that these systems may even improve crop pollination, but the mechanisms of how these improvements occur are still poorly understood. Using coffee as a focal crop, we explored how microclimatic conditions affected nectar traits (sugar and caffeine concentration) important for pollinator visitation. We also studied how microclimate, floral traits, floral availability at the coffee plant level, availability of floral resources provided by other plant species in the agroecosystem (neighborhood floral availability), and the presence of other bees affected the amount of time bees spent foraging on coffee flowers and the proportion of coffee pollen carried on their bodies. We explored these factors using the two dominant coffee species farmed on Puerto Rico, Coffea canephora and C. arabica , under sun and shade management. We found that high nectar sugar concentration and temperature were important predictors of short floral visits (<15 seconds), while increased number of bees and open coffee flowers were important predictors of longer floral visits (16-180 seconds). High nectar caffeine concentration was an important predictor of longer visits on C. arabica flowers while the opposite was observed for C. canephora flowers. For both species, high coffee floral availability was the main predicting factor for the proportion of coffee pollen on the bees bodies. Surprisingly, neither neighborhood floral availability nor the type of coffee plantation (agroforest/shade or sun) were important predictors of bee visitation. These results suggest non-coffee flowering plants in coffee plantations were neither competitors nor facilitators of coffee plantes for pollinators. Additionally, most of the bees surveyed were carrying 80% pollen from one species ( C. arabica or C. canephora ), likely resulting in little heterospecific pollen deposition between Coffea and non-Coffea flowers. Shade trees in coffee plantations do not detract from pollinator visitation to coffee flowers, suggesting that the provision of multiple ecological and wildlife conservation benefits by shade trees is not in conflict with a growers ability to maximize the benefits of insect pollination on fruit production.

Adjuntas Lares,Las Marias, Maricao, Puerto Rico Ut↗

USGS2015

Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia

Accurate information on the density and abundance of animal populations is essential for understanding species' ecology and for conservation planning, but is difficult to obtain. The endangered orangutan ( Pongo spp.) is an example; due to its elusive behavior and low densities, researchers have relied on methods that convert nest counts to orangutan densities and require substantial effort for reliable results. Camera trapping and spatial capture–recapture (SCR) models could provide an alternative but have not been used for primates. We compared density estimates calculated using the two methods for orangutans in the Wehea Forest, East Kalimantan, Indonesia. Camera trapping/SCR modeling produced a density estimate of 0.16 ± 0.09–0.29 indiv/km 2 , and nest counts produced a density estimate of 1.05 ± 0.18–6.01 indiv/km 2 . The large confidence interval of the nest count estimate is probably due to high variance in nest encounter rates, indicating the need for larger sample size and the substantial effort required to produce reliable results using this method. The SCR estimate produced a very low density estimate and had a narrower but still fairly wide confidence interval. This was likely due to unmodeled heterogeneity and small sample size, specifically a low number of individual captures and recaptures. We propose methodological fixes that could address these issues and improve precision. A comparison of the overall costs and benefits of the two methods suggests that camera trapping/SCR modeling can potentially be a useful tool for assessing the densities of orangutans and other elusive primates, and warrant further investigation to determine broad applicability and methodological adjustments needed.

East Kalimantan↗

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↗

USGS2022

Visualizing social-ecological intensities for management of recreation visitors in a multiuse system

Accounting for the variation of visitor conflicts and ecological disturbance of outdoor recreation activities across space and time can cause difficulty for managers seeking to make decisions in social-ecological systems (SESs). We develop a method to quantify and visualize social and ecological intensities resulting from outdoor recreation. We demonstrate the utility of our method at Valentine National Wildlife Refuge, where we conducted onsite surveys for an entire year of recreationists participating in consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing) and nonconsumptive (e.g., hiking) activities. We use survey results and combine them with expert consensus by engaging refuge managers and scientists (i.e., Delphi method) to chart patterns in social (e.g., visitor conflicts) and ecological (e.g., damages to natural resources) intensities across multiple spatial and temporal scales. We highlight unexpected patterns that are revealed by collectively considering multi-activity groups through space and time and combining different survey methods (onsite, Delphi method). Based on the consensus reached using the Delphi method , the consumptive group had the greatest potential for social conflicts and ecological disturbances. Social and ecological intensities (i.e., hotspots) of recreation varied across lake types and seasons, highlighting high-intensity areas and periods on the refuge. Accounting for diverse outdoor recreation activities and coinciding social and ecological intensities will allow managers of SESs the ability to concomitantly preserve ecological resources, prioritize conservation efforts, and minimize visitor conflicts. We demonstrate the utility and ease of use of this technique, which can be implemented by managers and scientists within their respective SES of interest.

Nebraska↗

USGS2013

Network modularity reveals critical scales for connectivity in ecology and evolution

For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

Nature Communications↗

USGS2009

Quantitative studies of bird movement: A methodological review

The past several years have seen development of a number of statistical models and methods for drawing inferences about bird movement using data from marked individuals. It can be difficult to keep up with this rapid development of new methods, so our purpose here is to categorize and review methods for drawing inferences about avian movement. We also outline recommendations about future work dealing both with methods development and actual studies directed at hypotheses about bird movement of interest from conservation, management, or ecological perspectives.

Bird Study↗

USGS2016

Revisiting Paine’s 1966 sea star removal experiment, the most-cited empirical article in the American Naturalist

“Food Web Complexity and Species Diversity” (Paine 1966) is the most-cited empirical article published in the American Naturalist . In short, Paine removed predatory sea stars ( Pisaster ochraceus ) from the rocky intertidal and watched the key prey species, mussels ( Mytilus californianus ), crowd out seven subordinate primary space-holding species. However, because these mussels are a foundational species, they provide three-dimensional habitat for over 300 associated species inhabiting the mussel beds; thus, removing sea stars significantly increases community-wide diversity. In any case, most ecologists cite Paine (1966) to support a statement that predators increase diversity by interfering with competition. Although detractors remained skeptical of top-down effects and keystone concepts, the paradigm that predation increases diversity spread. By 1991, “Food Web Complexity and Species Diversity” was considered a classic ecological paper, and after 50 years it continues to influence ecological theory and conservation biology.

American Naturalist↗

USGS2024

Advancing at-risk species recovery planning in an era of rapid ecological change with a transparent, flexible, and expert-engaged approach

In the face of unprecedented ecological changes, the conservation community needs strategies to recover species at risk of extinction. On the Island of Maui, we collaborated with species experts and managers to assist with climate-resilient recovery planning for 36 at-risk native plant species by identifying priority areas for the management of recovery populations. To do this, we developed a tailored spatial conservation prioritization (SCP) approach distinguished by its emphasis on transparency, flexibility, and expert (TFE) engagement. Our TFE SCP approach consisted of 2 iterative steps: first, the generation of multiple candidate conservation footprints (i.e., prioritization solutions) with a flexible greedy algorithm that reflects conservation practitioners’ priorities and, second, the selection of an optimal conservation footprint based on the consideration of trade-offs in expert-agreed criteria among footprints. This process maximized buy-in by involving conservation practitioners and experts throughout, from setting goals to reviewing optimization data, defining optimization rules, and designating planning units meaningful to practitioners. We minimized the conservation footprint area necessary to meet recovery goals while incorporating species-specific measures of habitat suitability and climate resilience and retaining species-specific information for guiding recovery efforts. Our approach reduced the overall necessary conservation area by 36%, compared with selecting optimal recovery habitats for each species separately, and still identified high-quality habitat for individual species. Compared with prioritizr (an existing SCP tool), our approach identified a conservation area of equal size but with higher quality habitat. By integrating the strengths of existing techniques in a flexible and transparent design, our approach can address natural resource management constraints and provide outputs suitable for local recovery planning, consequently enhancing engagement and buy-in from conservation practitioners and experts. It demonstrates a step forward in making conservation planning more responsive to real-world complexities and helps reduce barriers to implementation for local conservation practitioners.

Hawaii↗

USGS2003

Multiple stressor effects in relation to declining amphibian populations

Original research discusses the protocols and approaches to studying the effects of multiple environmental stressors on amphibian populations and gives new perspectives on this complicated subject. This new publication integrates a variety of stressors that can act in concert and may ultimately cause a decline in amphibian populations. Sixteen peer-reviewed papers cover: Toxicity Assessment examines methods, which range from long-established laboratory approaches for evaluating adverse chemical effects to amphibians, to methods that link chemicals in surface waters, sediments, and soils with adverse effects observed among amphibians in the field. Field and Laboratory Studies illustrates studies in the evaluation of multiple stressor effects that may lead to declining amphibian populations. A range of laboratory and field studies of chemicals, such as herbicides, insecticides, chlorinated organic compounds, metals, and complex mixtures are also included. Causal Analysis demonstrates the range of tools currently available for evaluating "cause-effect" relationships between environmental stressors and declining amphibian populations. Audience: This new publication is a must-have for scientists and resource management professionals from diverse fields, including ecotoxicology, chemistry, ecology, field biology, conservation biology, and natural resource management.

Special Technical Report↗

USGS2007

Distinctiveness, use, and value of midwestern oak savannas and woodlands as avian habitats

Oak savannas and woodlands historically covered millions of hectares in the midwestern United States but are rare today. We evaluated the ecological distinctiveness and conservation value of savannas and woodlands by examining bird distributions across a fire-maintained woody-vegetation gradient in northwest Indiana encompassing five habitats—open habitats with low canopy cover, savannas, woodlands, scrublands, and forests—during migration, breeding, and overwintering. Savannas and woodlands were significantly different in overall bird species composition from open and forest habitats but were often intermediate between open and forest in guild densities. Few bird species were consistently and highly concentrated in savannas or woodlands, and the Red-headed Woodpecker ( Melanerpes erythrocephalus ) was the only species significantly more abundant in savannas and woodlands than in open, scrub, and forest habitats. Fire frequency over a 15-year interval was a significant predictor of bird community composition and was positively related to species diversity, spring transient migrant density, and density of the most threatened species. Each habitat type had characteristics potentially important for avian conservation. Scrub had the highest density of transient migrants, which suggests it plays an important role as migration stopover habitat. More species were significantly concentrated in open or forest habitats than in the other habitats. Lack of species concentration and intermediate community composition suggested that birds experienced savannas and woodlands more as ecotones than as habitats distinct from forests or grasslands. However, this intermediate character can benefit conservation, as evidenced by savannas and woodlands having the highest density of the most threatened species along this woody-vegetation gradient.

The Auk↗

USGS2014

Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications

Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several downscaled climate projections (or downscaled datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these downscaled datasets, known as downscaling, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for downscaling and the number of downscaled datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available downscaled datasets, how do these model outputs compare to each other? Which variables are available, and are certain downscaled datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these downscaled datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.

Open-File Report↗

USGS2004

Effects of Abandoned Coal-Mine Drainage on Streamflow and Water Quality in the Mahanoy Creek Basin, Schuylkill, Columbia, and Northumberland Counties, Pennsylvania, 2001

This report assesses the contaminant loading, effects to receiving streams, and possible remedial alternatives for abandoned mine drainage (AMD) within the Mahanoy Creek Basin in east-central Pennsylvania. The Mahanoy Creek Basin encompasses an area of 157 square miles (407 square kilometers) including approximately 42 square miles (109 square kilometers) underlain by the Western Middle Anthracite Field. As a result of more than 150 years of anthracite mining in the basin, ground water, surface water, and streambed sediments have been adversely affected. Leakage from streams to underground mines and elevated concentrations (above background levels) of acidity, metals, and sulfate in the AMD from flooded underground mines and (or) unreclaimed culm (waste rock) degrade the aquatic ecosystem and impair uses of the main stem of Mahanoy Creek from its headwaters to its mouth on the Susquehanna River. Various tributaries also are affected, including North Mahanoy Creek, Waste House Run, Shenandoah Creek, Zerbe Run, and two unnamed tributaries locally called Big Mine Run and Big Run. The Little Mahanoy Creek and Schwaben Creek are the only major tributaries not affected by mining. To assess the current hydrological and chemical characteristics of the AMD and its effect on receiving streams, and to identify possible remedial alternatives, the U.S. Geological Survey (USGS) began a study in 2001, in cooperation with the Pennsylvania Department of Environmental Protection and the Schuylkill Conservation District. Aquatic ecological surveys were conducted by the USGS at five stream sites during low base-flow conditions in October 2001. Twenty species of fish were identified in Schwaben Creek near Red Cross, which drains an unmined area of 22.7 square miles (58.8 square kilometers) in the lower part of the Mahanoy Creek Basin. In contrast, 14 species of fish were identified in Mahanoy Creek near its mouth at Kneass, below Schwaben Creek. The diversity and abundance of fish species in Mahanoy Creek decreased progressively upstream from 13 species at Gowen City to only 2 species each at Ashland and Girardville. White sucker (Catostomus commersoni), a pollution-tolerant species, was present at each of the surveyed reaches. The presence of fish at Girardville was unexpected because of the poor water quality and iron-encrusted streambed at this location. Generally, macroinvertebrate diversity and abundance at these sites were diminished compared to Schwaben Creek and other tributaries draining unmined basins, consistent with the observed quality of streamwater and streambed sediment. Data on the flow rate and chemistry for 35 AMD sources and 31 stream sites throughout the Mahanoy Creek Basin were collected by the USGS during high base-flow conditions in March 2001 and low base-flow conditions in August 2001. A majority of the base-flow streamwater samples met water-quality standards for pH (6.0 to 9.0); however, few samples downstream from AMD sources met criteria for acidity less than alkalinity (net alkalinity = 20 milligrams per liter as CaCO3) and concentrations of dissolved iron (0.3 milligram per liter) and total manganese (1.0 milligram per liter). Iron, aluminum, and various trace elements including cobalt, copper, lead, nickel, and zinc, were present in many streamwater samples at concentrations at which continuous exposure can not be tolerated by aquatic organisms without an unacceptable effect. Furthermore, concentrations of sulfate, iron, manganese, aluminum, and (or) beryllium in some samples exceeded drinking-water standards. Other trace elements, including antimony, arsenic, barium, cadmium, chromium, selenium, silver, and thallium, did not exceed water-quality criteria for protection of aquatic organisms or human health. Nevertheless, when considered together, concentrations of iron, manganese, arsenic, cadmium, chromium, copper, lead, nickel, and zinc in a majority of the streambed sediment samples from Mahanoy Creek and

Scientific Investigations Report↗