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At least 667 records · Page 37Linked to original sources
USGS2023

Movement beyond the mean: decoupling sources of individual variation in brook trout movement across seasons

Movement is an important eco-evolutionary process that can shape population and ecosystem structure and function. Accordingly, a firm understanding of species movement ecology is often foundational to effective management and conservation. However, despite movement being an inherently individual-level behavior, there remains a tendency to describe dispersal and migration patterns using simple population-level processes and effects. Overlooking within- and among-individual variation in movement risks incomplete understanding of the intrinsic and extrinsic factors that govern dispersal dynamics and could potentially result in inadequate management of critical behavioral phenotypes. In this study, we monitored movement of over 100 brook trout ( Salvelinus fontinalis ) and quantified the effect of individual-level traits, season, and their interactions to better understand factors that influence vagility. Our results suggest that movement was higher in fall than in summer, particularly for fish in poor condition. But we found no significant main effects for sex, providing no evidence for sex-biased dispersal. To better understand sources of individual variation, we also allowed for sex- and season-specific residual standard deviations. In doing so, we found that, on average, movement was more variable in fall compared to summer, and that females were more variable than males in vagility. Taken together, these results demonstrate how intrinsic, individual-level traits can interact with abiotic environmental conditions to determine movement. They also highlight the potential for simple explanations of movement ecology to overlook important traits that may help predict individual-level behaviors.

Pennsylvania↗
USGS2024

Adaptive capacities of inland fisheries facing anthropogenic pressures

Inland fisheries face multiple, intensifying threats (i.e., proximate human pressures causing degraded ecological attributes) from land development, climate change, resource extraction, and competing demands for water resources. Planning for resiliency amidst these pressures requires understanding the factors that influence an inland fishery’s capacity to adapt to system changes under multiple threats. Incorporating expert knowledge can illuminate priority fisheries and provide important insights where data are otherwise limited. Using data from a global survey of 536 fishery professionals, this study examines perceptions of threats and adaptive capacity (i.e., ability to mitigate or respond to change) in major inland fisheries. We assessed associations across 29 different perceived threats and their ranked influence scores, tested agreement among five adaptive capacity domains (i.e., agency, assets, flexibility, learning, organization), and examined relationships between threats and adaptive capacity domains. Results provide quantitative evidence that the greatest threats to inland fisheries come from outside the fishing sector and that most inland fisheries face multiple threats. Results also support the five domains as a collective measure of adaptive capacity and illuminate a negative association between the threats to a fishery and a fishery’s adaptive capacity. These findings highlight the need for fishery managers to engage in decision making with non-fishery sectors (e.g., multi-sectoral management) and the prioritization of habitat and watershed-scale conservation and rehabilitation efforts for improved adaptability amidst ecological transformation.

Global Environmental Change↗
USGS2011

Ruddy Shelduck Tadorna ferruginea home range and habitat use during the non-breeding season in Assam, India

India is an important non-breeding ground for migratory waterfowl in the Central Asian Flyway. Millions of birds visit wetlands across the country, yet information on their distribution, abundance, and use of resources is rudimentary at best. Limited information suggests that populations of several species of migratory ducks are declining due to encroachment of wetland habitats largely by agriculture and industry. The development of conservation strategies is stymied by a lack of ecological information on these species. We conducted a preliminary assessment of the home range and habitat use of Ruddy Shelduck Tadorna ferruginea in the northeast Indian state of Assam. Seven Ruddy Shelducks were fitted with solar-powered Global Positioning System (GPS) satellite transmitters, and were tracked on a daily basis during the winter of 2009-2010. Locations from all seven were used to describe habitat use, while locations from four were used to quantify their home range, as the other three had too few locations (< 30) for home range estimation. A Brownian Bridge Movement Model (BBMM), used to estimate home ranges, found that the Ruddy Shelduck had an average core use area (i.e. the contour defining 50% of positions) of 40 km 2 (range = 22-87 km 2 ) and an average home range (95% contour) of 610 km 2 (range = 222-1,550 km 2 ). Resource Selection Functions (RSF), used to describe habitat use, showed that the birds frequented riverine wetlands more than expected, occurred on grasslands and shrublands in proportion to their availability, and avoided woods and cropland habitats. The core use areas for three individuals (75%) were on the Brahmaputra River, indicating their preference for riverine habitats. Management and protection of riverine habitats and nearby grasslands may benefit conservation efforts for the Ruddy Shelduck and waterfowl species that share these habitats during the non-breeding season.

Assam↗
USGS2024

A comparative framework to develop transferable species distribution models for animal telemetry data

Species distribution models (SDMs) have become increasingly popular for making ecological inferences, as well as predictions to inform conservation and management. In predictive modeling, practitioners often use correlative SDMs that only evaluate a single spatial scale and do not account for differences in life stages. These modeling decisions may limit the performance of SDMs beyond the study region or sampling period. Given the increasing desire to develop transferable SDMs, a robust framework is necessary that can account for known challenges of model transferability. Here, we propose a comparative framework to develop transferable SDMs, which was tested using satellite telemetry data from green turtles ( Chelonia mydas ). This framework is characterized by a set of steps comparing among different models based on (1) model algorithm (e.g., generalized linear model vs. Gaussian process regression) and formulation (e.g., correlative model vs. hybrid model), (2) spatial scale, and (3) accounting for life stage. SDMs were fitted as resource selection functions and trained on data from the Gulf of Mexico with bathymetric depth, net primary productivity, and sea surface temperature as covariates. Independent validation datasets from Brazil and Qatar were used to assess model transferability. A correlative SDM using a hierarchical Gaussian process regression (HGPR) algorithm exhibited greater transferability than a hybrid SDM using HGPR, as well as correlative and hybrid forms of hierarchical generalized linear models. Additionally, models that evaluated habitat selection at the finest spatial scale and that did not account for life stage proved to be the most transferable in this study. The comparative framework presented here may be applied to a variety of species, ecological datasets (e.g., presence-only, presence-absence, mark-recapture), and modeling frameworks (e.g., resource selection functions, step selection functions, occupancy models) to generate transferable predictions of species–habitat associations. We expect that SDM predictions resulting from this comparative framework will be more informative management tools and may be used to more accurately assess climate change impacts on a wide array of taxa.

Ecosphere↗
USGS2009

Broadening the focus of bat conservation and research in the USA for the 21st century

Appropriately, bat conservation in the USA during the 20th century focused on species that tend to aggregate in large numbers and locations (e.g. maternity roosts, hibernacula) where populations are most vulnerable. Extensive research into habitat needs (primarily for roosting) of reproductive females during the previous 2 decades has produced a wealth of information useful for developing conservation strategies for this group in their summer roost areas. However, the ecological needs of males, non-reproductive females, and juveniles have received far less attention, as have the ecological needs of all bats outside the pup-rearing season. Hence, it is unlikely that a single paradigm could comprehensively address conservation needs of all demographic groups within a species because they may have different seasonal distributions, reproductive strategies, and thermoregulatory needs. Herein, we recommend research into a wider spectrum of demographic groups and seasons to form a more holistic vision of the conservation needs of bats. We urge greater attention to understanding thermo-energetic and reproductive underpinnings of observed patterns of seasonal distribution and habitat selection by bats in the USA. Such understanding is instrumental for development of scientifically sound conservation strategies to confront emerging threats to conservation of bats in the 21st century: climate change, disease, habitat degradation, and environmental contaminants. We discuss interconnections among these emerging threats and the fundamental need to incorporate understanding of thermo-energetic strategies of bats in development of conservation strategies or legislation to mitigate potential impacts on bat populations of the USA.

Endangered Species Research↗
USGS2022

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R 2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes.

Kansas↗
USGS2016

The precision problem in conservation and restoration

Within the varied contexts of environmental policy, conservation of imperilled species populations, and restoration of damaged habitats, an emphasis on idealized optimal conditions has led to increasingly specific targets for management. Overly-precise conservation targets can reduce habitat variability at multiple scales, with unintended consequences for future ecological resilience. We describe this dilemma in the context of endangered species management, stream restoration, and climate-change adaptation. Inappropriate application of conservation targets can be expensive, with marginal conservation benefit. Reduced habitat variability can limit options for managers trying to balance competing objectives with limited resources. Conservation policies should embrace habitat variability, expand decision-space appropriately, and support adaptation to local circumstances to increase ecological resilience in a rapidly changing world.

Trends in Ecology and Evolution↗
USGS2023

Microhabitat use of native Santa Ana sucker and arroyo chub in an effluent-dominated southern California stream

A significant amount of the base flow of the Santa Ana River, located within California's arid Los Angeles metropolitan region, originates from two wastewater treatment facilities: the Rialto wastewater treatment facility and Rapid Infiltration and Extraction facility. The Santa Ana sucker ( Pantosteus santaanae , syn. Catostomus santaanae ) and arroyo chub ( Gila orcuttii ) are two native species listed in the Upper Santa Ana Habitat Conservation Plan, which aims to balance water supply needs with the ecological needs of native fauna. Consequently, an understanding of the habitat needs of these fishes will play a crucial role in achieving the goals outlined by the conservation plan. We used fish presence during snorkel surveys with habitat availability surveys to quantify habitat selection by both native fish species within a resource selection function analytical framework. We found that both species selected habitat near structures that could serve as refugia from potential predators. In addition, Santa Ana sucker selected habitats with high gravel and cobble substrate composition, presumably to fulfill complementary habitat needs such as foraging and spawning. Our results suggest that habitat alterations due to water management infrastructure and an increasing population size of nonnative predators may also affect native fish habitat selection in the Santa Ana River.

California↗
USGS2020

Calibrating environmental DNA metabarcoding to conventional surveys for measuring fish species richness

The ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environmental DNA metabarcoding is an approach that overcomes low detection probabilities and should consequently enhance estimates of biodiversity and its proxy, species richness. Here, we synthesize 37 studies in natural aquatic systems to compare species richness estimates for bony fish between eDNA metabarcoding and conventional methods, such as nets, visual census, and electrofishing. In freshwater systems with fewer than 100 species, we found eDNA metabarcoding detected more species than conventional methods. Using multiple genetic markers further increased species richness estimates with eDNA metabarcoding. For more diverse freshwater systems and across marine systems, eDNA metabarcoding reported similar values of species richness to conventional methods; however, more studies are needed in these environments to better evaluate relative performance. In systems with greater biodiversity, eDNA metabarcoding will require more populated reference databases, increased sampling effort, and multi-marker assays to ensure robust species richness estimates to further validate the approach. eDNA metabarcoding is reliable and provides a path for broader biodiversity assessments that can outperform conventional methods for estimating species richness.

Frontiers in Ecology and Evolution↗
USGS2025

Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse

Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However, false positive detections from ML classifiers can result in erroneous ecological models that can lead to misguided management and conservation actions. We used a two-stage general approach to understand and reduce false positive detections, a technique in which outputs of the primary classification model are passed to a secondary classification model to yield the probability that a detection from the primary model is a true positive detection. This approach is demonstrated on two open-source models that detect Ruffed Grouse ( Bonasa umbellus ). We analyzed over 9500 h of acoustic data collected in 2022–2023 from the Green Mountain National Forest in Vermont, USA, and found the two models detected different types of acoustic signals associated with differing life history traits. The first model yielded 4106 detections (71.5 % true positives) while the second model yielded 524 detections (17.0 % true positives). Secondary logistic regression models separated true positives and false positives with high accuracy (84.5 % and 89.8 % respectively). Our findings go beyond improving Ruffed Grouse monitoring and conservation efforts to, more broadly, illustrate how two-stage ML approaches can improve the use of model-derived detections in wildlife research.

Vermont↗
USGS2025

Scientific opportunities in the National Landscape Conservation System

The National Landscape Conservation System consists of unique and beautiful places across America’s landscapes where identified resources and values are protected and science is highlighted. The mission of the National Landscape Conservation System (NLCS), which is managed by the Bureau of Land Management and is often referred to as the agency’s National Conservation Lands, is to conserve, protect, and restore nationally significant landscapes for their cultural, ecological, and scientific values. This clear inclusion of science in the NLCS mission sets the stage for individual units to serve as places of learning, teaching, discovery, and innovation. Science is an integral part of managing the National Conservation Lands, and science conducted within and across the more than 900 units that make up the NLCS can inform and influence conservation and public land management well beyond its boundaries. Here, we highlight seven core aspects of National Conservation Lands that present valuable science opportunities: (1) the scientific values for which individual units are designated; (2) the many other resources, objects, and values within units; (3) the value of units as “control” sites for understanding the effects of activities such as mineral extraction that commonly occur elsewhere on multiple-use public lands but are often prohibited within National Conservation Lands; (4) the value of units for studying the effects of activities such as recreation that regularly occur and may be intensified on National Conservation Lands; (5) the high visibility of units, which draws strong interest and engagement from scientists, partners, and the public; (6) the functioning of the units as a network managed for a common purpose, which provides an opportunity to explore cross-cutting science questions across widely varying contexts and geographies; and (7) the opportunities units provide to promote and apply Indigenous Knowledge to scientific research to manage natural and cultural resources. Because of all of these characteristics, National Conservation Lands can serve as hubs for basic and applied science that can inform management of all public lands and resources into the future. We highlight these science opportunities through examples from existing units and suggest two actions that could help further science activities and impact on National Conservation Lands.

Parks Stewardship Forum↗
USGS2021

Structured decision making and optimal bird monitoring in the northern Gulf of Mexico

The avian conservation community struggles to design and implement large scale, long-term coordinated bird monitoring programs within the northern Gulf of Mexico due to the complexity of the conservation enterprise in the region; this complexity arises from the diverse stakeholders, multiple jurisdictions, complex ecological processes, myriad habitats, and over 500 species of birds using the region for at least some part of their annual cycle. In addition, long-term monitoring over large spatial scales is difficult because of the need for monitoring data to both (1) evaluate management and restoration outcomes, and (2) provide reliable information about the status and trends of bird populations over time. To address these challenges, the Gulf of Mexico Avian Monitoring Network developed a problem statement: “How can a cost-effective monitoring strategy for the Gulf Coast bird community and ecosystem be developed that evaluates ongoing conservation activities and chronic and acute threats; maximizes learning; and is flexible and holistic enough to detect novel ecological threats and evaluate new and emerging conservation activities?” A structured decision-making framework was then used to articulate and quantify stakeholder values related to the problem statement. One use of the stakeholder values was to develop a regional, strategic plan for bird monitoring, which is presented elsewhere. A formal and complete decision support tool for conservation investments in monitoring and research guided by the stakeholder values is presented in this report. The technical aspects of the stakeholder value model and a portfolio analysis that could be used to guide decision making when allocating resources for monitoring activities is described. Whereas the decision analysis presented here could be useful to any decision maker faced with difficult choices about resource allocation, it is designed for decision makers who request monitoring study proposals and then determine which combination of proposals to fund. The portfolio decision support tool is designed to help funding agencies and organizations identify resource allocation strategies to maximize stated objectives. To begin the decision analysis, an objectives hierarchy and quantitative performance metrics from the values of the Gulf of Mexico bird conservation community were created by a panel of regional stakeholders. Each fundamental objective and sub-objective in the hierarchy is composed of several performance metrics. To test the decision support tool, the authors evaluated a combination of monitoring study proposals written for the region and simulated proposals. Each proposal was scored against the performance metrics and used multi-attribute utility theory to combine the multiple objectives into a measure of total monitoring benefit. The total monitoring benefit and costs of each proposal were then used in a constrained optimization routine to identify optimal monitoring portfolios, that is, a combination of activities that maximizes monitoring benefits while meeting cost and other constraints of interest to stakeholders. A graphical solution based on the concept of Pareto efficiency, which is useful in situations when cost constraints and exact budgets are not known, is also provided. Finally, an evaluation of the sensitivity of the decision-making framework to the weights assigned to objectives by stakeholders is included. This decision support tool allows decision makers to identify an optimal suite of monitoring proposals with a transparent portfolio analysis that includes user-defined constraints (such as costs).

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2024

Ecological and social drivers of Mexican wolf home range size across spatiotemporal scales

Elucidating factors influencing home range size is fundamental to the ecology and management of wildlife species, particularly those of conservation concern, because they can provide insight into how species utilize and interact with their environment. Variation in home range size can be related to intraspecific competition and social organization, energetic requirements in relation to habitat productivity, allometric relationships, and population density. The Mexican Gray Wolf ( Canis lupus baileyi ) is an endangered subspecies of the Gray Wolf whose home range size has not yet been studied. We examined ecological and social drivers of home range size of 22 Mexican Wolf packs between 2017 and 2021 across 4 biological time frames: annual; denning; post-denning; and non-denning. We used a 95% Brownian Bridge Movement Model home range estimator and generalized linear mixed-effect models to assess these relationships. Home range size was inversely correlated with estimated ungulate biomass, which was the most influential driver of home range size at annual and post-denning time frames. Larger packs utilized larger ranges during denning and post-denning time frames, while packs with larger litters had smaller ranges during the denning season. Snow depth was inversely related to home range size during the non-denning season. Our results indicate that both ecological and social factors are important and seasonally dependent in driving Mexican Wolf home range size. Use of a multiscale approach in future home range studies could discern relevant factors for species during time frames of interest.

Journal of Mammology↗
USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗
USGS2024

Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States

In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.

western United States↗
USGS2018

Behavior and reproductive ecology of the Sicklefin Redhorse: An imperiled southern Appalachian Mountain fish

Many nongame fishes are poorly understood but are essential to maintaining healthy aquatic ecosystems globally. The undescribed Sicklefin Redhorse Moxostoma sp. is a rare, imperiled, nongame fish endemic to two southern Appalachian Mountain river basins. Little is known of its behavior and ecology, but this information is urgently needed for conservation planning. We assessed the spatial and temporal bounds of spawning migration, quantified seasonal weekly movement patterns, and characterized seasonal and spawning behavior using radiotelemetry and weir sampling in the Hiwassee River basin, North Carolina–Georgia, during 2006 and 2007. Hiwassee River tributaries were occupied predominantly during the fish's spawning season, lower reaches of the tributaries and the Hiwassee River were primarily occupied during the postspawning season (i.e., summer and fall), and lower lotic reaches of Hiwassee River (upstream from Hiwassee Lake) were occupied during winter. Adults occupied Hiwassee Lake only as a movement corridor during spawning migrations. Both sexes conducted upstream spawning migrations simultaneously, but males occupied spawning tributaries longer than females. Sicklefin Redhorse exhibited interannual spawning‐area and tributary fidelity. Cold water temperatures associated with hypolimnetic releases from reservoirs and meteorological conditions influenced spawning migration distance and timing. During 2007, decreased discharges during the spawning season were associated with decreases in migration distance and spawning tributary occupancy duration. Foraging was the dominant behavior observed annually, followed by reproductive behaviors (courting and spawning) during the spawning season. No agonistic reproductive behavior was observed, but females exhibited a repetitious postspawning digging behavior that may be unique in the family Catostomidae. Our findings suggest that protection and restoration of river continuity, natural flow regimes, seasonally appropriate water temperatures, and geographic range expansion are critical components to include in Sicklefin Redhorse conservation planning. Fisheries and ecosystem managers can use our findings to justify sensitive management decisions that conserve and restore critical streams and rivers occupied by this imperiled species.

Hiwassee River↗
USGS2017

Ecology of the macrophyte Podostemum ceratophyllum Michx. (Hornleaf riverweed), a widespread foundation species of eastern North American rivers

Podostemum ceratophyllum , commonly called Hornleaf Riverweed, occurs in mid-order montane and piedmont rivers of eastern North America, where the plant grows submerged and attached to rocks and stable substrates in swift, aerated water. Multiple studies, mostly conducted in the southern portions of the plant’s range, have shown that Podostemum can variously influence benthic communities in flowing waters. However, a synthetic review of the biology and ecology of the plant is needed to inform conservation, particularly because P. ceratophyllum is reported to be in decline in much of its range, for mostly unknown reasons. We have thus summarized the literature showing that Podostemum provides substantial habitat for invertebrates and fish, may be consumed by invertebrates, turtles, and other vertebrates, removes and sequesters dissolved elements (i.e., nitrogen, phosphorus, calcium, zinc, etc.) from the water column, and contributes organic matter to the detrital pool. Podostemum may be tolerant to some forms of pollution but appears vulnerable to sedimentation, epiphytic over-growth, and hydrologic changes that result in desiccation, and possibly increased herbivory pressure. Much remains unknown about Podostemum , including aspects of morphological variation, seed dispersal, and tolerance to changes in temperature and water chemistry. Nonetheless, Podostemum may be considered a foundation species, whose loss from eastern North American rivers is likely to affect higher trophic levels and ecosystem processes.

Aquatic Botany↗
USGS2014

Association, roost use and simulated disruption of Myotis septentrionalis maternity colonies

How wildlife social and resource networks are distributed on the landscape and how animals respond to resource loss are important aspects of behavioral ecology. For bats, understanding these responses may improve conservation efforts and provide insights into adaptations to environmental conditions. We tracked maternity colonies of northern bats ( Myotis septentrionalis ) at Fort Knox, Kentucky, USA to evaluate their social and resource networks and space use. Roost and social network structure differed between maternity colonies. Overall roost availability did not appear to be strongly related to network characteristics or space use. In simulations for our two largest networks, roost removal was related linearly to network fragmentation; despite this, networks were relatively robust, requiring removal of >20% of roosts to cause network fragmentation. Results from our analyses indicate that northern bat behavior and space use may differ among colonies and potentially across the maternity season. Simulation results suggest that colony social structure is robust to fragmentation caused by random loss of small numbers of roosts. Flexible social dynamics and tolerance of roost loss may be adaptive strategies for coping with ephemeral conditions in dynamic forest habitats.

Behavioural Processes↗