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USGS2017

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. Currently, consistent, continent-wide routine cropland mapping of Africa does not exist, with most studies focused either on certain portions of the continent or at most a one-time effort at mapping the continent at coarse resolution remote sensing. In this research, we addressed these limitations by applying an automated cropland mapping algorithm (ACMA) that captures extensive knowledge on the croplands of Africa available through: (a) ground-based training samples, (b) very high (sub-meter to five-meter) resolution imagery (VHRI), and (c) local knowledge captured during field visits and/or sourced from country reports and literature. The study used 16-day time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) composited data at 250-m resolution for the entire African continent. Based on these data, the study first produced accurate reference cropland layers or RCLs (cropland extent/areas, irrigation versus rainfed, cropping intensities, crop dominance, and croplands versus cropland fallows) for the year 2014 that provided an overall accuracy of around 90% for crop extent in different agro-ecological zones (AEZs). The RCLs for the year 2014 (RCL2014) were then used in the development of the ACMA algorithm to create ACMA-derived cropland layers for 2014 (ACL2014). ACL2014 when compared pixel-by-pixel with the RCL2014 had an overall similarity greater than 95%. Based on the ACL2014, the African continent had 296 Mha of net cropland areas (260 Mha cultivated plus 36 Mha fallows) and 330 Mha of gross cropland areas. Of the 260 Mha of net cropland areas cultivated during 2014, 90.6% (236 Mha) was rainfed and just 9.4% (24 Mha) was irrigated. Africa has about 15% of the world’s population, but only about 6% of world’s irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2025

Reproductive biology of invasive grass carp (Ctenopharyngodon idella) in two North American systems

Grass carp ( Ctenopharyngodon idella ) are nonnative, herbivorous freshwater fish that represent an ecological threat in North American waters. However, data are limited on reproductive biology specific to wild populations in midwestern North America, despite recent concern for grass carp establishment within the Great Lakes. Basic information on reproductive traits could be useful to determine reproductive potential, inform future population modelling and provide information to aid control efforts. Our objectives were to evaluate grass carp age-at-maturity, spawning season timing, fecundity type, developmental timing and spawning strategy. Additionally, we evaluated the reliability of the gonadosomatic index (GSI) as a proxy for identifying mature grass carp and compared body condition across study areas. We sampled grass carp in portions of the Mississippi River watershed within the state of Missouri and within the Lake Erie basin. Based on gonad histological samples ( n = 274), grass carp are batch spawners with indeterminate fecundity and asynchronous ovarian developmental timing. This allows flexibility in their spawning, exemplified by a protracted spawning season in Lake Erie (April to November) in temperatures ranging from 12.3 to 27.3°C. Minimum observed age-at-maturity for females in Missouri and for both males and females in the Lake Erie population was age-3 and age-2 for males in Missouri. Accuracy of GSI as a measure of maturity during the spawning season was 89.7% and 87.5%, for females and males, respectively. Compared to Missouri, grass carp in Lake Erie had a significantly higher body condition, and females ready to spawn had significantly higher GSI values, suggesting that the grass carp in Lake Erie are healthier and more fecund relative to Missouri and, if left uncontrolled, potentially have a high probability of establishment within the Great Lakes. The results of this study will allow managers to identify the reproductive status of grass carp in the field and more accurately estimate populations and reproductive potential.

Michigan, Missouri, Ohio↗

USGS2021

How many Ciscoes are needed for stocking in the Laurentian Great Lakes?

Historically, Cisco Coregonus artedi and deepwater ciscoes Coregonus spp. were the most abundant and ecologically important fish species in the Laurentian Great Lakes, but anthropogenic influences caused nearly all populations to collapse by the 1970s. Fishery managers have begun exploring the feasibility of restoring populations throughout the basin, but questions regarding hatchery propagation and stocking remain. We used historical and contemporary stock-recruit parameters previously estimated for Ciscoes in Wisconsin waters of Lake Superior, with estimates of age-1 Cisco rearing habitat (broadly defined as total ha ≤ 80 m depth) and natural mortality, to estimate how many fry (5.5 months post-hatch), fall fingerling (7.5 months post-hatch), and age-1 (at least 12 months post-hatch) hatchery-reared Ciscoes are needed for stocking in the Great Lakes to mimic recruitment rates in Lake Superior, a lake that has undergone some recovery. Estimated stocking densities suggested that basin-wide stocking would require at least 0.641-billion fry, 0.469-billion fall fingerlings, or 0.343-billion age-1 fish for a simultaneous restoration effort targeting historically important Cisco spawning and rearing areas in Lakes Huron, Michigan, Erie, Ontario, and Saint Clair. Numbers required for basin-wide stocking were considerably greater than current or planned coregonine production capacity, thus simultaneous stocking in the Great Lakes is likely not feasible. Provided current habitat conditions do not preclude Cisco restoration, managers could maximize the effectiveness of available production capacity by concentrating stocking efforts in historically important spawning and rearing areas, similar to the current stocking effort in Saginaw Bay, Lake Huron. Other historically important Cisco spawning and rearing areas within each lake (listed in no particular order) include: (1) Thunder Bay in Lake Huron, (2) Green Bay in Lake Michigan, (3) the islands near Sandusky, Ohio, in western Lake Erie, and (4) the area near Hamilton, Ontario, and Bay of Quinte in Lake Ontario. Our study focused entirely on Ciscoes but may provide a framework for describing future stocking needs for deepwater ciscoes.

Great Lakes↗

USGS2010

Effects of earlier sea ice breakup on survival and population size of polar bears in western Hudson Bay

Some of the most pronounced ecological responses to climatic warming are expected to occur in polar marine regions, where temperature increases have been the greatest and sea ice provides a sensitive mechanism by which climatic conditions affect sympagic (i.e., with ice) species. Population-level effects of climatic change, however, remain difficult to quantify. We used a flexible extension of Cormack-Jolly-Seber capture-recapture models to estimate population size and survival for polar bears (Ursus maritimus), one of the most ice-dependent of Arctic marine mammals. We analyzed data for polar bears captured from 1984 to 2004 along the western coast of Hudson Bay and in the community of Churchill, Manitoba, Canada. The Western Hudson Bay polar bear population declined from 1,194 (95% CI = 1,020-1,368) in 1987 to 935 (95% CI = 794-1,076) in 2004. Total apparent survival of prime-adult polar bears (5-19 yr) was stable for females (0.93; 95% CI = 0.91-0.94) and males (0.90; 95% CI = 0.88-0.91). Survival of juvenile, subadult, and senescent-adult polar bears was correlated with spring sea ice breakup date, which was variable among years and occurred approximately 3 weeks earlier in 2004 than in 1984. We propose that this correlation provides evidence for a causal association between earlier sea ice breakup (due to climatic warming) and decreased polar bear survival. It may also explain why Churchill, like other communities along the western coast of Hudson Bay, has experienced an increase in human-polar bear interactions in recent years. Earlier sea ice breakup may have resulted in a larger number of nutritionally stressed polar bears, which are encroaching on human habitations in search of supplemental food. Because western Hudson Bay is near the southern limit of the species' range, our findings may foreshadow the demographic responses and management challenges that more northerly polar bear populations will experience if climatic warming in the Arctic continues as projected.

Journal of Wildlife Management↗

USGS2004

Importance of storm events in controlling ecosystem structure and function in a Florida Gulf Coast estuary

From 8/95 to 2/01, we investigated the ecological effects of intra- and inter-annual variability in freshwater flow through Taylor Creek in southeastern Everglades National Park. Continuous monitoring and intensive sampling studies overlapped with an array of pulsed weather events that impacted physical, chemical, and biological attributes of this region. We quantified the effects of three events representing a range of characteristics (duration, amount of precipitation, storm intensity, wind direction) on the hydraulic connectivity, nutrient and sediment dynamics, and vegetation structure of the SE Everglades estuarine ecotone. These events included a strong winter storm in November 1996, Tropical Storm Harvey in September 1999, and Hurricane Irene in October 1999. Continuous hydrologic and daily water sample data were used to examine the effects of these events on the physical forcing and quality of water in Taylor Creek. A high resolution, flow-through sampling and mapping approach was used to characterize water quality in the adjacent bay. To understand the effects of these events on vegetation communities, we measured mangrove litter production and estimated seagrass cover in the bay at monthly intervals. We also quantified sediment deposition associated with Hurricane Irene's flood surge along the Buttonwood Ridge. These three events resulted in dramatic changes in surface water movement and chemistry in Taylor Creek and adjacent regions of Florida Bay as well as increased mangrove litterfall and flood surge scouring of seagrass beds. Up to 5 cm of bay-derived mud was deposited along the ridge adjacent to the creek in this single pulsed event. These short-term events can account for a substantial proportion of the annual flux of freshwater and materials between the mangrove zone and Florida Bay. Our findings shed light on the capacity of these storm events, especially when in succession, to have far reaching and long lasting effects on coastal ecosystems such as the estuarine ecotone of the SE Everglades.

Journal of Coastal Research↗

USGS2025

Revised length categories and standard weight equation for Northern Pikeminnow

Objective Length and weight indices (e.g., proportional size distribution, relative weight) provide standardized benchmarks that are useful for comparing groups of fish, identifying ecological interactions, and evaluating the effect of management actions. However, the current length categories and standard weight ( W s ) equation for Northern Pikeminnow Ptychocheilus oregonensis , a species of important management focus in the Pacific Northwest, were developed using limited data, unclear methods, and no validation. As such, we sought to revise the length categories and W s equation for Northern Pikeminnow. Methods We used the all-tackle world record to develop length categories for Northern Pikeminnow. We compiled data from 100,663 Northern Pikeminnow from 114 populations in Idaho, Montana, Oregon, Washington, and British Columbia to develop a revised W s equation. Most fish were measured in fork length (FL), so we converted total lengths (TLs) to FLs using the equation TL = −2.301 + 0.916(FL); r 2 = 0.998. We used the regression line percentile, linear empirical percentile (EmP), and quadratic EmP methods to develop 50th percentile and 75th percentile W s equations. We then assessed length-related biases in our W s equations and the previously published equation. Results We propose minimum FLs of 17 cm (7 inches; stock), 26 cm (10 inches; quality), 35 cm (14 inches; preferred), 41 cm (16 inches; memorable), and 51 cm (20 inches; trophy) for proportional size distribution calculations. The previously published W s equation exhibited substantial length-related biases according to the Willis and weighted empirical quartile method tests. The EmP 50th-percentile W s equation was the only equation that we evaluated that did not exhibit length-related bias. The EmP 50th-percentile W s equation was the best performing equation (i.e., no length-related bias detected). The equation is log 10 ( W s ) = −5.258 + 3.135(FL), where W s is in grams and FL is in millimeters. The equation is valid for Northern Pikeminnow 90–580 mm FL. Conclusion The length categories, length conversion, and W s equation presented here will aid fisheries professionals in the study and management of Northern Pikeminnow populations.

British Columbia, Idaho, Montana, Oregon Washingto↗

USGS2016

Pika ( Ochotona princeps ) losses from two isolated regions reflect temperature and water balance, but reflect habitat area in a mainland region

Although biotic responses to contemporary climate change are spatially pervasive and often reflect synergies between climate and other ecological disturbances, the relative importance of climatic factors versus habitat extent for species persistence remains poorly understood. To address this shortcoming, we performed surveys for American pikas ( Ochotona princeps ) at > 910 locations in 3 geographic regions of western North America during 2014 and 2015, complementing earlier modern (1994–2013) and historical (1898–1990) surveys. We sought to compare extirpation rates and the relative importance of climatic factors versus habitat area for pikas in a mainland-versus-islands framework. In each region, we found widespread evidence of distributional loss—local extirpations, upslope retractions, and encounter of only old sign. Locally comprehensive surveys suggest extirpation of O. princeps from 5 of 9 new sites from the hydrographic Great Basin and from 11 of 29 sites in northeastern California. Although American pikas were recorded as recently as 2011 in Zion National Park and in 2012 from Cedar Breaks National Monument in Utah, O. princeps now appears extirpated from all reported localities in both park units. Multiple logistic regressions for each region suggested that both temperature-related and water-balance-related variables estimated from DAYMET strongly explained pika persistence at sites in the Great Basin and in Utah but not in the Sierra-Cascade “mainland” portion of northeastern California. Conversely, talus-habitat area did not predict American pika persistence in the Great Basin or Utah but strongly predicted persistence in the Sierra-Cascade mainland. These results not only add new areas to our understanding of long-term trend of the American pika’s distribution, but also can inform decisions regarding allocation of conservation effort and management actions. Burgeoning research on species such as O. princeps has collectively demonstrated the heterogeneity and nuance with which climate can act on the distribution of mountain-dwelling mammals.

Journal of Mammalogy↗

USGS2022

Space use and site fidelity of wintering whooping cranes on the Texas Gulf Coast

The Aransas-Wood Buffalo population (the only non-reintroduced, migratory population) of endangered whooping cranes ( Grus americana ) overwinters along the Texas Gulf Coast, USA. Understanding whooping crane space use on the wintering grounds reveals essential aspects of this species' ecology, which subsequently assists with conservation. Using global positioning system telemetry data from marked whooping cranes during 2009–2017, we fit continuous-time stochastic process models to describe movement and home range using autocorrelated kernel density estimation (AKDE) and explored variation in home range size in relation to age, sex, reproductive status, and drought conditions. We used the Bhattacharyya coefficient of overlap and distance between home range centroids to quantify site fidelity. We examined the effects of time between winter home ranges and the sex of the crane on site fidelity using Bayesian mixed-effects beta regression. Winter whooping crane 95% AKDE home range size averaged 30.1 ± 45.2 (SD) km 2 (median = 14.3, range = 1.1–308.6). Home ranges of sub-adult females were approximately 2 times larger than those of sub-adult males or families. As drought worsened, home ranges typically expanded. Between consecutive years, the home ranges of an adult crane exhibited 68 ± 31% overlap (site fidelity), but fidelity to winter sites declined in subsequent winters. The overlap of adult home ranges with the nearest unrelated family averaged 33 ± 28%. As a whooping crane aged, overlap with its winter home range as a juvenile declined, regardless of sex. By 4 years of age, a whooping crane had approximately 14 ± 28% overlap with its juvenile winter home range. Limited evidence suggested male whooping cranes return to within 2 km of their juvenile home range by their fifth winter. Previous data obtained from aerial surveys led ecologists to assume that whooping crane families normally used small areas (~2 km 2 ) and expressed persistent site fidelity. Our analyses showed <8% of families had home ranges ≤2 km 2 , with the average area 15 times greater, and waning site fidelity over time. Our work represents an analysis of whooping crane home ranges for this population, identifying past misconceptions of winter space use and resulting in better estimates of space requirements for future conservation efforts.

Texas↗

USGS2018

Designing a protected area to safeguard imperiled species from urbanization

Reserve design is a process that can address ecological, social, and political factors to identify parcels of land needed to sustain wildlife populations and other natural resources. Acquisition of parcels for a large terrestrial reserve is difficult because it typically occurs over a long timeframe and thus invokes consideration of future conditions such as climate and urbanization changes. In central Florida, a new protected area, the Everglades Headwaters National Wildlife Refuge, has been authorized by the United States Government. The new refuge will host important threatened and endangered species and habitats, as well as be located to allow for species adaptation from climate change impacts. For this study we combined habitat objectives defined by the U.S. Fish and Wildlife Service and projections from two urbanization models to provide guidance for Everglades Headwaters National Wildlife Refuge design. We used Marxan with Zones to find near-optimal solutions for protecting explicit amounts of five target habitats. We identified parcels for inclusion into the reserve design that the model allocated among two zones representing different methods of protection: fee-simple purchase (up to 20,234 hectares authorized by the United States government), and conservation easement agreements (up to 40,469 hectares authorized). As expected, for all scenarios we found an increase in costs as the proportion of fee-simple purchases was increased, reflecting the lesser cost of easements, but the number of parcels required for protection differed little among scenarios. The two urbanization models showed considerable agreement over which habitat patches were not forecast to be developed, and showed some agreement over which parcels might be developed. The U.S. Fish and Wildlife Service may benefit from focusing on parcels that are selected frequently by our analyses under both urban scenarios because these parcels are more likely to be in areas where urbanization threats and demand for land is reduced. The reserve designs we generated met U.S. Fish and Wildlife Service habitat goals within fee and easement zone restrictions, and we found reserve configurations that fell well below the mandated size limit.

Florida↗

USGS2023

Support for management actions to protect night sky quality: Insights from visitors to state and national park units in the U.S.

Light pollution is a global phenomenon where anthropogenic light sources continue to grow unabated, affecting both social and ecological systems. This is leaving parks and protected areas as some of the last vestiges of naturally dark environments for protecting views of the night sky. Yet, even parks and protected areas have outdoor lighting. Alternative lighting practices are needed to reduce or prevent light pollution from within parks. However, making parks darker may not be desirable for some visitors if they believe it will reduce navigability, safety, or restrict how they recreate (e.g., requiring the use of red-light flashlights after dark and before dawn). How visitors will respond to alternative lighting practices that park managers can implement is still unknown. We used an on-site intercept survey at nine state and national park units in Utah, U.S. , to investigate nighttime visitors' support or opposition to management actions to protect night sky quality and their interest in learning about topics related to night skies. Further, this study also segmented visitors into two groups: those ‘dependent’ on the dark sky as a resource and those whose activities did not depend on a dark sky. Defining what a ‘dark sky dependent’ visitor is, which has yet to be done in the literature, is a fundamental step to furthering night sky research and management efforts. Across nine parks and protected areas, 62% of nighttime visitors participated in dark sky dependent activities. Findings indicate broad support for management actions designed to improve night sky quality, with between 74% and 89% of all visitors supporting seven different management actions. There was stronger support from dark sky dependent visitors for some elements of alternative lighting practices, but there was still strong support for those who do not participate in dark sky dependent outdoor recreation. Additionally, between 57% and 75% of visitors were interested in learning more about topics related to night skies. This research indicates most visitors would welcome actions to preserve the quality of the rapidly dwindling naturally dark experiences offered by parks and protected areas.

Utah↗

USGS2022

Accounting for residual heterogeneity in double-observer sightability models decreases bias in burro abundance estimates

Feral burros ( Equus asinus ) and horses ( E. ferus caballus ) inhabiting public land in the western United States are intended to be managed at population levels established to promote a thriving, natural ecological balance. Double-observer sightability (M DS ) models, which use detection records from multiple observers and sighting covariates, perform well for estimating feral horse abundances, but their effectiveness for use in burro populations is less understood. These M DS models help minimize detection bias, yet bias can be further reduced with models that account for unmodeled variation, or residual heterogeneity, in detection probability. In populations containing radio-marked individuals, residual heterogeneity can be estimated with M DS models by including a covariate that corresponds to the marked status of a group (M H models). Another approach is to use information from detections missed by both observers to account for the characteristics that make groups more or less likely to be detected, or recaptured, by the second observer (M R models). We used aerial survey data from 3 burro populations (Sinbad Herd Management Area, UT [2016–2018], Lake Pleasant Herd Management Area, AZ [2017], and Fort Irwin National Training Center, CA [2016–2017]) to develop M DS models applicable for feral burros in the southwestern United States. Our objectives were to quantify precision and bias of standard M DS surveys for feral burros and to examine which model type for incorporating residual heterogeneity (M H or M R ) would result in the least-biased estimates of burro populations relative to the minimum number known alive (MNKA) within the Sinbad Herd Management Area. Standard M DS model estimates achieved a mean coefficient of variation of 0.08, while underestimating MNKA by an average of 27.1%. Accounting for residual heterogeneity through recapture probability in M R models resulted in estimates closer to MNKA than M H models (9.5% vs. 16.5% less than MNKA). Our results indicate that M DS models can achieve precise enough estimates to monitor feral burro populations, but they routinely produce negatively biased estimates. We encourage the use of radio-collars to reduce bias in future burro surveys by accounting for residual heterogeneity through M R models.

Journal of Wildlife Management↗

USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗

USGS2010

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Journal of Applied Statistics↗

USGS2023

Marshbird response to herbicide control of cattail in northwestern Minnesota

Wetlands provide essential habitat for a wide variety of wildlife species. In the once wetland-rich Prairie Pothole Region and adjacent areas of central North America, many wetlands have been converted to agricultural production. Many remaining wetlands experience ecological change via the invasion and spread of non-native plant species, such as non-native narrowleaf ( Typha angustifolia ) and hybrid cattail ( Typha x glauca ), which spread aggressively and displace native vegetation, especially in large, impounded wetlands. Management of wetlands in these landscapes often includes broad-scale herbicide application intended to break up mats of cattail and restore areas to more wildlife-friendly conditions. Although restoration of wildlife habitat is a common goal of such management, marshbird response to invasive cattail control is poorly understood. To evaluate the effects of cattail management on wetland wildlife, we conducted standardized call-broadcast surveys for 5 species of marshbirds at 9 study sites that included survey locations associated with areas treated with herbicide and paired areas not treated with herbicide in wetland impoundments in northwestern Minnesota, USA, using a before-after, control-impact study design. We surveyed American bitterns ( Botaurus lentiginosus ), least bitterns ( Ixobrychus exilis ), pied-billed grebes ( Podilymbus podiceps ), soras ( Porzana carolina ), and Virginia rails ( Rallus limicola ) during the breeding season prior to herbicide application (late summer and early autumn of 2015) and during the 3 breeding seasons after herbicide application (2016–2018). We modeled species counts using a generalized linear mixed model with year-by-treatment interactions as fixed effects and site as a random effect. Before herbicide application, expected mean counts did not differ between treatment and control survey locations. Three years post-treatment, we detected significant increases in expected mean counts at treatment compared to control survey locations for soras ( t 193 = −3.373, P = 0.020) and Virginia rails ( t 193 = −3.167, P = 0.037), and point estimates for all species except least bittern were higher at treatment survey locations. Overall, our results suggest that these marshbird species responded positively to herbicide control of invasive cattail and that breeding marshbirds in these and similar wetland systems may experience positive population response over a period of at least 3 years following treatment.

Minnesota↗

USGS2001

Spatial paradigms of lotic diatom distribution: A landscape ecology perspective

Spatial distributional patterns of benthic diatoms and their relation to current velocity were investigated in an unshaded cobble-bottom reach of White Creek (Washington County, NY). On 27 August 1999, diatoms were sampled and current velocity and depth were measured on a regular square sampling grid with a grain size of 0.01 m2, interval of 0.5 m, and extent of 16 m2. The relative abundance of the 18 common diatom species enumerated in the 81 samples was subjected to detrended correspondence analysis (DCA). The first axis (DCA1) explained 51% of the variance in diatom data and separated the samples according to current regimes. The spatial autocorrelation of DCA1 sample scores in deposition and erosion regions of White Creek was determined by Moran's I statistic to indicate patch size. In White Creek the patch length of all diatom communities was more than 3.1 m, whereas the patch width was 1 m in the deposition region and 0.5 m in the erosion region. There were 5 dominant diatom taxa, Achnanthes minutissima Ku??tz. et vars, Fragilaria capucina Dezmazie??res et vars, F. crotonensis Kitt., Diatoma vulgaris Bory, and Synedra ulna (Nitz.) Ehr. et vars. The patch length of the dominant species varied from 1 to more than 4.1 m, whereas the patch width, if defined, was 0.5 m. Achnanthes minutissima and F. capucina, the two diatom species with the highest relative abundance, displayed spatially structured patches of low abundance and comparatively random patches of high abundance, suggesting broad scale abiotic control of species performance in low abundance regions and finer scale biotic control of high abundance areas. Another objective of this study was to test the hypothesis that higher current velocities, which generally impede immigration, would increase randomness and complexity (i.e. homogeneity of diatom distributional patterns). The spatial complexity in low versus high velocity transects was determined by calculating the respective fractal dimension (D) of DCA1 scores. D of DCA1 was higher in the higher current velocity transects, suggesting that spatial complexity and homogeneity of diatom communities increased in faster currents. Partial canonical correspondence analysis was conducted on diatom, environmental, and spatial data to assess how much of the variance in species distribution could be attributed to environmental (current velocity and depth) versus spatial factors. The variance of species data, explained by the environment (exclusively current velocity), was 38%; whereas space alone contributed only 10%, indicating that 1) current velocity was the major factor that controlled diatom distribution in streams and 2) there were other spatially dependent variables, most likely biotic, but their role in shaping diatom communities was minor.

Journal of Phycology↗

USGS2021

Using fecal DNA and closed-capture models to estimate feral horse population size

Accurate population estimates provide the foundation for managing feral horses ( Equus caballus ferus ) across the western United States. Certain feral horse populations are protected by the Wild and Free-Roaming Horses and Burros Act of 1971 and managed by the Bureau of Land Management (BLM) or the United States Forest Service on designated herd management areas (HMAs) or wild horse territories, respectively. Horses are managed to achieve an appropriate management level (AML), which represents the number of horses determined by BLM to contribute to a thriving natural ecological balance and avoid deterioration of the range. To achieve AML for each HMA, BLM resource managers need accurate and precise population estimates. We tested the use of non-invasive fecal samples in a genetic capture-recapture framework to estimate population size in a closed horse population at the Little Book Cliffs HMA, Colorado, USA, with a known size of 153 individuals. We collected 1,957 samples over 3 independent sampling periods in 2014 and amplified them at 8 microsatellite loci. We applied mark-recapture models to determine population size using 954 samples that amplified at all 8 loci. We subsampled and reanalyzed our dataset to simulate different data collection protocols and evaluated effects on accuracy and precision of estimates using N-mixture modeling, full likelihood closed-capture modeling, and capwire single-occasion modeling that used data from all 3 sampling periods. Our model results were accurate and precise for analyses that used data from all 3 occasions; however, capwire single-occasion modeling was not accurate when we analyzed each sampling period separately. For all subsampling analysis scenarios, reducing sample size decreased precision, whether by reducing number of field staff, field days, or geographic areas surveyed on each period. Reducing spatial coverage of the survey area did not result in accurate population estimates and only marginally lowered the number of samples that would need to be collected to maintain accuracy. Because laboratory analysis contributes the greatest expense for this method ($80 U.S./sample), reducing fecal sample size is advantageous. Our results demonstrate that non-invasive sampling combined with good survey design and careful genetic and capture-recapture analyses can provide an alternative method to estimate the number of feral horses in a closed population. This method may be especially appropriate in situations where aerial inventories are not practical or accurate because of low sighting conditions. But the higher costs associated with laboratory sample analyses may reduce the method's feasibility compared to helicopter surveys.

Colorado↗

USGS2017

Trends in snowmelt-related streamflow timing in the conterminous United States

Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940–2014, 0.9 days/decade) and 3.4 days (1960–2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940–2014, 0.5 days/decade) and 5.2 days (1960–2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February–May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.

Journal of Hydrology↗

USGS2016

Long-term lesser prairie-chicken nest ecology in response to grassland management

Long-term population and range declines from habitat loss and fragmentation caused the lesser prairie-chicken ( Tympanuchus pallidicinctus ) to be a species of concern throughout its range. Current lesser prairie-chicken range in New Mexico and Texas is partially restricted to sand shinnery oak ( Quercus havardii ; hereafter shinnery oak) prairies, on which cattle grazing is the main socioeconomic driver for private landowners. Cattle producers within shinnery oak prairies often focus land management on shrub eradication using the herbicide tebuthiuron to promote grass production for forage; however, herbicide application alone, and in combination with grazing, may affect nest site selection and nest survival of lesser prairie-chickens through the reduction of shinnery oak and native grasses. We used a controlled, paired, completely randomized design study to assess the influence of grazing and tebuthiuron application and their combined use on nest site selection and nest survival from 2001 to 2010 in Roosevelt County, New Mexico, USA at 2 spatial scales (i.e., treatment and microhabitat) in 4 treatments: tebuthiuron with grazing, tebuthiuron without grazing, no tebuthiuron with grazing, and a control of no tebuthiuron and no grazing. Grazing treatment was a short-duration system in which plots were grazed once during the dormant season and once during the growing season. Stocking rate was calculated each season based on measured forage production and applied to remove ≤25% of available herbaceous material per season. At the treatment scale, we compared nest site selection among treatments using 1-way χ 2 tests and nest survival among treatments using a priori candidate nest survival models in Program MARK. At the microhabitat scale, we identified important habitat predictors of nest site selection and nest survival using logistic regression and a priori candidate nest survival models in Program MARK, respectively. Females typically used treatments as expected and we did not detect trends in selection. Nest survival did not differ among treatments. At the microhabitat scale, nest sites had less bare ground ( P  = 0.001) and greater angles of obstruction ( P  ≤ 0.001) compared to random sites. There was a high degree of model selection uncertainty among our candidate models at the microhabitat scale and survival estimates were similar among habitat covariates. Results suggest a tebuthiuron application rate of 0.60 kg/ha, short-duration grazing, and a combination of these management techniques were not detrimental to lesser prairie-chicken nest site selection or nest survival. However, intensified management that increases bare ground or reduces overhead cover may negatively affect lesser prairie-chicken nesting habitat and nest survival.

Journal of Wildlife Management↗