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USGS2002

Collaborative approaches to the evolution of migration and the development of science-based conservation in shorebirds

Shorebirds are among the most highly migratory creatures on earth. Both the study of their ecology and ongoing efforts to conserve their populations must reflect this central aspect of their biology. Many species of shorebirds use migration and staging sites scattered throughout the hemisphere to complete their annual migrations between breeding areas and nonbreeding habitats (Morrison 1984). The vast distances between habitats they use pose significant challenges for studying their migration ecology. At the same time, the large number of political boundaries shorebirds cross during their epic migrations create parallel challenges for organizations working on their management and conservation. Nebel et al. (2002) represent a collaborative effort to understand the conservation implications of Western Sandpiper ( Calidris mauri ) migration ecology on a scale worthy of this highly migratory species. The data sets involved in the analysis come from four U.S. states, two Canadian provinces, and a total of five nations. Only by collaborating on this historic scale were the authors able to assemble the information necessary to understand important aspects of the migration ecology of this species, and the implications for conservation of the patterns they discovered. Collaborative approaches to shorebird migration ecology developed slowly over several decades. The same period also saw the creation of large-scale efforts to monitor and conserve shorebirds. This overview first traces the history of the study of migration ecology of shorebirds during that fertile period, and then describes the monitoring and protection efforts that have been developed in an attempt to address the enormous issues of scale posed by shorebird migration ecology and conservation.

The Auk↗

USGS2021

Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist

Quantifying the contribution of habitat dynamics relative to intrinsic population processes in regulating species persistence remains an ongoing challenge in ecological and applied conservation. Understanding these drivers and their relationship is essential for managing habitat‐dependent species, especially those that specialize in transitional habitats. Limitations in the ability of natural disturbance to mediate transitional habitat dynamics have resulted in a decline in early‐ and mid‐successional vegetation structure and prompted the need for aggressive habitat management to replace natural perturbations and increase habitat structural complexity. We describe a collaborative effort with a group of independent land managers to design an adaptive management program for restoring an imperiled ecosystem and recovering declining populations of an endemic habitat specialist. We developed a set of integrated, hierarchical models to estimate management‐mediated transition rates among vegetation classes in two dominant scrub communities and the species response (local colonization and extinction probabilities) as a function of habitat state. Models were fit using a long‐term data set of habitat and occupancy observations from 361 Florida scrub‐jay territories across two Florida counties. Occupancy model results correspond closely to previous approaches of estimating differential survival and reproductive success associated with habitat conditions, with highest colonization and lowest extinction rates estimated for those habitat states found to have the highest rates of survival and reproduction. In addition to offering an innovative approach for jointly modeling habitat and species population dynamics, the program we describe will also be of interest from a management perspective by providing guidance for developing collaborative, adaptive management frameworks from the ground up. We engaged land managers via workshops to specify objectives and desired state‐variable conditions, identify management alternatives, and elicit consensus opinions on model parameters. Treating expert opinions as pseudo‐observations to define Dirichlet priors allowed us to make use of existing management knowledge. Formal learning was then accumulated by updating transition probability estimates as management activities were implemented over the study period. We believe this adaptive management framework provides a useful approach for increasing our understanding of complex ecological relationships and hope that it will be adopted by others who have interest in informing management and conservation efforts.

Florida↗

USGS2015

Management applications of discontinuity theory

Human impacts on the environment are multifaceted and can occur across distinct spatiotemporal scales. Ecological responses to environmental change are therefore difficult to predict, and entail large degrees of uncertainty. Such uncertainty requires robust tools for management to sustain ecosystem goods and services and maintain resilient ecosystems. We propose an approach based on discontinuity theory that accounts for patterns and processes at distinct spatial and temporal scales, an inherent property of ecological systems. Discontinuity theory has not been applied in natural resource management and could therefore improve ecosystem management because it explicitly accounts for ecological complexity. Synthesis and applications . We highlight the application of discontinuity approaches for meeting management goals. Specifically, discontinuity approaches have significant potential to measure and thus understand the resilience of ecosystems, to objectively identify critical scales of space and time in ecological systems at which human impact might be most severe, to provide warning indicators of regime change, to help predict and understand biological invasions and extinctions and to focus monitoring efforts. Discontinuity theory can complement current approaches, providing a broader paradigm for ecological management and conservation.

Journal of Applied Ecology↗

USGS2006

Bird communities of natural and modified habitats in Panama

Only a small proportion of land can realistically be protected as nature reserves and thus conservation efforts also must focus on the ecological value of agroecosystems and developed areas surrounding nature reserves. In this study, avian communities were surveyed in 11 habitat types in central Panama, across a gradient from extensive forest to intensive agricultural land uses, to examine patterns of species richness and abundance and community composition. Wooded habitats, including extensive and fragmented forests, shade coffee plantations, and residential areas supported the most species and individuals. Nearctic-Neotropical migratory species were most numerous in lowland forest fragments, shade coffee, and residential areas. Introduced Pinus caribbea and sugar cane plantations supported the fewest species compared to all other habitats. Cattle pastures left fallow for less than two years supported more than twice as many total species as actively grazed pastures, such that species richness in fallow pastures was similar to that found in wooded habitats. Community similarities were relatively low among all habitat types (none exceeding the observed 65% similarity between extensive and fragmented lowland forests), but communities in shade coffee and residential areas were 43% and 54′% similar to lowland forest fragments, respectively. Fallow pastures and residential areas shared 60% of their species. Bird communities in shade coffee and residential areas were characterized by higher proportions of frugivorous and nectarivorous species than in native forests. These same guilds also were better represented in fallow than in grazed pastures. Raptors and piscivorous species were most prevalent in cattle pastures and rice fields. These results, though based upon only species richness and abundance, demonstrate that many human-altered habitats have potential ecological value for birds, and conservation efforts in tropical areas should focus greater attention on enhancement of agricultural and developed lands as wildlife habitat. To understand the true conservation value of these modified lands will require examination not only of numbers but also of the types of species supported by these habitats, their reproductive output and survival rates.

Ecography↗

USGS2024

The status and conservation needs of the Micronesian Megapode (Megapodius laperouse laperouse) across the Mariana archipelago

Context Accurate baseline data for wildlife populations are important to track trends of these populations over time and to identify threats to their long-term persistence. Aims We aimed to assess the status and distribution of the little studied megapode ( Megapodius laperouse laperouse ) across the Mariana Islands. Methods Using passive and call playback facilitated surveys in 2008 through 2010, we employed point–transect distance sampling to assess island-level and archipelago-wide status of this megapode. To assess conservation needs, we defined human presence as the current, recent, or intermittent occurrence of humans on islands. Key results We recorded 657 megapode detections and estimated an archipelago level abundance of 11,542 individuals (95% CI: 5456–17,623) from 699 sampling points across 10 islands. Three islands supported 86% of the megapode population, but cumulatively comprise only 2% of the archipelago’s land area. Conclusions Micronesian Megapodes preferred native forest. Human presence and the availability of native forest may limit their abundance and distribution in the Mariana Islands. Although the probability of detecting megapodes was significantly greater on islands without high human presence, significantly more detections were recorded in forests with dense or closed understory on those islands that supported greater human populations. Implications Given their status and confined distribution in the Mariana Islands, additional studies investigating megapode incubation sites and movement within and between islands would provide fundamental information on megapode ecology and enhance conservation efforts. Continued and expanded ungulate removal, predator control, and habitat restoration would further enhance the likelihood of megapode persistence in the archipelago.

Pacific Conservation Biology↗

USGS2025

Using GPS tracking data to validate the conservation value of bird migration counts

Effective conservation of migratory birds requires gathering of information about their population trends, often acquired using migratory bird counts. These schemes ideally operate at migratory bottlenecks, through which a significant portion of the counted migratory populations is funneled. Yet it is rare to validate the conservation value of the data from these counts. Here we perform this validation using GPS tracking data collected from two migratory species during their movement over two count schemes: the globally endangered steppe eagle counted in Eilat, Israel, and the black kite, counted in Batumi, Georgia. We use tracking data to answer two questions: which populations are counted and what affects the probability that a given individual will be counted. Our results illustrate variability in the effectiveness of these two migratory bird counting schemes. Considering the goal of estimating population trends, we show that Eilat does not represent a good location for understanding population trends of steppe eagles, while Batumi appears to provide better information on demographic trends of black kites. We further present differences in annual and individual variability, evidence regarding the breeding area origins of the counted populations and effects of environmental factors on the raptors' routes and, consequently, on the probabilities of being counted. Beyond the direct implications of our results, this study provides an example of using telemetry data to parameterize inference from bird counts. Further coupling of migratory bird count data and GPS data can improve our understanding of migration ecology and the conservation of migratory species.

Biological Conservation↗

USGS2013

A spatial mark–resight model augmented with telemetry data

Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark-resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark-recapture. However, density estimation using mark-resight is difficult because the area sampled must be explicitly defined, historically using ad-hoc approaches. We develop a spatial mark-resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows <100% individual identification of marked individuals. We implemented the model in a Bayesian framework, using a custom-made Metropolis-within-Gibbs Markov chain Monte Carlo algorithm. As an example, we applied this model to a mark-resight study of raccoons on South Core Banks, a barrier island in Cape Lookout National Seashore, North Carolina. We estimated a population of 186.71 ± 14.81 individuals, which translated to a density of 8.29 ± 0.66 individuals per km 2 . The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.

Ecology↗

USGS2022

Spatially explicit management of genetic diversity using ancestry probability surfaces

1. Ecological restoration and conservation efforts are increasing worldwide and the management of intraspecific genetic variation in plants and animals, an important component of biodiversity, is increasingly valued. As a result, tailorable, spatially explicit approaches to map genetic variation are needed to support decision-making and management frameworks related to the recovery of threatened and endangered species and the maintenance of genetic resources in species utilized by humans, such as for restoration or agricultural purposes. 2. Here, we describe and demonstrate a workflow to spatially interpolate patterns of genetic differentiation using novel functions in the R package POPMAPS ( Pop ulation M anagement using A ncestry P robability S urfaces). Our approach uses empirical genetic data to estimate ancestry coefficients across a user-defined landscape correlated with patterns of differentiation in the focal species. The resulting surface, which we term the ancestry probability surface, includes two components: hard population boundaries and estimations of uncertainty that represent confidence in population assignments (i.e., ancestry probabilities). 3. An ancestry probability surface developed for Hilaria jamesii , an important graminoid utilized in restoration across the western United States, demonstrates the functionality of POPMAPS . Genetic distances among empirical sites correlated better with least-cost distances across suitable habitat than with geographic distances, informing the surface over which the interpolation was conducted (i.e., a model indicating habitat suitability). A jackknifing procedure identified parameter values resulting in robust population assignments across the species’ range, which were utilized in downstream analyses to estimate ancestry coefficients from empirical data. Ancestry coefficients were translated into ancestry probabilities, which tended to be low for cells that were intermediate in distance between empirical sampling locations representing different populations or when influenced by empirical sampling locations with mixed genetic ancestry. 4. POPMAPS allows users to tailor parameter values and analytical approaches and thereby incorporate species-specific biological characteristics and desired levels of uncertainty into maps illustrating patterns of genetic differentiation. Ancestry probability surfaces may be used to guide management or investigate further ecological or evolutionary hypotheses. We discuss how maps produced by POPMAPS can inform multiple management challenges including species recovery planning and the utilization of commonly used species in restoration.

Methods in Ecology and Evolution↗

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↗