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USGS2017

Role of a naturally varying flow regime in Everglades restoration

The Everglades is a low-gradient floodplain predominantly on organic soil that undergoes seasonally pulsing sheetflow through a network of deepwater sloughs separated by slightly higher elevation ridges. The seasonally pulsing flow permitted the coexistence of ridge and slough vegetation, including the persistence of productive, well-connected sloughs that seasonally concentrated prey and supported wading bird nesting success. Here we review factors contributing to the origin and to degradation of the ridge and slough ecosystem in an attempt to answer “How much flow is needed to restore functionality”? A key restoration objective is to increase sheetflow lost during the past century to reestablish interactions between flow, water depth, vegetation production and decomposition, and transport of flocculent organic sediment that build and maintain ridge and slough distinctions. Our review finds broad agreement that perturbations of water level depth and its fluctuations were primary in the degradation of landscape functions, with critical contributions from perturbed water quality, and flow velocity and direction. Whereas water levels are expected to be improved on average across a range of restoration scenarios that replace between 79 and 91% of predrainage flows, the diminished microtopography substantially decreases the probability of timely improvements in some areas whereas others that retain microtopographic differences are poised for restoration benefits. New advances in predicting restoration outcomes are coming from biophysical modeling of ridge–slough dynamics, system-wide measurements of landscape functionality, and large-scale flow restoration experiments, including active management techniques to kick-start slough regeneration.

Florida↗

USGS2014

Reproductive ecology of lampreys

Lampreys typically spawn in riffle habitats during the spring. Spawning activity and diel (i.e., during daylight and at night) behavioral patterns are initiated when spring water temperatures increase to levels that coincide with optimal embryologic development. Nests are constructed in gravel substrate using the oral disc to move stones and the tail to fan sediment out of the nest. Spawning habitat used by individual species is generally a function of adult size, where small-bodied species construct nests in shallower water with slower flow and smaller gravel than large-bodied species. The mating system of lampreys is primarily polygynandrous (i.e., where multiple males mate with multiple females). Lamprey species with adult total length less than 30 cm generally spawn communally, where a nest may contain 20 or more individuals of both sexes. Lamprey species with adult sizes greater than 35 cm generally spawn in groups of two to four. Operational sex ratios of lampreys are highly variable across species, populations, and time, but are generally male biased. The act of spawning typically starts with the male attaching with his oral disc to the back of the female’s head; the male and female then entwine and simultaneously release gametes. However, alternative mating behaviors (e.g., release of gametes without paired courtship and sneaker males) have been observed. Future research should determine how multiple modalities of communication among lampreys (including mating pheromones) are integrated to inform species recognition and mate choice. Such research could inform both sea lamprey control strategies and provide insight into possible evolution of reproductive isolation mechanisms between paired lamprey species in sympatry.

Book chapter↗

USGS2007

Human influence on California fire regimes

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

USGS2008

Effects of the herbicide diuron on cordgrass (Spartina foliosa) reflectance and photosynthetic parameters

Early indicators of salt marsh plant stress are needed to detect stress before it is manifested as changes in biomass and coverage. We explored a variety of leaf-level spectral reflectance and fluorescence variables as indicators of stress in response to the herbicide diuron. Diuron, a Photosystem II inhibitor, is heavily used in areas adjacent to estuaries, but its ecological effects are just beginning to be recognized. In a greenhouse experiment, we exposed Spartina foliosa , the native cordgrass in California salt marshes, to two levels of diuron. After plant exposure to diuron for 28 days, all spectral reflectance indices and virtually all fluorescence parameters indicated reduced pigment and photosynthetic function, verified as reduced CO 2 assimilation. Diuron exposure was not evident, however, in plant morphometry, indicating that reflectance and fluorescence were effective indicators of sub-lethal diuron exposure. Several indices (spectral reflectance index ARI and fluorescence parameters EQY, Fo, and maximum rETR) were sensitive to diuron concentration. In field trials, most of the indices as well as biomass, % cover, and canopy height varied predictably and significantly across a pesticide gradient. In the field, ARI and Fo regressed most significantly and strongly with pesticide levels. The responses of ARI and Fo in both the laboratory and the field make these indices promising as sensitive, rapid, non-destructive indicators of responses of S. foliosa to herbicides in the field. These techniques are employed in remote sensing and could potentially provide a link between landscapes of stressed vegetation and the causative stressor(s), which is crucial for effective regulation of pollution.

Estuaries and Coasts↗

USGS2012

Developing a broader scientific foundation for river restoration: Columbia River food webs

Well-functioning food webs are fundamental for sustaining rivers as ecosystems and maintaining associated aquatic and terrestrial communities. The current emphasis on restoring habitat structure—without explicitly considering food webs—has been less successful than hoped in terms of enhancing the status of targeted species and often overlooks important constraints on ecologically effective restoration. We identify three priority food web-related issues that potentially impede successful river restoration: uncertainty about habitat carrying capacity, proliferation of chemicals and contaminants, and emergence of hybrid food webs containing a mixture of native and invasive species. Additionally, there is the need to place these food web considerations in a broad temporal and spatial framework by understanding the consequences of altered nutrient, organic matter (energy), water, and thermal sources and flows, reconnecting critical habitats and their food webs, and restoring for changing environments. As an illustration, we discuss how the Columbia River Basin, site of one of the largest aquatic/riparian restoration programs in the United States, would benefit from implementing a food web perspective. A food web perspective for the Columbia River would complement ongoing approaches and enhance the ability to meet the vision and legal obligations of the US Endangered Species Act, the Northwest Power Act (Fish and Wildlife Program), and federal treaties with Northwest Indian Tribes while meeting fundamental needs for improved river management.

Proceedings of the National Academy of Sciences of↗

USGS2015

A quantitative framework for estimating risk of collision between marine mammals and boats

Speed regulations of watercraft in protected areas are designed to reduce lethal collisions with wildlife but can have economic consequences. We present a quantitative framework for investigating the risk of deadly collisions between boats and wildlife. We apply encounter rate theory to demonstrate how marine mammal-boat encounter rate can be used to predict the expected number of deaths associated with management scenarios. We illustrate our approach with management scenarios for two endangered species: the Florida manatee Trichechus manatus latirostris and the North Atlantic right whale Eubalaena glacialis . We used a Monte Carlo simulation approach to demonstrate the uncertainty that is associated with our estimate of relative mortality. We show that encounter rate increased with vessel speed but that the expected number of encounters varies depending on the boating activities considered. For instance, in a scenario involving manatees and boating activities such as water skiing, the expected number of encounters in a given area (in a fixed time interval) increased with vessel speed. In another scenario in which a vessel made a transit of fixed length the expected number of encounters decreases slightly with boat speed. In both cases the expected number of encounters increased with distanced travelled by the boat. For whales, we found a slight reduction (~0.1%) in the number of encounters under a scenario where speed is unregulated; this reduction, however, is negligible, and overall expected relative mortality was ~30% lower under the scenario with speed regulation. The probability of avoidance by the animal or vessel was set to 0 because of lack of data, but we explored the importance of this parameter on the model predictions. In fact, expected relative mortality under speed regulations decreases even further when the probability of avoidance is a decreasing function of vessel speed. By applying encounter rate theory to the case of boat collisions with marine mammals, we gained new insights about encounter processes between wildlife and watercraft. Our work emphasizes the importance of considering uncertainty when estimating wildlife mortality. Finally, our findings are relevant to other systems and ecological processes involving the encounter between moving agents.

Methods in Ecology and Evolution↗

USGS2020

After-hatch and hatch year Buff-breasted Sandpipers (Calidris subruficollis) can be sexed accurately using morphometric measures

Determining the sex of birds quickly in the field can help in studies of behavior and distribution, and when selecting particular sexes for deploying tracking devices or collecting samples. However, discerning males from females is difficult in species that are plumage monomorphic and have overlapping sexual-size dimorphism, as in Buff-breasted Sandpipers Calidris subruficollis . We developed three discriminant functions to sex Buff-breasted Sandpipers based on measurements of live birds captured in Brazil whose sex was confirmed with molecular techniques. We validated these discriminant functions using morphometric measures from other independent samples of known-sex live birds from wintering (Brazil), migration (Texas), and breeding (Alaska) sites. Discriminant functions derived from birds captured in Brazil accurately sexed ≥88% of the validation sample from Brazil, Texas, and Alaska. Errors in classification occurred among males on the wintering (0–5%) and breeding (8–12%) grounds, and females during migration (0–11%). Discriminant functions worked well because of the substantial sexual size dimorphism present in the species, with male traits being in general 5.2–10.4% larger than female traits. The size of morphological traits did not vary by age (after controlling for sex) for birds sampled on the wintering grounds and during migration. Our results indicate that discriminant functions can be used to sex after-hatch year (AHY) Buff-breasted Sandpipers throughout their range, and for hatch year (HY) birds during their first southbound migration and winter. Being able to accurately sex both AHY and HY birds using only morphological measurements will improve studies of the ecology and population structure of this species and enhance the application of conservation measures.

Wader Study↗

USGS2013

Predicting thermal reference conditions for USA streams and rivers

Temperature is a primary driver of the structure and function of stream ecosystems. However, the lack of stream temperature (ST) data for the vast majority of streams and rivers severely compromises our ability to describe patterns of thermal variation among streams, test hypotheses regarding the effects of temperature on macroecological patterns, and assess the effects of altered STs on ecological resources. Our goal was to develop empirical models that could: 1) quantify the effects of stream and watershed alteration (SWA) on STs, and 2) accurately and precisely predict natural (i.e., reference condition) STs in conterminous USA streams and rivers. We modeled 3 ecologically important elements of the thermal regime: mean summer, mean winter, and mean annual ST. To build reference-condition models (RCMs), we used daily mean ST data obtained from several thousand US Geological Survey temperature sites distributed across the conterminous USA and iteratively modeled ST with Random Forests to identify sites in reference condition. We first created a set of dirty models (DMs) that related STs to both natural factors (e.g., climate, watershed area, topography) and measures of SWA, i.e., reservoirs, urbanization, and agriculture. The 3 models performed well (r 2 = 0.84–0.94, residual mean square error [RMSE] = 1.2–2.0 ° C). For each DM, we used partial dependence plots to identify SWA thresholds below which response in ST was minimal. We then used data from only the sites with upstream SWA below these thresholds to build RCMs with only natural factors as predictors (r 2 = 0.87–0.95, RMSE = 1.1–1.9 ° C). Use of only reference-quality sites caused RCMs to suffer modest loss of predictor space and spatial coverage, but this loss was associated with parts of ST response curves that were flat and, therefore, not responsive to further variation in predictor space. We then compared predictions made with the RCMs to predictions made with the DMs with SWA set to 0. For most DMs, setting SWAs to 0 resulted in biased estimates of thermal reference condition.

Freshwater Science↗

USGS2025

Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems

The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.

Biogeosciences↗

USGS2021

Using social values in the prioritization of research: Quantitative examples and generalizations

Identifying critical uncertainties about ecological systems can help prioritize research efforts intended to inform management decisions. However, exclusively focusing on the ecological system neglects the objectives of natural resource managers and the associated social values tied to risks and rewards of actions. I demonstrate how to prioritize research efforts for a harvested population by applying expected value of perfect information (EVPI) to harvest decisions made with a density-independent matrix population model. Research priorities identified by EVPI diverge from priorities identified by matrix elasticity analyses that ignore social utility. Using a density-dependent harvest model, the value of information about the intrinsic productivity of a population is shown to be sensitive to the socially determined penalty for implementing a harvest rate that deviates from the goal because of imperfection in estimation. Synthesis and applications . The effect of including social values into harvest decision-making depends on the assumed population model, uncertainty in population vital rates, and the particular form of the utility function used to represent risk/reward of harvest. EVPI analyses that include perceived utility of different outcomes can be used by managers seeking to optimize monitoring and research spending. Collaboration between applied ecologists and social scientists that quantitatively measure peoples' values is needed in many structured decision-making processes.

Ecology and Evolution↗

USGS2011

USGS research on Florida's isolated freshwater wetlands

The U.S. Geological Survey (USGS) has studied wetland hydrology and its effects on wetland health and ecology in Florida since the 1990s. USGS wetland studies in Florida and other parts of the Nation provide resource managers with tools to assess current conditions and regional trends in wetland resources. Wetland hydrologists in the USGS Florida Water Science Center (FLWSC) have completed a number of interdisciplinary studies assessing the hydrology, ecology, and water quality of wetlands. These studies have expanded the understanding of wetland hydrology, ecology, and related processes including: (1) the effects of cyclical changes in rainfall and the influence of evapotranspiration; (2) surface-water flow, infiltration, groundwater movement, and groundwater and surfacewater interactions; (3) the effects of water quality and soil type; (4) the unique biogeochemical components of wetlands required to maintain ecosystem functions; (5) the effects of land use and other human activities; (6) the influences of algae, plants, and invertebrates on environmental processes; and (7) the effects of seasonal variations in animal communities that inhabit or visit Florida wetlands and how wetland function responds to changes in the plant community.

Florida↗

USGS2021

Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters

Executive Summary Along the coast of the U.S. Gulf of Mexico, the eastern oyster ( Crassostrea virginica ) plays important ecological and economic roles. Commercial landings from this region account for more than 50 percent of all U.S. landings; these oyster reefs also provide varied ecosystem services, including nursery habitat for many fish and macroinvertebrate species, shoreline protection, and water-quality maintenance. Declining trends in both total oyster production and functional reef area across this region have spurred investment in restoration of oyster resources, with specific calls for restoration projects to develop a network of reefs and identify broodstock and sanctuary reef restoration sites. Decision making related to restoration and establishment of a network of oyster reefs in the Gulf of Mexico requires information on both the environment and the effects of the environment on the oyster life cycle (including larval movement, survival, oyster recruitment, reproduction, growth, and mortality). Here, we examined the current state of data and model development in this region with the goal of providing an overview of oyster modeling approaches and an inventory of available data and existing oyster models. This report is meant to provide an overview to managers for understanding existing efforts and identify a path forward to most efficiently inform oyster resource management and restoration planning in moving from a single reef management approach to a reef network management approach. Numerous models related to some aspect of the oyster life cycle have been built, calibrated, and validated for various Gulf of Mexico estuaries over the last few decades (over 30 models identified). These models, which could inform site restoration, can be classified into four approaches: (1) oyster Habitat Suitability Index (HSI) models; (2) larval transport models; (3) on-reef oyster models that may include oyster growth, mortality and reproduction, and substrate persistence; and (4) coupled larval transport on-reef metapopulation models that simulate the entire oyster life cycle. The data requirements, model complexity and assumptions, and transferability vary by approach. Specifically, some approaches may offer greater accessibility, flexibility, and transferability spatially or temporally, with minimal data input, but only provide broad information to support site selection. In contrast, other approaches may require significant site-specific data for their construction and validation but may provide more accurate and location-specific data to support site selection for broodstock reefs. Regardless of modeling approach used, data on environmental drivers, such as salinity, water temperature, or water flow impacting oyster metabolism and movement, are required at appropriate spatial and temporal scales. While numerous data collection platforms, environmental models, and research products exist within Gulf of Mexico estuaries to provide important environmental data to use as drivers in the oyster models, significant variability in temporal and spatial coverage of the data, and variation in the availability of future condition models, exists across estuaries. This variation influences the spatial and temporal scales at which oyster models may be developed and impacts the calibration and validation of the oyster models within a given estuary, affecting its potential ability to address specific management or restoration questions. While multiple modeling approaches exist for informing site selection of broodstock or sanctuary oyster reefs, the development, calibration, and validation of a single modeling platform presents the most efficient, transferable, and useful tool for managers across the Gulf of Mexico. The development of a single modeling platform would involve using standardized input variables, governing equations, and assumptions for the modeled oyster processes and outputs, and for standardized calibration and validation procedures that could be applied within each estuary. The differences among estuary applications would require substituting only estuary-specific environmental data, and calibrating and validating the modeling approach with local oyster data. Two modeling approaches likely to be useful include (1) development of a general geospatial HSI modeling framework that could be applied consistently across estuaries and (2) a mechanistic coupled larval transport on-reef metapopulation model requiring only estuarine specific calibration and hydrodynamic models. Both approaches benefit from existing work across multiple Gulf of Mexico estuaries and could provide valuable support for oyster restoration, but may differ in their ability to address specific questions related to oyster restoration. HSI models specifically guide restoration practitioners in determining suitable habitat based on available data. The HSI approach, while currently more widely used and accessible, requires more development of larval suitability and larval input and output components in order to inform reef connectivity. A metapopulation approach considering the full oyster life cycle that simulates both on-reef oyster growth, mortality, reproduction, substrate persistence, and larval transport (ideally with larval growth and mortality) would provide the greatest detail and level of understanding but requires significant up-front investment. The larval oyster model and on-reef oyster model are usually developed independently for systems, although the two approaches can be coupled to represent the entire oyster life cycle in order to characterize and assess a reef metapopulation. This approach may be less accessible and much more data-intensive, however, and it requires some expertise to run and apply to inform oyster resource management. Ultimately, the development of single modeling platforms for each of these approaches would provide flexible tools applicable across all Gulf of Mexico oyster supporting estuaries. By using a single platform for model development, testing, calibrating and validating, and evaluation of modeled future scenarios, oyster restoration scientists and managers would not only be able to examine different scenario outcomes within a single estuary, but could also have comparable modeled results to evaluate potential outcomes, across estuaries and regions, that are not confounded by varying modeled data inputs, governing equations, assumptions, or user judgement.

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS2018

Montane-breeding bird distribution and abundance across national parks of southwestern Alaska

Between 2004 and 2008, biologists conducted an inventory of breeding birds during May–June primarily in montane areas (>100 m above sea level) in Aniakchak National Monument and Preserve (Aniakchak NMP), Katmai National Park and Preserve (Katmai NPP), and Lake Clark National Park and Preserve (Lake Clark NPP) in southwestern Alaska. Observers conducted 1,021 point counts along 169 transects within 63 10-km × 10-km plots that were randomly selected and stratified by ecological subsection. We created hierarchical N-mixture models to estimate detection probability and abundance for 15 species, including 12 passerines, 2 galliforms, and 1 shorebird. We first modeled detection probability relative to observer, date within season, and proportion of dense vegetation cover around the point, then modeled abundance as a function of land cover composition (proportion of seven coarse-scale land cover types) within 300 m of the survey point. Land cover relationships varied widely among species but most showed selection for low to tall shrubs (0.2–5 m tall) and an avoidance of alpine and 2 dwarf shrub–herbaceous cover types. After adjusting for species not observed, we estimated a minimum of 107 ± 9 species bred in the areas surveyed within the three parks combined. Species richness was negatively associated with elevation and associated land cover types. At comparable levels of survey effort (n = 721 birds detected), species richness was greatest in Lake Clark NPP (75 ± 12 species), lowest in Aniakchak NMP (45 ± 6 species), and intermediate at Katmai NPP (59 ± 10 species). Species richness was similar at equivalent survey effort (n = 973 birds detected) within the Lime Hills, Alaska Range, and Alaska Peninsula ecoregions (68 ± 8; 79 ± 11; 67 ± 11, respectively). Species composition was similar across all three parks and across the three major ecoregions (Alaska Range, Alaska Peninsula, Lime Hills) that encompass them. Our results provide baseline estimates of relative abundance and models of abundance and species richness relative to land cover that can be used to assess future changes in avian distribution. Additionally, these subarctic montane parks may serve as signals of landscape change and barometers for the assessment of population and distributional changes as a result of warming temperatures and changing precipitation patterns.

Alaska↗

USGS2017

Temperature

Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.

Book chapter↗

USGS2022

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra ( Equus quagga ) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Etosha National Park↗

USGS2017

Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western US

Article for outlet: Plant Ecology. Abstract: Big sagebrush (Artemisia tridentata Nutt.) plant communities are widespread non-forested drylands in western North American and similar to all shrub steppe ecosystems world-wide are composed of a shrub overstory layer and a forb and graminoid understory layer. Forbs account for the majority of plant species diversity in big sagebrush plant communities and are important for ecosystem function. Few studies have explored the geographic patterns of forb species richness and composition and their relationships with environmental variables in these communities. Our objectives were to examine the small and large-scale spatial patterns in forb species richness and composition and the influence of environmental variables. We sampled forb species richness and composition along transects at 15 field sites in Colorado, Idaho, Montana, Nevada, Oregon, Utah, and Wyoming, built species-area relationships to quantify differences in forb species richness at sites, and used Principal Components Analysis and nonmetric multidimensional scaling to identify relationships among environmental variables and forb species richness and composition. We found that species richness was most strongly correlated with soil texture, while species composition was most related to climate. The combination of climate and soil texture influences water availability, with important consequences for forb species richness and composition, which suggests climate-change induced modification of soil water availability may have important implications for plant species diversity in the future. Our paper is the first to our knowledge to examine forb biodiversity patterns in big sagebrush ecosystems in relation to environmental factors across the big sagebrush region.

Colorado, Idaho, Montana, Nevada, Oregon, Utah, Wy↗

USGS2025

Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system

Predation establishes risk, which can indirectly influence prey behavior and ecology. We evaluated the influence of Mexican gray wolves ( Canis lupus baileyi ) on habitat selection and spatiotemporal predator avoidance strategies of elk ( Cervus canadensis ). We fit 866 adult female elk with GPS collars across areas of varying wolf densities within the Mexican wolf experimental population area of eastern Arizona and western New Mexico between 2019−2021. Using step-selection functions we examined relative intensity of elk use in relation to landscape attributes, estimated predator/prey diel activity, and measures of risk. Risk metrics included predicted wolf presence, habitat openness, and predicted risky places modeled from attributes of locations where wolves killed elk. Wolf activity varied across seasons and increased midday and night in fall and monsoon seasons. Relative use by elk was best explained by incorporating an interaction between diel period and predicted risky places across all seasons. Elk utilized risky places more in times of nutritional deficit associated with high energetic demands of the third trimester pregnancy and lactation and when forage quality was best, during spring and monsoon season. Particularly, use of risky places increased at less risky times in areas with more established wolf presence, suggesting use of risky places varied relative to exposure to Mexican wolves. These behaviors highlight the importance of temporal avoidance when predators and prey are highly mobile and largely overlap in space. Our research suggests temporally responding to predictable and relatively static environmental characteristics associated with encounter and kill rates may better balance energetic trade-offs than anticipating changes in wolf activity or spatially avoiding areas with higher wolf presence. Thus, elk appear to be more willing to take chances and mitigate cursorial predation risk with a more immediate, reactive approach and make proactive trade-offs during the seasons they can best increase fitness.

Arizona, New Mexico↗

USGS2010

Microbial community shifts influence patterns in tropical forest nitrogen fixation

The role of biodiversity in ecosystem function receives substantial attention, yet despite the diversity and functional relevance of microorganisms, relationships between microbial community structure and ecosystem processes remain largely unknown. We used tropical rain forest fertilization plots to directly compare the relative abundance, composition and diversity of free-living nitrogen (N)-fixer communities to in situ leaf litter N fixation rates. N fixation rates varied greatly within the landscape, and 'hotspots' of high N fixation activity were observed in both control and phosphorus (P)-fertilized plots. Compared with zones of average activity, the N fixation 'hotspots' in unfertilized plots were characterized by marked differences in N-fixer community composition and had substantially higher overall diversity. P additions increased the efficiency of N-fixer communities, resulting in elevated rates of fixation per nifH gene. Furthermore, P fertilization increased N fixation rates and N-fixer abundance, eliminated a highly novel group of N-fixers, and increased N-fixer diversity. Yet the relationships between diversity and function were not simple, and coupling rate measurements to indicators of community structure revealed a biological dynamism not apparent from process measurements alone. Taken together, these data suggest that the rain forest litter layer maintains high N fixation rates and unique N-fixing organisms and that, as observed in plant community ecology, structural shifts in N-fixing communities may partially explain significant differences in system-scale N fixation rates.

Oecologia↗