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USGS2020

Crossroads of highly pathogenic H5N1: overlap between wild and domestic birds in the Black Sea-Mediterranean impacts global transmission

Understanding transmission dynamics that link wild and domestic animals is a key element of predicting the emergence of infectious disease, an event that has highest likelihood of occurring wherever human livelihoods depend on agriculture and animal trade. Contact between poultry and wild birds is a key driver of the emergence of highly pathogenic avian influenza (HPAI), a process that allows for host-switching and accelerated reassortment, diversification and spread of virus between otherwise unconnected regions. This study addresses questions relevant to the spillover of HPAI at a transmission hotspot: what is the nature of the wild bird-poultry interface in Egypt and adjacent Black Sea-Mediterranean countries and how has this contributed to outbreaks occurring worldwide? Using a spatio-temporal model of infection risk informed by satellite tracking of waterfowl and viral phylogenetics, this study identified ecological conditions that contribute to spillover in this understudied region. Results indicated that multiple ducks (Northern Shoveler and Northern Pintail) hosted segments that shared ancestry with HPAI H5 from both clade 2.2.1 and clade 2.3.4 supporting the role of Anseriformes in linking viral populations in East Asia and Africa over large-distances. Quantifying the interface between wild ducks and H5N1-infected poultry revealed an increasing interface in late winter peaking in early spring when ducks expanded their range before migration, with key differences in the timing of poultry contact risk between local and long-distance migrants.

Virus Evolution↗

USGS2019

Integrated modeling reveals shifts in waterfowl population dynamics under climate change

1. Climate change has been identified as one of the most important drivers of wildlife populations. The development of appropriate conservation strategies relies on reliable predictions of population responses to climate change, which require in-depth understanding of the complex relationships between climate and population dynamics through density dependent demographic processes. Integrated population models (IPMs) are a type of modeling approach that unify the analyses of demography and abundance data, providing opportunities to understand and predict population demography and dynamics under climate change. 2. In this study we developed dynamic N-mixture models for large scale population estimates, which became an important component of the IPM we used in data analysis. We then analyzed four decades (1974-2014) of Mallard ( Anas platyrhynchos ) breeding population survey, band-recovery, and climate data covering a large spatial extent from North American prairies through boreal habitat to Alaska. Our goals were to examine the complex relationships among climate, density dependent processes, waterfowl population demography and dynamics, identify the key demographic parameters that are sensitive to climate change and are influential to population growth, and forecast population responses to climate change. 3. Our results revealed the interactive effects of temperature and density dependent processes on Mallard recruitment and to a less extent apparent survival. We also found that recruitment explained more variance of population growth than apparent survival. We then forecasted a decrease in Mallard breeding population density in the Northern Prairie Potholes and an increase in Mallard breeding population density in the northern part of our study area, indicating potential shifts in Mallard population dynamics under future climate change. 4. Synthesis and applications Different strategies need to be considered across regions to conserve waterfowl populations under climate change. Strategies that facilitate recruitment are essential for high-density populations that are relatively vulnerable to climate change. By contrast, low-density populations are relatively resilient to climate change and their habitats may serve as future climate refugia. Adaptive management is essential for evaluating management consequences. Our modelling framework approach can be easily adapted for other species and thus has wide applications in ecology and conservation.

Ecography↗

USGS2011

The human dimension of fire regimes on Earth

Humans and their ancestors are unique in being a fire‐making species, but ‘natural’ (i.e. independent of humans) fires have an ancient, geological history on Earth. Natural fires have influenced biological evolution and global biogeochemical cycles, making fire integral to the functioning of some biomes. Globally, debate rages about the impact on ecosystems of prehistoric human‐set fires, with views ranging from catastrophic to negligible. Understanding of the diversity of human fire regimes on Earth in the past, present and future remains rudimentary. It remains uncertain how humans have caused a departure from ‘natural’ background levels that vary with climate change. Available evidence shows that modern humans can increase or decrease background levels of natural fire activity by clearing forests, promoting grazing, dispersing plants, altering ignition patterns and actively suppressing fires, thereby causing substantial ecosystem changes and loss of biodiversity. Some of these contemporary fire regimes cause substantial economic disruptions owing to the destruction of infrastructure, degradation of ecosystem services, loss of life, and smoke‐related health effects. These episodic disasters help frame negative public attitudes towards landscape fires, despite the need for burning to sustain some ecosystems. Greenhouse gas‐induced warming and changes in the hydrological cycle may increase the occurrence of large, severe fires, with potentially significant feedbacks to the Earth system. Improved understanding of human fire regimes demands: (1) better data on past and current human influences on fire regimes to enable global comparative analyses, (2) a greater understanding of different cultural traditions of landscape burning and their positive and negative social, economic and ecological effects, and (3) more realistic representations of anthropogenic fire in global vegetation and climate change models. We provide an historical framework to promote understanding of the development and diversification of fire regimes, covering the pre‐human period, human domestication of fire, and the subsequent transition from subsistence agriculture to industrial economies. All of these phases still occur on Earth, providing opportunities for comparative research.

Journal of Biogeography↗

USGS2005

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

Journal of Ecology↗

USGS2011

The fundamental thermal niche of adult landlocked striped bass

Researchers have described the temperatures selected by landlocked striped bass Morone saxatilis in different locales throughout the USA. However, seasonally low concentrations of dissolved oxygen (DO) in many systems prevented striped bass from using the cool waters (<22??C) they may have preferred. In Melton Hill Reservoir, a 92-km-long impoundment on the Clinch River in east Tennessee, 15 adult striped bass were tagged with temperature-sensing radio tags and tracked for an average of 418 d in 1999-2000. Cold, hypolimnetic discharges from an upstream dam and heated discharge from a steam-generating electric facility near the midpoint of this run-of-the-river reservoir provided a broad range of temperatures in most seasons, and hypoxic habitats were uncommon even during stratification. The mean temperature occupied by striped bass varied seasonally (repeated-measures analysis of variance, P < 0.0001) and was highest in summer (17.5??C), intermediate in spring and fall (15.4-16.9??C), and lowest in winter (13.0??C). The mean and modal temperatures occupied during the growing season (May-October 1999) were 17.5??C and 19.0??C, respectively; 30% of the observations were between 9??C and 15??C. These data indicate that the fundamental thermal niche of adult landlocked striped bass may be lower than literature estimates. These results also represent the first unbiased field estimates of the influence of season on the thermal ecology of adult striped bass. The thermal characteristics of habitats considered optimal in habitat suitability index models for adult landlocked striped bass (i.e., 18-24??C) should be revised to include cooler waters. ?? Copyright by the American Fisheries Society 2005.

Transactions of the American Fisheries Society↗

USGS2005

Broad-scale predictors of canada lynx occurrence in eastern North America

The Canada lynx (Lynx canadensis) is listed as a threatened species throughout the southern extent of its geographic range in the United States. Most research on lynx has been conducted in the western United States and Canada; little is known about the ecology of lynx in eastern North America. To fill critical knowledge gaps about this species, we modeled and mapped lynx occurrence using habitat and weather data from 7 eastern states and 3 Canadian provinces. Annual snowfall, road density, bobcat (L. rufus) harvest, deciduous forest, and coniferous forest were compared at 1,150 lynx locations and 1,288 random locations. Nineteen a priori models were developed using the information-theoretic approach, and logistic regression models were ranked using Akaike's Information Criterion (AIC) and by our ability to correctly classify reserved data (Kappa). Annual snowfall and deciduous forest predicted lynx presence and absence for a reserved dataset (n = 278) with 94% accuracy. A map of the probability of lynx occurrence throughout the region revealed that 92% of the potential habitat (i.e., >50% probability of occurrence) was concentrated in a relatively contiguous complex encompassing northern Maine, New Brunswick, and the Gaspe?? peninsula of Quebec. Most of the remaining potential habitat (5%) was on northern Cape Breton Island in Nova Scotia. Potential habitat in New Hampshire, Vermont, and New York was small (1,252 km2), fragmented, and isolated (>200 km) from known lynx populations. When federally listed as threatened in the contiguous United States in 2000, inadequate regulations on federal lands were cited as the primary threat to Canada lynx. However, the majority of potential lynx habitat in the eastern United States is on private lands and continuous with potential habitat in Canada. Therefore, lynx conservation in eastern North America will need to develop partnerships across national, state, and provincial boundaries as well as with private landowners.

Journal of Wildlife Management↗

USGS2015

Sampling techniques for burbot in a western non-wadeable river

Burbot, Lota lota (L.), populations are declining throughout much of their native distribution. Although numerous aspects of burbot ecology are well understood, less is known about effective sampling techniques for burbot in lotic systems. Occupancy models were used to estimate the probability of detection ( ) for three gears (6.4- and 19-mm bar mesh hoop nets, night electric fishing), within the context of various habitat characteristics. During the summer, night electric fishing had the highest estimated detection probability for both juvenile ( , 95% C.I.; 0.35, 0.26–0.46) and adult (0.30, 0.20–0.41) burbot. However, small-mesh hoop nets (6.4-mm bar mesh) had similar detection probabilities to night electric fishing for both juvenile (0.26, 0.17–0.36) and adult (0.27, 0.18–0.39) burbot during the summer. In autumn, a similar overlap between detection probabilities was observed for juvenile and adult burbot. Small-mesh hoop nets had the highest estimated probability of detection for both juvenile and adult burbot (0.46, 0.33–0.59), whereas night electric fishing had a detection probability of 0.39 (0.28–0.52) for juvenile and adult burbot. By using detection probabilities to compare gears, the most effective sampling technique can be identified, leading to increased species detections and more effective management of burbot.

Fisheries Management and Ecology↗

USGS1985

Effects of flood control alternatives on fish and wildlife resources of the Malheur-Harney lakes basin

Malheur Lake is the largest freshwater marsh in the western contiguous United States and is one of the main management units of the Malheur National Wildlife Refuge in southeastern Oregon. The marsh provides excellent waterfowl production habitat as well as vital migration habitats for birds in the Pacific flyway. Water shortages have typically been a problem in this semiarid area; however, record snowfalls and cool summers have recently caused Malheur Lake to rise to its highest level in recorded history. This has resulted in the loss of approximately 57,000 acres of important wildlife habitat as well as extensive flooding of local ranches, roads, and railroad lines. Because of the importance of the Refuge, any water management plan for the Malheur-Harney Lakes Basin needs to consider the impact of management alternatives on the hydrology of Malheur Lake. The facilitated modeling workshop described in this report was conducted January 14-18, 1985, under the joint sponsorship of the Portland Ecological Services Field Office and the Malheur National Wildlife Refuge, Region 1, U.S. Fish and Wildlife Service (FWS). The Portland Field Office is responsible for FWS reporting requirements on Federal water resource projects while the Refuge staff has management responsibility for much of the land affected by high water levels in the Malheur-Harney Lakes Basin. The primary objective of the workshop was to begin gathering and analyzing information concerning potential fish and wildlife impacts, needs, and opportunities associated with proposed U.S. Army Corps of Engineers (COE) flood control alternatives for Malheur Lake. The workshop was structured around the formulation of a computer model that would simulate the hydrologic effects of the various alternatives and any concommitant changes in vegetation communities and wildlife use patterns. The simulation model is composed of three connected submodels. The Hydrology submodel calculates changes in lake volume, elevation, and surface area, as well as changes in water quality, that result from the proposed water management projects (upstream storage, upstream diversions, drainage canals) and the no action alternative. The Vegetation submodel determines associated changes in the areal extent of wetland and upland vegetation communities. Finally, the Wildlife submodel calculates indices of abundance or habitat suitability for colonial nesting birds (great egret, double-crested cormorant, white-faced ibis), greater sandhill crane, diving ducks, tundra swan, dabbling ducks, and Canada goose based on hydrologic and vegetation conditions. The model represents the Malheur-Harney Lakes Basin, but provides water quantity and quality indicators associated with additional flows that might occur in the Malheur River Basin. Several management scenarios, representing various flood control alternatives and assumptions concerning future runoff, were run to analyze model behavior. Scenario results are not intended as an analysis of all potential management actions or assumptions concerning future runoff. Rather, they demonstrate the type of analysis that could be conducted if the model was sufficiently refined and tested. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. This workshop initiated interaction among the primary State and Federal resource and development agencies in a nonadversarial forum. The exchange of information and expertise among agencies provided the FWS with the best information currently available for use in the Planning Aid Letter it will develop at the Reconnaissance state of the COE study. If the COE subsequently initiates a Feasability Study, this information will be refined further and will aid the FWS in preparing its Coordination Act Report on any flood control alternative proposed by the COE. The model building and testing process also helped identify model limitations and more general information needs that should be evaluated for further study prior to preparation of an FWS Coordination Act Report. Major needs associated with the Hydrology submodel include a more detailed representation of hydrologic units (separately consider Harney Lake, Mud Lake, and Malheur Lake or the three hydrological units within Malheur Lake, rather than a combined lake system) and explicitly representation of groundwater storage and discharge in water budget calculations. A better representation of the hydrological units will require more detailed topographic data for the basin, capacity-elevation and elevation-surface area curves for each unit, and better water flow data between the units. Additional water quality parameters and constraints on proposed canal operation due to conditions in the Malheur River might also be added. Key Vegetation submodel needs include fine-tuning existing vegetation relationships in the model and adding relationships to address the influence of historical conditions on vegetation development, effects of very rapid changes in lake level, effects of wildlife populations (e.g., carp, muskrat), responses of vegetation to habitat management actions (e.g, haying, grazing, burning), and better representation of sago pondweed dynamics. A complementary geographic information system might also be developed for spatial analyses. Major needs that should be evaluated for the Wildlife submodel include addition of other wildlife species that have important effects on habitat on the Refuge (e.g., carp, muskrat) and consideration of additional life-cycle requisites and controlling variable for species presently in the model. Some of these limitations could perhaps be overcome if historical data on habitat conditions were developed to use with historical data on wildlife populations.

Oregon↗

USGS2011

Conservation in the face of climate change: The roles of alternative models, monitoring, and adaptation in confronting and reducing uncertainty

The broad physical and biological principles behind climate change and its potential large scale ecological impacts on biota are fairly well understood, although likely responses of biotic communities at fine spatio-temporal scales are not, limiting the ability of conservation programs to respond effectively to climate change outside the range of human experience. Much of the climate debate has focused on attempts to resolve key uncertainties in a hypothesis-testing framework. However, conservation decisions cannot await resolution of these scientific issues and instead must proceed in the face of uncertainty. We suggest that conservation should precede in an adaptive management framework, in which decisions are guided by predictions under multiple, plausible hypotheses about climate impacts. Under this plan, monitoring is used to evaluate the response of the system to climate drivers, and management actions (perhaps experimental) are used to confront testable predictions with data, in turn providing feedback for future decision making. We illustrate these principles with the problem of mitigating the effects of climate change on terrestrial bird communities in the southern Appalachian Mountains, USA.

Southern Appalachian Mountains↗

USGS2023

Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data

The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl ( Strix occidentalis caurina ) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km 2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl ( Strix varia ), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.

Oregon↗

USGS2017

Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass

Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N -mixture model. Multinomial N -mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N -mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N -mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.

Missouri, Oklahoma↗

USGS2020

Assessing the ecological risks of per‐ and polyfluoroalkyl substances: Current state‐of‐the science and a proposed path forward

Per‐ and poly‐fluoroalkyl substances (PFAS) encompass a large, heterogenous group of chemicals of potential concern to human health and the environment. Based on information for a few relatively well‐understood PFAS such as perfluorooctane sulfonate and perfluorooctanoate, there is ample basis to suspect that at least a subset can be considered persistent, bioaccumulative, and/or toxic. However, data suitable for determining risks in either prospective or retrospective assessments are lacking for the majority of PFAS. In August 2019, the Society of Environmental Toxicology and Chemistry sponsored a workshop that focused on the state‐of‐the‐science supporting risk assessment of PFAS. The present review summarizes discussions concerning the ecotoxicology and ecological risks of PFAS. First, we summarize currently available information relevant to problem formulation/prioritization, exposure, and hazard/effects of PFAS in the context of regulatory and ecological risk assessment activities from around the world. We then describe critical gaps and uncertainties relative to ecological risk assessments for PFAS and propose approaches to address these needs. Recommendations include the development of more comprehensive monitoring programs to support exposure assessment, an emphasis on research to support the formulation of predictive models for bioaccumulation, and the development of in silico, in vitro, and in vivo methods to efficiently assess biological effects for potentially sensitive species/endpoints. Addressing needs associated with assessing the ecological risk of PFAS will require cross‐disciplinary approaches that employ both conventional and new methods in an integrated, resource‐effective manner.

Environmental Toxicology and Chemistry↗

USGS2016

Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling

Climate extremes, such as drought, may have immediate and potentially prolonged effects on carbon cycling. Grasslands store approximately one-third of all terrestrial carbon and may become carbon sources during droughts. However, the magnitude and duration of drought-induced disruptions to the carbon cycle, as well as the mechanisms responsible, remain poorly understood. Over the next century, global climate models predict an increase in two types of drought: chronic but subtle ‘press-droughts’, and shorter term but extreme ‘pulse-droughts’. Much of our current understanding of the ecological impacts of drought comes from experimental rainfall manipulations. These studies have been highly valuable, but are often short term and rarely quantify carbon feedbacks. To address this knowledge gap, we used the Community Land Model 4.0 to examine the individual and interactive effects of pulse- and press-droughts on carbon cycling in a mesic grassland of the US Great Plains. A series of modeling experiments were imposed by varying drought magnitude (precipitation amount) and interannual pattern (press- vs. pulse-droughts) to examine the effects on carbon storage and cycling at annual to century timescales. We present three main findings. First, a single-year pulse-drought had immediate and prolonged effects on carbon storage due to differential sensitivities of ecosystem respiration and gross primary production. Second, short-term pulse-droughts caused greater carbon loss than chronic press-droughts when total precipitation reductions over a 20-year period were equivalent. Third, combining pulse- and press-droughts had intermediate effects on carbon loss compared to the independent drought types, except at high drought levels. Overall, these results suggest that interannual drought pattern may be as important for carbon dynamics as drought magnitude and that extreme droughts may have long-lasting carbon feedbacks in grassland ecosystems.

Global Change Biology↗

USGS2020

A novel quantitative framework for riverscape genetics

Riverscape genetics, which applies concepts in landscape genetics to riverine ecosystems, lack appropriate quantitative methods that address the spatial autocorrelation structure of linear stream networks and account for bidirectional geneflow. To address these challenges, we present a general framework for the design and analysis of riverscape genetic studies. Our framework starts with the estimation of pairwise genetic distance at sample sites and the development of a spatially structured ecological network (SSEN) on which riverscape covariates are measured. We then introduce the novel bidirectional geneflow in riverscapes (BGR) model that uses principles of isolation-by-resistance to quantify the effects of environmental covariates on genetic connectivity, with spatial covariance defined using simultaneous autoregressive models on the SSEN and the generalized Wishart distribution to model pairwise distance matrices arising through a random walk model of geneflow. We highlight the utility of this framework in an analysis of riverscape genetics for brook trout ( Salvelinus fontinalis ) in north central Pennsylvania, USA. Using the fixation index ( F ST ) as the measure of genetic distance, we estimated the effects of 12 riverscape covariates on geneflow by evaluating the relative support of eight competing BGR models. We then compared the performance of the top-ranked BGR model to results obtained from comparable analyses using multiple regression on distance matrices (MRM) and the program STRUCTURE. We found that the BGR model had more power to detect covariate effects, particularly for variables that were only partial barriers to geneflow and/or uncommon in the riverscape, making it more informative for assessing patterns of population connectivity and identifying threats to species conservation. This case study highlights the utility of our modeling framework over other quantitative methods in riverscape genetics, particularly the ability to rigorously test hypotheses about factors that influence geneflow and probabilistically estimate the effect of riverscape covariates, including stream flow direction. This framework is flexible across taxa and riverine networks, is easily executable, and provides intuitive results that can be used to investigate the likely outcomes of current and future management scenarios.

Ecological Applications↗

USGS2017

Are nest boxes ecological traps for red-footed falcons Falco vespertinius at Naurzum

Nest box programs are frequently implemented for conservation of cavity-nesting birds, but their effectiveness is rarely evaluated in comparison to birds not using nest boxes. In the European Palearctic, Red-Footed Falcon ( Falco vespertinus ) populations are both of high conservation concern and are strongly associated with nest box programs in heavily managed landscapes. We used a 21-year monitoring dataset developed from monitoring 753 nesting attempts by Red-footed Falcons at the Naurzum Zapovednick to evaluate response of demographic parameters of Redfooted Falcons to environmental factors including use of nest boxes. Variations in lay date and in numbers of eggs were not well explained by any one model, but instead by combinations of models with terms for nest type, land cover type and degree of coloniality. In contrast, variation in both offspring loss and numbers of fledglings produced were fairly well explained by a single model including terms for nest type, land cover type, and an interaction between the two parameters (65% and 81% model weights respectively). Because, for other species, early lay dates are associated with individual fitness, this interaction highlighted a potential ecological trap where falcons using nest boxes on forest edges at Naurzum lay eggs earlier but suffer greater offspring loss and produce lower numbers of fledglings than do those in other nesting settings.

Kostanay Oblast↗

USGS2015

Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders

Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29) . Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions and objectives prior to sampling data and fitting models.

PLoS ONE↗

USGS2015

On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene

Patterns, mechanisms, projections, and consequences of tree mortality and associated broad-scale forest die-off due to drought accompanied by warmer temperatures—“hotter drought”, an emerging characteristic of the Anthropocene—are the focus of rapidly expanding literature. Despite recent observational, experimental, and modeling studies suggesting increased vulnerability of trees to hotter drought and associated pests and pathogens, substantial debate remains among research, management and policy-making communities regarding future tree mortality risks. We summarize key mortality-relevant findings, differentiating between those implying lesser versus greater levels of vulnerability. Evidence suggesting lesser vulnerability includes forest benefits of elevated [CO 2 ] and increased water-use efficiency; observed and modeled increases in forest growth and canopy greening; widespread increases in woody-plant biomass, density, and extent; compensatory physiological, morphological, and genetic mechanisms; dampening ecological feedbacks; and potential mitigation by forest management. In contrast, recent studies document more rapid mortality under hotter drought due to negative tree physiological responses and accelerated biotic attacks. Additional evidence suggesting greater vulnerability includes rising background mortality rates; projected increases in drought frequency, intensity, and duration; limitations of vegetation models such as inadequately represented mortality processes; warming feedbacks from die-off; and wildfire synergies. Grouping these findings we identify ten contrasting perspectives that shape the vulnerability debate but have not been discussed collectively. We also present a set of global vulnerability drivers that are known with high confidence: (1) droughts eventually occur everywhere; (2) warming produces hotter droughts; (3) atmospheric moisture demand increases nonlinearly with temperature during drought; (4) mortality can occur faster in hotter drought, consistent with fundamental physiology; (5) shorter droughts occur more frequently than longer droughts and can become lethal under warming, increasing the frequency of lethal drought nonlinearly; and (6) mortality happens rapidly relative to growth intervals needed for forest recovery. These high-confidence drivers, in concert with research supporting greater vulnerability perspectives, support an overall viewpoint of greater forest vulnerability globally. We surmise that mortality vulnerability is being discounted in part due to difficulties in predicting threshold responses to extreme climate events. Given the profound ecological and societal implications of underestimating global vulnerability to hotter drought, we highlight urgent challenges for research, management, and policy-making communities.

Ecosphere↗

USGS2022

Natural and anthropogenic landscape factors shape functional connectivity of an ecological specialist in urban Southern California

Identifying how natural (i.e., unaltered by human activity) and anthropogenic landscape variables influence contemporary functional connectivity in terrestrial organisms can elucidate the genetic consequences of environmental change. We examine population genetic structure and functional connectivity among populations of a declining species, the Blainville's horned lizard ( Phrynosoma blainvillii ), in the urbanized landscape of the Greater Los Angeles Area in Southern California, USA. Using single nucleotide polymorphism data, we assessed genetic structure among populations occurring at the interface of two abutting evolutionary lineages, and at a fine scale among habitat fragments within the heavily urbanized area. Based on the ecology of P. blainvillii , we predicted which environmental variables influence population structure and gene flow and used gravity models to distinguish among hypotheses to best explain population connectivity. Our results show evidence of admixture between two evolutionary lineages and strong population genetic structure across small habitat fragments. We also show that topography, microclimate, and soil and vegetation types are important predictors of functional connectivity, and that anthropogenic disturbance, including recent fire history and urban development, are key factors impacting contemporary population dynamics. Examining how natural and anthropogenic sources of landscape variation affect contemporary population genetics is critical to understanding how to best manage sensitive species in a rapidly changing landscape.

California↗