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At least 1,729 records · Page 96Linked to original sources
USGS2022

Controlling invasive fish in fluctuating environments: Model analysis of common carp (Cyprinus carpio) in a shallow lake

Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.

Oregon↗
USGS2022

Evaluating temporal and spatial transferability of a tidal inundation model for foraging waterbirds

For ecosystem models to be applicable outside their context of development, temporal and spatial transferability must be demonstrated. This presents a challenge for modeling intertidal ecosystems where spatiotemporal variation arises at multiple scales. Models specializing in tidal dynamics are generally inhibited from having wider ecological applications by coarse spatiotemporal resolution or high user competency. The Tidal Inundation Model of Shallow-water Availability (TiMSA) uniquely simulates tides to empirically derive a time-integrated measure of availability for a shallow-water depth range defined by the user. To evaluate temporal and spatiotemporal transferability, we employed TiMSA at the development site in the Florida Keys and at novel subsites in the Florida Bay (application site) under a different time period (application period). We used foraging little blue herons ( Egretta caerulea ) as the ecological unit with which to constrain the model's “water depth window,” that is, range of water depths to estimate shallow-water availability. At the development site, temporally consistent water depth windows contrasted with interannual variation in shallow-water availability, which revealed short-term changes in Little Blue Heron foraging habitat. At the application site, water depth accuracy varied by subsite and was correlated with spatial error in bathymetric elevation. Although TiMSA parameters were sensitive to environmental temporal variation and uncertainty in spatial data, a spatially explicit water depth window generated reliable estimates of shallow-water conditions over space and time at the development and application sites. By exploring the contributing factors to model error, we provide solutions to reduce uncertainty of TiMSA parameters at potential application sites and recommendations for addressing bathymetric inaccuracy in digital elevation models. Accurately quantifying spatiotemporal changes of shallow water has implications for monitoring habitat conditions for tidally influenced species and projecting future changes to coastal ecosystems in response to anthropogenic stressors and natural disturbances such as sea level rise.

Florida↗
USGS2022

Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world

Drylands represent more than 41% of the global land surface and are at degradation risk due to land use and climate change. Developing strategies to mitigate degradation and restore drylands in the face of these threats requires an understanding of how drylands are shaped by not only soils and climate, but also geology and geomorphology. However, few studies have completed such a comprehensive analysis that relates spatial variation in plant communities to all aspects of the geologic–geomorphic–edaphic–plant–climate system. The focus of this study is the Colorado Plateau, a high-elevation dryland in the southwestern United States, which is particularly sensitive to future change due to climate vulnerability and increasing land-use pressure. Here, we examined 135 long-term vegetation-monitoring sites in three national parks and characterized connections between geology, geomorphology, soils, climate, and dryland plant communities. To first understand the geologic and geomorphic influences on soil formation and characteristics, we explore associations between soil pedons, bedrock geology, and geomorphology. Then, we characterize principal axes of variation in plant communities and ascertain controls and linkages between components of the edaphic–geomorphic system and plant community ordinations. Geologic and geomorphic substrate exerted controls on important properties of the soil profile, particularly depth, water-holding capacity, rockiness, salinity, and fine sands. Ordination identified five distinct plant communities and three primary axes of variation, representing gradients of woody- to herbaceous-dominated communities (Axis 1), saline scrublands to C 3 grasslands (Axis 2), and annual to perennial communities (Axis 3). Geology, geomorphology, and soil explained a large proportion of variation in Axis 1 (74%), while climate variables largely explained Axis 2 (68%), and Axis 3 was not well explained by the random forest models. The variables identified as most influential to each axis were, respectively: (1) soil depth; (2) aridity, lithology, and soil salinity; and (3) temperature and precipitation. We posit that Axis 3 represents a land degradation gradient due to historic grazing, likely exacerbated by dry conditions. Results provide a novel framework that links the geologic and geomorphic evolution of landscapes, with the distribution of soils and plant communities that can guide ecosystem management, exemplifying an approach applicable to drylands globally.

Arizona, Colorado, New Mexico, Utah↗
USGS2022

Sea otters in a California estuary: Detecting temporal and spatial dynamics with volunteer monitoring

Volunteer monitoring can support conservation of imperiled wildlife, by providing higher resolution data in space and time than those available from professional scientists. However, concerns have been raised that data collected by amateurs are inaccurate or inconsistent and thus do not allow for robust detection of spatial or temporal trends. We evaluated the rigor and value of volunteer monitoring data for one iconic wildlife species, the southern sea otter ( Enhydra lutris nereis ), in Elkhorn Slough estuary in central California, USA, and explored whether volunteer monitoring could provide added value to complement limited professional surveys. First, we compiled and analyzed sea otter counts taken on daily ecotourist boat trips along the estuary, and then compared temporal patterns to data collected by professional scientists tasked with monitoring this federally listed species. Second, we analyzed data on sea otter abundance, habitat use, and behavior collected by a team of trained volunteers, the Elkhorn Slough Reserve Otter Monitoring Program. Overall, we demonstrated the ability to detect important ecological patterns relevant to sea otter conservation and wetland habitat management using volunteer-derived datasets. Long-term trends and inter-annual variability were similar between professional agency monitoring data and volunteer datasets. Moreover, the much higher frequency of volunteer observations allowed for seasonal and tidal dynamics to be detected that could not be revealed by less frequent professional monitoring. We found higher sea otter abundance in the estuary in spring–summer, indicating seasonality in use of the estuary. We detected differences in habitat use of the estuary between higher and lower tides, and greater frequency of foraging at low tide and in certain areas. Volunteer observations revealed fine-scale differences in habitat use: eelgrass beds were used much more heavily than adjacent areas only a few meters away. Volunteer data can thus provide critical information about coastal habitat use and behavior that can improve conservation strategies for threatened wildlife species.

California↗
USGS2023

Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta

Terminal channels were historically a common feature of tidal delta ecosystems but have become increasingly rare as landscapes have been modified. Tidal hydrodynamics are a defining feature in tidal terminal channel ecosystems from which native aquatic communities have evolved. However, few studies have explored the relationship between fish community structure and hydrodynamics in these tidal terminal channel ecosystems. We sampled fish communities throughout a network of terminal channels within the northeasternmost region of the San Francisco Estuary to determine the relationship between fish community structure and hydrodynamics within these environments. We collected two years (2017 and 2018) of fish community samples using gill nets and analyzed data using multivariate community analyses and count models. We found metrics of fish diversity and counts of native fishes to be greatest upstream (farthest from tidal influence) of the tidal excursion within terminal channels. Counts of non-native fishes were less affected by this hydrodynamic feature of terminal channels and more tightly correlated to local habitat conditions (e.g., water temperature, depth). Our results suggest that channel hydrodynamics plays a role in structuring fish communities within terminal channels, particularly native fishes. These results indicate that hydrodynamics in tidal delta ecosystems may be able to be altered in ways that benefit native fishes without the cost of water pumping.

California↗
USGS2023

Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration

Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza viruses (AIVs). Although infection with low pathogenic AIVs is generally considered asymptomatic in wild birds, prior work has shown that influenza-infected birds occasionally delay migration and/or reduce local movements relative to their uninfected counterparts. However, most observational research to date has focused on a few species in northern Europe; given that influenza viruses are widespread globally and outbreaks of highly pathogenic strains are increasingly common, it is important to explore influenza–movement relationships across more species and regions. Here, we used telemetry data to investigate relationships between influenza infection and movement behavior in 165 individuals from four species of North American waterfowl that overwinter in California, USA. We studied both large-scale migratory and local overwintering movements and found that relationships between influenza infection and movement patterns varied among species. Northern pintails ( Anas acuta ) with antibodies to avian influenza, indicating prior infection, made migratory stopovers that averaged 12 days longer than those with no influenza antibodies. In contrast, greater white-fronted geese ( Anser albifrons ) with antibodies to avian influenza made migratory stopovers that averaged 15 days shorter than those with no antibodies. Canvasbacks ( Aythya valisineria ) that were actively infected with influenza upon capture in the winter delayed spring migration by an average of 28 days relative to birds that were uninfected at the time of capture. At the local scale, northern pintails and canvasbacks that were actively infected with influenza used areas that were 7.6 and 4.9 times smaller than those of uninfected ducks, respectively, during the period of presumed active influenza infection. We found no evidence for an influence of active influenza infection on local movements of mallards ( Anas platyrhynchos ). These results suggest that avian influenza can influence waterfowl movements and illustrate that the relationships between avian influenza infection and wild bird movements are context- and species-dependent. More generally, understanding and predicting the spread of multihost pathogens requires studying multiple taxa across space and time.

Ecosphere↗
USGS2024

Spatial extent drives patterns of relative climate change sensitivity for freshwater fishes of the United States

Assessing the sensitivity of freshwater species to climate change is an essential component of prioritizing conservation efforts for threatened freshwater ecosystems and organisms. Sensitivity to climate change can be systematically evaluated for multiple species using geographic attributes such as range size and climate niche breadth, and using species traits associated with climate change sensitivity. These systematic evaluations produce relative rankings of species sensitivity to aid conservation prioritization and to identify relatively sensitive species that may otherwise be understudied or overlooked. Due in part to biogeographic constraints, species assemblages change across regions and spatial extents; yet, the degree to which spatial factors influence relative rankings of species sensitivity is unclear. The spatial extent of multispecies analyses may alter relative rankings of species climate sensitivity; alternatively, relative climate sensitivity may be conserved among spatial scales, resulting in consistent identification of sensitive species among regions and spatial extents. We investigated how spatial extent influences our understanding of relative climate sensitivity for 137 native freshwater fishes of the United States that were representative of taxonomic, trait, and geographic diversity. Using publicly available occurrence data from the Global Biodiversity Information Facility, we calculated a systematic, geographically derived index of climate change sensitivity for study species at national and regional extents, including within four major hydrologic subregions of the United States. We examined the effects of spatial extent on the relative ranking of climate sensitivity among species, and we explored relationships among climate sensitivity, species traits, and conservation status at regional and national extents. We found that climate sensitivity rankings of species were influenced by spatial extent in some specific instances, but that relative rankings were largely conserved across spatial scales. However, correlations among geographically derived climate sensitivity rankings and species traits associated with climate sensitivity were variable across scales and regions, suggesting that links between geographic rarity and species traits may be scale-dependent in some cases. Finally, we found few associations between climate sensitivity and current conservation status among species. Systematic approaches to quantifying climate sensitivity may offer an opportunity to identify sensitive but overlooked species for pre-listing actions such as monitoring or conservation agreements.

Ecosphere↗
USGS2024

Evaluating the effects of nest management on a recovering raptor using integrated population modeling

Evaluating population responses to management is a crucial component of successful conservation programs. Models predicting population growth under different management scenarios can provide key insights into the efficacy of specific management actions both in reversing population decline and in maintaining recovered populations. Bald eagle ( Haliaeetus leucocephalus ) conservation in the United States has seen many successes over the last 50 years, yet the extent to which the bald eagle population has recovered in Arizona, an important population within the Southwest region, remains an area of debate. Estimates of the species' population trend and an evaluation of ongoing nest-level management practices are needed to inform management decisions. We developed a Bayesian integrated population model (IPM) and population viability analysis (PVA) using a 36-year dataset to assess Arizona bald eagle population dynamics and their underlying demographic rates under current and possible future management practices. We estimated that the population grew from 77 females in 1993 to 180 females in 2022, an average yearly increase of 3%. Breeding sites that had trained personnel (i.e., nestwatchers) stationed at active nests to mitigate human disturbance had a 28% higher reproductive output than nests without this protection. Uncertainty around population trends was high, but scenarios that continued the nestwatcher program were less likely to predict abundance declines than scenarios without nestwatchers. Here, the IPM-PVA framework provides a useful tool both for estimating the effectiveness of past management actions and for exploring the management needs of a delisted population, highlighting that continued management action may be necessary to maintain population viability even after meeting certain recovery criteria.

Arizona↗
USGS2024

The effects of spatio-temporal variation in marine resources on the occupancy dynamics of a terrestrial avian predator

Identifying how species respond to system drivers such as weather, climate, habitat, and resource availability is critical in understanding population change. In coastal areas, the transfer of nutrients across the marine and terrestrial interface increases complexity. Nesting populations of bald eagles ( Haliaeetus leucocephalus ) along the Pacific coast of North America, although terrestrial, are largely dependent on marine resources during the breeding season and therefore represent a good focal species for understanding linkages of nutrients between terrestrial and marine systems. Due to their location, coastal eagle populations are susceptible to a variety of climate-induced perturbations, from both land and sea. The northeast Pacific Marine Heatwave (PMH) of 2014-2016 had wide-ranging impacts on the marine ecosystem and provided an opportunity to explore how marine conditions can impact terrestrial wildlife populations. We used a spatially-explicit multi-state occupancy modeling framework to analyze >30yrs of bald eagle nest occupancy data collected in four large national parks along a coastal-interior gradient in Alaska, USA. We assessed occupancy state in relation to weather conditions, salmon abundance, access to alternate prey resources, and the PMH event to help elucidate the factors affecting bald eagle occupancy dynamics over time. We found that occupancy probability was higher in areas where prey resources were concentrated (e.g., near seabird colonies, where bears facilitate access to salmon carcasses). We also found that the probability of reproductive success was higher during warmer, drier springs with higher-than-average salmon abundance. After the onset of the marine heatwave, success declined in the areas most dependent on non-salmon marine resources. These findings confirm the importance of spring weather conditions and access to salmon resources during the critical chick-rearing period, but also reveal that marine heatwaves may have important secondary effects through a reduction in the overall quantity or quality of prey available to bald eagles. Given ongoing warming at high latitudes and the expectation that marine heatwaves will become more common, our findings are useful for understanding ongoing and future changes in the transfer of nutrients from marine to terrestrial ecosystems and how such changes may impact terrestrial species such as bald eagles.

Alaska↗
USGS2025

Winter tick sharing between ungulates in the Greater Yellowstone Ecosystem and implications for apparent competition

Host species heterogeneity can drive parasite dynamics through variation in host competency as well as host abundance. We explored how elk ( Cervus canadensis ) with apparent subclinical infestations of winter tick ( Dermacentor albipictus ) may be a cryptic reservoir and drive winter tick dynamics, impacting moose ( Alces alces ) populations. We found that winter tick infestation loads did not vary remarkably between both host species and winter ticks sourced from elk and moose produced similar numbers of larvae which activated within 5 days of each other. We also found similar larval densities in habitats predominately used by elk, moose, and both host species. Our analysis of 2793 informative single-nucleotide polymorphisms showed genetic differentiation among tick populations that were only ~75 km apart, but fewer differences among ticks from elk or moose in the same locality, suggesting sharing of winter ticks across host species. Despite the clinical signs of high winter tick infestations being most apparent on moose, elk may be critical drivers of winter tick population dynamics and indirectly compete with moose in areas where they outnumber moose populations, a common characteristic of ungulate communities in western North America. Management interventions aimed at addressing winter tick issues on moose may wish to consider the movement patterns and abundance of cryptic reservoirs like elk.

Wyoming↗
USGS2025

Cytotype and local adaptation drive phenotypic variation in two subspecies of big sagebrush (Artemisia tridentata)

Big sagebrush ( Artemisia tridentata ) is a widespread and locally dominant shrub throughout many ecosystems in western North America. A. tridentata ssps. tridentata and wyomingensis are two subspecies whose populations occupy the warm-arid regions of the species range and whose trailing edge is threatened by climate change. Previous studies have presented conflicting results in relation to the genetic control of physiological variation in A. tridentata . Understanding how different genetic factors contribute to physiological variation can provide insight into how these two subspecies may respond to future climate change. To explore possible variation among and within two subspecies of A. tridentata , we measured physiological and morphological traits in A . t . tridentata and A. t. wyomingensis during mid-summer (July), seven years after establishment in a common garden. Contributions to trait variation were quantified for both genetic (subspecies and cytotype) and environmental (climate-of-origin) factors. Measurements revealed an unequal contribution to phenotypic variation by subspecies, cytotype, and climate-of-origin. Ploidy and climate-of-origin were more important than subspecies in driving phenotypic variation in A. tridentata. These findings suggest that A. tridentata has a highly plastic drought response, or that culling (mortality over time due to environmental factors) in the common garden over seven years has led to a lack of genetic diversity within the garden. Understanding what factors drive phenotypic expression in big sagebrush can provide better insight into how climate change may affect migration and extirpation and may aid in the effectiveness of restoration efforts.

Idaho↗
USGS2025

Assessing the effects of climate and visitor use on amphibian occupancy in a protected landscape with long-term data

Determining where animals are, and if they are persisting across protected landscapes, is necessary to implement appropriate management and conservation actions. For long-lived animals and those with boom-and-bust life histories, perspective across time contributes to discerning temporal trends in occupancy and persistence, and potentially in identifying mechanisms affecting those parameters. Long-term data are particularly useful in protected areas to quantify indicators of change that may be less obvious or occur more slowly. We used long-term amphibian data from Rocky Mountain National Park (RMNP) in a Bayesian occupancy modeling framework to estimate changes in occupancy, colonization, and persistence of amphibians over three decades and to explore the effects of climate, landscape change, and visitor use as mechanisms behind observed changes. Our results indicate that colonization and persistence are low and/or declining for Pseudacris maculata , Lithobates sylvaticus , and Ambystoma mavortium , and that occupied catchments are increasingly isolated. We found visitor use to have a consistently negative effect on occupancy and persistence of amphibians in RMNP, and that all species are more likely to occupy catchments with more complex habitat and a higher proportion of wetlands. While these results are sobering, they also provide a way forward where mitigation efforts can target identified drivers of change.

Colorado↗
USGS2026

Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins

Climatic extremes can impact the productivity of aquatic species, affecting ecosystems and fishery-dependent communities. Advances in climate products, such as gridded datasets and downscaled projections, may be useful for quantifying freshwater habitat conditions and predicting climate change effects on fish. However, limited guidance exists for selecting climate products to develop indicators of freshwater habitat conditions that influence fish population dynamics. Here, we develop an approach for identifying streamflow and stream temperature models to address this need. We evaluated skill in predicted versus observed streamflow and stream temperature, with predictions depending on different models and gridded climate data as inputs. The best performing models were used in a case study exploring habitat conditions influencing Chinook salmon in the Yukon and Kuskokwim River basins, two remote high-latitude watersheds with few in situ habitat observations and recent salmon declines. Three modeled streamflow datasets had variable performance (median Nash–Sutcliffe efficiencies from 0.39 to 0.70). Three gridded temperature products differed in their ability to explain variation in weekly stream temperatures (median r 2 from 0.42 to 0.76). We selected a single gridded air temperature dataset to compare two novel predictive stream temperature models, both of which had good accuracy (root mean squared error [RMSE] of 1.19 and 0.95°C). Stream temperature indicators calculated from modeled daily data, maximum temperatures during adult migration and cumulative temperatures during juvenile rearing, had high spatial correlation across tributaries within the Yukon and Kuskokwim River basins and showed significant warming over the past 40 years. Streamflow indicators calculated from modeled daily data, maximum flow during spawning and median flow during rearing, had few trends and were largely uncorrelated within the Yukon River basin and moderately correlated within the Kuskokwim River basin. Overall, we found that generic measures of model performance varied considerably, and it was important to consider the models best suited to our case study. For both streamflow and stream temperature, multiple high-performing models allowed estimation of ecologically relevant conditions affecting Chinook salmon. The approach we used to estimate local-scale habitat conditions has value to identify synchronous conditions that may influence multiple salmon populations under a changing subarctic climate.

Alaska↗
USGS2026

American kestrel population trends and vital rates at the continental scale

The American kestrel ( Falco sparverius , hereafter referred to as kestrel) has declined across much of its North American range since at least the mid-1960s. Kestrel population dynamics have been explored through a multitude of local studies and two broad reviews of available data. Across large geographic extents, however, the demographic cause(s) of kestrel population declines remain(s) largely unknown. As part of a collaborative effort to elucidate the drivers of kestrel population declines, we developed a continental-scale integrated population model using band-recovery data, productivity data, and Breeding Bird Survey indices from 1986 to 2019 to estimate indices of annual population sizes, survival, and productivity rates across the continental United States. We detected a decline in population size of ~1%–2% per year. Overall estimates of population growth from 1986 to 2019 suggest a 29% decline in population size (95% CI = −34% to −23%). There was little evidence of a trend in brood size. However, survival of juvenile birds (mean = −0.015, SD = 0.008 and mean = −0.024, SD = 0.010 for females and males, respectively) and adult males (mean = −0.016, SD = 0.010) in the summer declined, suggesting that these vital rates could be contributing to declines in populations over time. Winter adult survival rates (mean = −0.004, SD = 0.009 and mean = −0.009, SD = 0.010 for females and males, respectively) also declined but to a lesser extent than summer survival. For juvenile birds, winter survival increased (mean = 0.006, SD = 0.008 and mean = 0.002, SD = 0.009 for females and males, respectively); however, this was not enough to offset declines in summer survival and annual survival rates declined over the time series. Annual adult survival was also low relative to previous research on kestrel survival rates. Given the importance of survival to population trends, our findings provide support for several previously proposed broad classes of factors potentially contributing to observed population declines: declines in arthropod prey, second-generation rodenticides, neonicotinoid insecticides, and predation.

Ecosphere↗
USGS2017

The interacting roles of climate, soils, and plant production on soil microbial communities at a continental scale

Soil microbial communities control critical ecosystem processes such as decomposition, nutrient cycling, and soil organic matter formation. Continental scale patterns in the composition and functioning of microbial communities are related to climatic, biotic, and edaphic factors such as temperature and precipitation, plant community composition, and soil carbon, nitrogen, and pH. Although these relationships have been well explored individually, the examination of the factors that may act directly on microbial communities vs. those that may act indirectly through other ecosystem properties has not been well developed. To further such understanding, we utilized structural equation modeling (SEM) to evaluate a set of hypotheses about the direct and indirect effects of climatic, biotic, and edaphic variables on microbial communities across the continental United States. The primary goals of this work were to test our current understanding of the interactions among climate, soils, and plants in affecting microbial community composition, and to examine whether variation in the composition of the microbial community affects potential rates of soil enzymatic activities. A model of interacting factors created through SEM shows several expected patterns. Distal factors such as climate had indirect effects on microbial communities by influencing plant productivity, soil mineralogy, and soil pH, but factors related to soil organic matter chemistry had the most direct influence on community composition. We observed that both plant productivity and soil mineral composition were important indirect influences on community composition at the continental scale, both interacting to affect organic matter content and microbial biomass and ultimately community composition. Although soil hydrolytic enzymes were related to the moisture regime and soil carbon, oxidative enzymes were also affected by community composition, reflected in the abundance of soil fungi. These results highlight that soil microbial communities can be modeled within the context of multiple interacting ecosystem properties acting both directly and indirectly on their composition and function, and this provides a rich and informative context with which to examine communities. This work also highlights that variation in climate, microbial biomass, and microbial community composition can affect maximum rates of soil enzyme activities, potentially influencing rates of decomposition and nutrient mineralization in soils.

Ecology↗
USGS2018

Inferring species interactions through joint mark–recapture analysis

Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub ( Gila cypha ) and introduced rainbow trout ( Oncorhynchus mykiss ) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.

Ecology↗
USGS2019

Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.

Ecology↗
USGS2019

Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?

Occupancy models are widely applied to estimate species distributions, but few methods exist for model checking. Thorough model assessments can uncover inadequacies and allow for deeper ecological insight by exploring structure in the observed data not accounted for by a model. We introduce occupancy model residual definitions that utilize the posterior distribution of the partially latent occupancy states. Residual‐based assessments are valuable because they can target specific assumptions and identify ways to improve a model, such as adding spatial correlation or meaningful covariates. Our approach defines separate residuals for occupancy and detection, and we use simulation to examine whether missing structure for modeling detection probabilities can be distinguished from that for occupancy probabilities. In many scenarios, our residual diagnostics were able to successfully separate inadequacies at the different model levels, but we describe other situations when this may not be the case. Applying Moran's I residual diagnostics to assess models for silver‐haired (Lasionycteris noctivagans) and little brown (Myotis lucifugus) bats only provided evidence of residual spatial correlation among detections. Targeting specific model assumptions using carefully chosen residual diagnostics is valuable for any analysis, and we remove previous barriers for occupancy analyses — lack of examples and practical advice.

Ecology↗