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USGS2023

Estimates of predator densities using mobile DIDSON surveys: Implications for survival of Central Valley Chinook Salmon

The Sacramento–San Joaquin Delta (hereafter, “the Delta”) is one of the estuaries with the most invasive species in the world, and nonnative predators may be a major factor in the observed decline of Central Valley Chinook Salmon Oncorhynchus tshawytscha over recent decades. In order for managers to take actions that might reduce predation-related mortality for these ecologically, culturally, and economically valuable fish, it is important to understand the factors influencing the distribution and abundance of piscivores in the Delta. In this study, we used a dual-frequency identification sonar (i.e., DIDSON) to conduct mobile surveys to quantify the abundances of piscivores in the Delta. We then used these data to identify the habitat features that are correlated with the abundance of piscivores. Prior to conducting the surveys, we used DIDSON data from captured fish to develop an algorithm to distinguish piscivores from nonpiscivores with high confidence (98% accuracy). A generalized linear mixed-effects model fit to these survey data indicated that predator abundances were most associated with areas of increased submerged aquatic vegetation patches, and channels that are straighter, with increased bathymetric complexity. When applied to the entire survey area, this model was successfully able to predict known areas of high predator densities. These results indicate that one approach to reduce predator densities in key locations throughout the Delta, and improve juvenile salmonid outmigration survival, is to reduce the extent of invasive submerged aquatic vegetation. Because experimental predator removals have been largely ineffective in the Delta, efforts to manipulate habitat to discourage nonnative predator recruitment and favor native species recruitment may provide a more effective solution to improve salmonid survival rates.

California↗

USGS2012

Patterns and controlling factors of species diversity in the Arctic Ocean

Aim The Arctic Ocean is one of the last near-pristine regions on Earth, and, although human activities are expected to impact on Arctic ecosystems, we know very little about baseline patterns of Arctic Ocean biodiversity. This paper aims to describe Arctic Ocean-wide patterns of benthic biodiversity and to explore factors related to the large-scale species diversity patterns. Location Arctic Ocean. Methods We used large ostracode and foraminiferal datasets to describe the biodiversity patterns and applied comprehensive ecological modelling to test the degree to which these patterns are potentially governed by environmental factors, such as temperature, productivity, seasonality, ice cover and others. To test environmental control of the observed diversity patterns, subsets of samples for which all environmental parameters were available were analysed with multiple regression and model averaging. Results Well-known negative latitudinal species diversity gradients (LSDGs) were found in metazoan Ostracoda, but the LSDGs were unimodal with an intermediate maximum with respect to latitude in protozoan foraminifera. Depth species diversity gradients were unimodal, with peaks in diversity shallower than those in other oceans. Our modelling results showed that several factors are significant predictors of diversity, but the significant predictors were different among shallow marine ostracodes, deep-sea ostracodes and deep-sea foraminifera. Main conclusions On the basis of these Arctic Ocean-wide comprehensive datasets, we document large-scale diversity patterns with respect to latitude and depth. Our modelling results suggest that the underlying mechanisms causing these species diversity patterns are unexpectedly complex. The environmental parameters of temperature, surface productivity, seasonality of productivity, salinity and ice cover can all play a role in shaping large-scale diversity patterns, but their relative importance may depend on the ecological preferences of taxa and the oceanographic context of regions. These results suggest that a multiplicity of variables appear to be related to community structure in this system.

Journal of Biogeography↗

USGS2009

Sources, sinks, and spatial ecology of cotton mice in longleaf pine stands undergoing restoration

The Fire and Fire Surrogate studya replicated, manipulative experimentsought the most economically and ecologically efficient way to restore the nation's fire-maintained ecosystems. As part of this study, we conducted a 3-year markrecapture study, comprising 105,000 trap-nights, to assess demographic responses of cotton mice (Peromyscus gossypinus) to Fire and Fire Surrogate treatments at the Gulf Coastal Plain site, where longleaf pine was the ecosystem to be restored. We compared competing models to evaluate restoration effects on variation in apparent survival and recruitment over time, space, and treatment, and incorporated measures of available source habitat for cotton mice with reverse-time modeling to infer immigration from outside the study area. The top-ranked survival model contained only variation over time, but the closely ranked 2nd and 3rd models included variation over space and treatment, respectively. The top 4 recruitment models all included effects for availability of source habitat and treatments. Burning appeared to degrade habitat quality for cotton mice, showing demographic characteristics of a sink, but treatments combining fire with thinning of trees or application of herbicide to the understory appeared to improve habitat quality, possibly creating sources. Bottomland hardwoods outside the study also acted as sources by providing immigrants to experimental units. Models suggested that population dynamics operated over multiple spatial scales. Treatments applied to 15-ha stands probably only caused local variation in vital rates within the larger population. ?? 2009 American Society of Mammalogists.

Journal of Mammalogy↗

USGS2017

The efficacy of combined educational and site management actions in reducing off-trail hiking in an urban-proximate protected area

Park and protected area managers are tasked with protecting natural environments, a particularly daunting challenge in heavily visited urban-proximate areas where flora and fauna are already stressed by external threats. In this study, an adaptive management approach was taken to reduce extensive off-trail hiking along a popular trail through an ecologically diverse and significant area in the Chesapeake and Ohio National Historical Park near Washington DC. Substantial amounts of off-trail hiking there had created an extensive 16.1 km network of informal (visitor-created) trails on a 39 ha island in the Potomac Gorge. A research design with additive treatments integrating educational and site management actions was applied and evaluated using self-reported behavior from an on-site visitor survey and unobtrusive observations of off-trail hiking behavior at two locations along the trail. Study treatments included: 1) trailhead educational signs developed using attribution theory and injunctive-proscriptive wording, 2) symbolic “no hiking” prompter signs attached to logs placed across all informal trails, 3) placement of concealing leaf litter and small branches along initial sections of informal trails, 4) restoration work on selected trails with low fencing, and 5) contact with a trail steward to personally communicate the trailhead sign information. The final, most comprehensive treatment reduced visitor-reported intentional off-trail hiking from 70.3% to 43.0%. Direct observations documented reduction in off-trail hiking from 25.9% to 2.0%. The educational message and site management actions both contributed to the decline in off-trail travel and the two evaluation methods enhanced our ability to describe the efficacy of the different treatments in reducing off-trail travel.

Bear Island↗

USGS2022

Selecting the optimal fine-scale historical climate data for assessing current and future hydrological conditions

High-resolution historical climate grids are readily available and frequently used as inputs for a wide range of regional management and risk assessments, including water supply, ecological processes, and as baseline for climate change impact studies that compare them to future projected conditions. Because historical gridded climates are produced using various methods, their portrayal of landscape conditions differ, which becomes a source of uncertainty when they are applied to subsequent analyses. Here we tested the range of values from five gridded climate datasets. We compared their values to observations from 1231 weather stations, first using each dataset’s native scale, and then after each was rescaled to 270-m resolution. We inputted the downscaled grids to a mechanistic hydrology model and assessed the spatial results of six hydrological variables across California, in 10 ecoregions and 11 large watersheds in the Sierra Nevada. PRISM was most accurate for precipitation, ClimateNA for maximum temperature, and TopoWx for minimum temperature. The single most accurate dataset overall was PRISM due to the best performance for precipitation and low air temperature errors. Hydrological differences ranged up to 70% of the average monthly streamflow with an average of 35% disagreement for all months derived from different historical climate maps. Large differences in minimum air temperature data produced differences in modeled actual evapotranspiration, snowpack, and streamflow. Areas with the highest variability in climate data, including the Sierra Nevada and Klamath Mountains ecoregions, also had the largest spread for snow water equivalent, recharge, and runoff.

Journal of Hydrometeorology↗

USGS2025

Detection of deer at remote camera sites in relation to snow conditions

In the rain-snow transition zone of the Pacific Northwest, climate change is expected to alter the incidence of rain-on-snow and freeze-thaw events, which will change snow density and hardness dynamics. In winter, the ability of economically and ecologically important wildlife species, such as deer ( Odocoileus spp.), to efficiently move through the landscape and access forage is mediated by snow conditions. Therefore, snow properties such as density and hardness can directly affect how energetically costly it is for these animals to survive. However, little is known about whether and how ungulates use habitats based on snow density and hardness. We deployed a stratified network of remote camera stations in complex forested terrain in Latah County, Idaho, USA, to remotely measure snow depth and detect deer. We also collected snow density and hardness measurements throughout the winter. We used these data to determine the degree to which the probability of deer presence at cameras could be explained by snow conditions and air temperature. Snow depth and density had negative relationships with the probability of deer presence, while ram resistance (a proxy for snow hardness) had a marginal positive effect. We were able to estimate snow conditions important to deer in winter 2020–2021 primarily using data obtained from cameras. This provides an important proof-of-concept that can be applied at different sites and climate conditions to gain a deeper understanding of how deer are affected by snowpack properties. These methods can be used by managers to determine how ungulates are affected by snow depth, density, and hardness collectively and subsequently inform ungulate management in a changing climate.

Idaho↗

USGS2025

An approach to modeling abundance of marine wildlife over space and time using unstructured aerial surveys

Estimating spatial and temporal patterns in abundance is often a goal of ecological studies and can be useful for informing management decisions, such as determining the optimal placement of wildlife protection zones. However, estimating abundance can be difficult in practice, especially over large areas, because of imperfect detection, where individuals are present but not detected because of either availability or observer error. Several methods for estimating abundance that account for imperfect detection exist but can be logistically challenging to implement. We present a simpler approach to some of the more commonly used techniques for estimating the abundance of marine wildlife over space and time from unstructured aerial surveys. This approach combines a spatial model for count data with auxiliary information on detection probability obtained from small-scale or previous studies. We employ generalized linear models and generalized additive models with spatial habitat covariates to illustrate this approach using maximum-likelihood with free, open-source statistical software. This framework is intended to be accessible and flexible, requiring lower survey costs and less computation time than other alternatives for estimating abundance. Indeed, our simulation results show that this approach can reduce computation times, while appropriately characterizing uncertainty, compared to a Bayesian approach. We also present R code for our approach using an example of estimating Florida manatee ( Trichechus manatus latirostris ) abundance in Indian River County in Florida, USA. This approach could be applied to other study systems and marine wildlife species using unstructured aerial surveys.

Florida↗

USGS2025

Larger larval sea lamprey (Petromyzon marinus) have longer survival times when exposed to the lampricide 3-trifluoromethyl-4-nitrophenol

Invasive sea lamprey ( Petromyzon marinus ) in the Laurentian Great Lakes have negatively impacted ecologically and economically important fishes for nearly a century. To mitigate these effects, the lampricide 3-trifluoromethyl-4-nitrophenol (TFM) is applied annually on a rotating basis to selected Great Lakes tributaries to kill larval lamprey before they become juveniles, out-migrate to the lakes, and parasitize other fishes. It has been hypothesized that larval size (e.g., mass, length) may affect survival time in response to TFM. To test this hypothesis, we conducted an experiment with 8611 larvae across four temporal replicates, in which TFM concentrations equivalent to those used in present-day stream treatments were applied for up to 18 h. When examining the survival times of larval lamprey exposed to TFM, we found a significant, positive relationship between length, mass, toxicity, and their interactions. For every 1 mm increase in total length, a corresponding increase by 1 g of mass reduced survival time by 0.4315 min [95 % CI: 0.5283–0.2992] and vice versa (i.e., the significant interaction between length and mass revealed that as larvae increase in mass, the survival benefit to being longer decreases, and vice versa). The changes in total length and mass of larval sea lamprey stored in ethanol for 4 months was also quantified. The observation that five larvae survived well past the 12-hour time window of a typical TFM field treatment highlights the need for continuous monitoring and the development of new control strategies to ensure the continued effective management of this invasive species.

Michigan↗

USGS2013

Ecological impacts of energy-wood harvests: Lessons from whole-tree harvesting and natural disturbance

Recent interest in using forest residues and small-diameter material for biofuels is generating a renewed focus on harvesting impacts and forest sustainability. The rich legacy of research from whole-tree harvesting studies can be examined in light of this interest. Although this research largely focused on consequences for forest productivity, in particular carbon and nutrient pools, it also has relevance for examining potential consequences for biodiversity and aquatic ecosystems. This review is framed within a context of contrasting ecosystem impacts from whole-tree harvesting because it represents a high level of biomass removal. Although whole-tree harvesting does not fully use the nonmerchantable biomass available, it indicates the likely direction and magnitude of impacts that can occur through energy-wood harvesting compared with less-intensive conventional harvesting and to dynamics associated with various natural disturbances. The intent of this comparison is to gauge the degree of departure of energy-wood harvesting from less intensive conventional harvesting. The review of the literature found a gradient of increasing departure in residual structural conditions that remained in the forest when conventional and whole-tree harvesting was compared with stand-replacing natural disturbance. Important stand- and landscape-level processes were related to these structural conditions. The consequence of this departure may be especially potent because future energy-wood harvests may more completely use a greater range of forest biomass at potentially shortened rotations, creating a great need for research that explores the largely unknown scale of disturbance that may apply to our forest ecosystems.

Journal of Forestry↗

USGS2017

Imputation approaches for animal movement modeling

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals ( Callorhinus ursinus ) in the Bering Sea. Supplementary materials accompanying this paper appear online.

Journal of Agricultural, Biological, and Environme↗

USGS2021

Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model

Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied ( r 2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana ). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple ( Acer rubrum ), and eastern hemlock ( Tsuga canadensis ) where soil moisture was sufficient. On drier sandy soils, eastern white pine ( Pinus strobus ), red pine ( P. resinosa ), northern red oak ( Quercus rubra ), and white oak ( Q. alba ) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.

New York↗

USGS2021

Growth inhibition of the harmful alga Prymnesium parvum by plant-derived products and identification of ellipticine as highly potent allelochemical

Prymnesium parvum is a toxin-producing harmful alga that has caused ecological and economic damage worldwide. Effective methods to control blooms of this species in the field, however, are unavailable. This study examined five natural compounds present in the invasive plant Arundo donax and one synthetic derivative (5,6-dichlorogramine) for their effect on P. parvum growth. All compounds except one inhibited growth in the following order of potency: ellipticine > > 5,6-dichlorogramine > 1 H-indole = 2,4,6-trimethyl-benzonitrile > gramine. Ellipticine was by far the most potent inhibitor, with full algicidal activity at concentrations as low as 0.04 mg L −1 and 3- and 9-day IC 50 values of 0.012 and 0.007 mg L −1 , respectively. A reduction in chlorophyll content and swimming activity and an increase in length and volume (swelling) were documented in algal cells exposed to 0.01–0.02 mg ellipticine L −1 . These results show that ellipticine is among the most potent natural algicides identified to date. The sixth compound tested, oleamide, unexpectedly stimulated algal growth above control levels. Overall, these observations confirm the existence of highly potent anti- P. parvum allelochemicals in giant reed and demonstrate potential for using products derived from this plant in the development of natural, environmentally friendly methods to control harmful algal blooms.

Journal of Applied Phycology↗

USGS2019

A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades

The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remote sensing-based studies. Overall, CWP data from 148 crop growing study sites (60 wheat, 43 corn, and 45 rice) spread across the world were gathered from published articles spanning 31 different countries. There was overwhelming evidence of a significant increase in CWP with an increase in latitude for predominately northern hemisphere datasets. For example, corn grown in latitude 40–50° had much higher mean CWP (2.45 kg/m³) compared to mean CWP of corn grown in other latitudes such as 30–40° (1.67 kg/m³) or 20–30° (0.94 kg/m³). The same trend existed for wheat and rice as well. For soils, none of the CWP values, for any of the three crops, were statistically different. However, mean CWP in higher latitudes for the same soil was significantly higher than the mean CWP for the same soil in lower latitudes. This applied for all three crops studied. For wheat, the global CWP categories were low (≤0.75 kg/m³), medium (>0.75 to <1.10 kg/m³), and high CWP (≥1.10 kg/m³). For corn the global CWP categories were low (≤1.25 kg/m³), medium (>1.25 to ≤1.75 kg/m³), and high (>1.75 kg/m³). For rice the global CWP categories were low (≤0.70 kg/m³), medium (>0.70 to ≤1.25 kg/m³), and high (>1.25 kg/m³). USA and China are the only two countries that have consistently high CWP for wheat, corn, and rice. Australia and India have medium CWP for wheat and rice. India’s corn, however, has low CWP. Egypt, Turkey, Netherlands, Mexico, and Israel have high CWP for wheat. Romania, Argentina, and Hungary have high CWP for corn, and Philippines has high CWP for rice. All other countries have either low or medium CWP for all three crops. Based on data in this study, the highest consumers of water for crop production also have the most potential for water savings. These countries are USA, India, and China for wheat; USA, China, and Brazil for corn; India, China, and Pakistan for rice. For example, even just a 10% increase in CWP of wheat grown in India can save 6974 billion liters of water. This is equivalent to creating 6974 lakes each of 100 m³ in volume that leads to many benefits such as acting as ‘water banks’ for lean season, recreation, and numerous ecological services. This study establishes the volume of water that can be saved for each crop in each country when there is an increase in CWP by 10%, 20%, and 30%.

International Journal of Digital Earth↗

USGS2017

Age and growth comparisons of Hovsgol grayling ( Thymallus nigrescens Dorogostaisky, 1923), Baikal grayling ( T. baicalensis Dybowski, 1874), and lenok ( Brachymystax lenok Pallas, 1773) in lentic and lotic habitats of Northern Mongolia

Despite concern over the conservation status of many Mongolian salmonids and the importance of their ecological role in Mongolia's aquatic ecosystems, little is known about their basic biology. Hovsgol grayling ( Thymallus nigrescens ) is endemic to Lake Hovsgol, Mongolia and listed as endangered on the Mongolian Red List. Baikal grayling ( T. baicalensis ) and lenok ( Brachymystax lenok ) are found in lakes and rivers throughout the Selenge drainage. A detailed study of the age and growth of these three salmonids was conducted based on 1,682 samples collected from July 2006 to July 2013 in Lake Hovsgol, its outlet the Eg River, and one of the Eg's largest tributaries, the Uur River. Our results suggest that Hovsgol grayling in particular can reach a much older maximum age (17 years in our samples) than previously believed based on aging from scales. Female Hovsgol grayling were heavier at a given length than their male counterparts. Lenok had a greater average length-at-age in Lake Hovsgol compared to the rivers and greater weight-at-length in the warmer Uur River than in the Eg; female lenok from the rivers had a greater average length-at-age than their male counterparts. This study provides critical new information for the management and conservation of these threatened salmonid species in Mongolia.

Journal of Applied Ichthyology↗

USGS2024

Linking temperature sensitivity of mangrove communities, populations and individuals across a tropical-temperate transitional zone

Climate change is reshaping coastal wetlands worldwide, driving ecosystem shifts like mangrove poleward expansion into saltmarshes in tropical-temperate transitional zones. Though warming is recognized as the primary driver, a lack of detailed field studies limits our ability to predict mangrove responses to rapid climate warming. Here, we characterized how mangroves vary across a temperature gradient at 18 sites along Florida's Gulf of Mexico coast (USA). We used minimum air temperature ( T min ) derived from daily data from 1989 to 2021 as the independent variable and applied plot-based and synoptic approaches to quantify species-specific mangrove variation at community, population, and individual levels. We then used these results to spatially project future mangrove ecosystem properties under multiple warming scenarios. Across the T min gradient from −10.8 to −1.4°C, mangrove canopy height and coverage ranged from 0.4 to 11.5 m and 15% to 98%, respectively, with both exhibiting sigmoidal increases with T min . Estimated mangrove aboveground biomass ranged from 0 to 496.7 Mg/ha and showed a positive linear relationship with T min due both to the tall tree stratum's increased biomass per tree and higher abundance. While the population abundance and coverage of Rhizophora mangle and Laguncularia racemosa had positive linear relationships with T min , Avicennia germinans exhibited a significant quadratic relationship, reflecting the higher freeze tolerance of this species. Such tolerance may stem from A. germinans ' higher morphological plasticity observed at the individual level, adapting to cold stress by exhibiting a more shrub-like architecture at colder sites. Based on these field-derived quantitative relationships, we projected substantial increases in mangrove coverage and canopy height near current range limits, with tall A. germinans dominating in the north and R. mangle dominating the centre and south of the study region. Synthesis. To better predict the ecological consequences in coastal wetlands under future climate change, it is essential to understand how mangroves respond to winter temperature regimes across a temperature gradient. Collectively, these cross-level and species-specific results advance our understanding of mangrove temperature sensitivity and provide information about the future of coastal wetland structure and function in response to a changing climate.

Florida↗

USGS2012

Feedbacks between inundation, root production, and shoot growth in a rapidly submerging brackish marsh

1. Ecogeomorphic feedbacks between mineral sediment deposition and above-ground plant growth are thought to have dominated the evolution of many coastal ecosystems and landforms. However, land-use-related reductions in sediment delivery rates to estuaries world-wide suggest that these above-ground feedbacks may not apply in some of the world's most vulnerable coastal landscapes. 2. To understand the relationships between sea level rise and marsh survival, we measured root and shoot growth over experimentally manipulated elevations in a rapidly submerging, sediment deficient marsh. 3. Root growth was highest at a distinct optimum elevation in both Schoenoplectus americanus and Spartina patens . S. americanus shoot growth was highest at an optimum elevation, but S. patens shoot growth increased with elevation throughout the intertidal zone. 4. For marsh elevations that are higher than optimum (expected at low sea level rise rates), we propose that an acceleration in the rate of sea level rise will lead to enhanced root growth, organic accretion and wetland stability. For suboptimum marsh elevations (expected at rapid sea level rise rates and/or low sediment supply), increases in the water level will lead to reduced root growth and a decrease in the rate of elevation gain. 5. More than 80% of the marshland in our study area has an elevation below the optimum for root growth, suggesting that this previously unknown feedback could explain observations of rapid marsh deterioration in the region. 6. Synthesis . Below-ground responses of marshes to sea level rise are more broadly applicable than above-ground feedbacks because they are consistent among different species and do not depend on the availability of mineral sediment.

Journal of Ecology↗

USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗

USGS2019

Factors influencing nesting ecology of lesser prairie-chickens

Lesser prairie-chicken ( Tympanuchus pallidicinctus ) populations have declined since the 1980s. Understanding factors influencing nest-site selection and nest survival are important for conservation and management of lesser prairie-chicken populations. However, >75% of the extant population is in the northern extent of the range where data on breeding season ecology are lacking. We tested factors influencing fine-scale and regional nest-site selection and nest survival across the northern portion of the lesser prairie-chicken range. We trapped and affixed satellite global positioning system and very high frequency transmitters to female lesser prairie-chickens ( n = 307) in south-central and western Kansas and eastern Colorado, USA. We located and monitored 257 lesser prairie-chicken nests from 2013 to 2016. We evaluated nest-site selection and nest survival in comparison to vegetation composition and structure. Overall, nest-site selection in relation to vegetation characteristics was similar across our study area. Lesser prairie-chickens selected nest microsites with 75% visual obstruction 2.0–3.5 dm tall and 95.7% of all nests were in habitat with ≥1 dm and ≤4 dm visual obstruction. Nests were located in areas with 6–8% bare ground, on average, avoiding areas with greater percent cover of bare ground. The type of vegetation present was less important than cover of adequate height. Nest survival was maximized when 75% visual obstruction was 2.0–4.0 dm. Nest survival did not vary spatially or among years and generally increased as intensity of drought decreased throughout the study although not significantly. To provide nesting cover considering yearly variation in drought conditions, it is important to maintain residual cover by managing for structural heterogeneity of vegetation. Managing for structural heterogeneity could be accomplished by maintaining or strategically applying practices of the Conservation Reserve Program, using appropriate fire and grazing disturbances in native working grasslands, and establishing site-specific monitoring of vegetation composition and structure.

Colorado, Kansas↗