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At least 1,261 records · Page 70Linked to original sources
USGS2016

Assessing the sensitivity of avian species abundance to land cover and climate

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

Ecosphere↗
USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗
USGS2016

Climate change is advancing spring onset across the U.S. national park system

Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change. Here, we use estimates of start of spring based on climatically modeled dates of first leaf and first bloom derived from indicator plant species to evaluate the recent timing of spring onset (past 10–30 yr) in each U.S. natural resource park relative to its historical range of variability across the past 112 yr (1901–2012). Of the 276 high latitude to subtropical parks examined, spring is advancing in approximately three-quarters of parks (76%), and 53% of parks are experiencing “extreme” early springs that exceed 95% of historical conditions. Our results demonstrate how changes in climate seasonality are important for understanding ecological responses to climate change, and further how spatial variability in effects of climate change necessitates different approaches to management. We discuss how our results inform climate change adaptation challenges and opportunities facing parks, with implications for other protected areas, by exploring consequences for resource management and planning.

Ecosphere↗
USGS2016

Using structural equation modeling to link human activities to wetland ecological integrity

The integrity of wetlands is of global concern. A common approach to evaluating ecological integrity involves bioassessment procedures that quantify the degree to which communities deviate from historical norms. While helpful, bioassessment provides little information about how altered conditions connect to community response. More detailed information is needed for conservation and restoration. We have illustrated an approach to addressing this challenge using structural equation modeling (SEM) and long-term monitoring data from Rocky Mountain National Park (RMNP). Wetlands in RMNP are threatened by a complex history of anthropogenic disturbance including direct alteration of hydrologic regimes; elimination of elk, wolves, and grizzly bears; reintroduction of elk (absent their primary predators); and the extirpation of beaver. More recently, nonnative moose were introduced to the region and have expanded into the park. Bioassessment suggests that up to half of the park's wetlands are not in reference condition. We developed and evaluated a general hypothesis about how human alterations influence wetland integrity and then develop a specific model using RMNP wetlands. Bioassessment revealed three bioindicators that appear to be highly sensitive to human disturbance (HD): (1) conservatism, (2) degree of invasion, and (3) cover of native forbs. SEM analyses suggest several ways human activities have impacted wetland integrity and the landscape of RMNP. First, degradation is highest where the combined effects of all types of direct HD have been the greatest (i.e., there is a general, overall effect). Second, specific HDs appear to create a “mixed-bag” of complex indirect effects, including reduced invasion and increased conservatism, but also reduced native forb cover. Some of these effects are associated with alterations to hydrologic regimes, while others are associated with altered shrub production. Third, landscape features created by historical beaver activity continue to influence wetland integrity years after beavers have abandoned sites via persistent landforms and reduced biomass of tall shrubs. Our model provides a system-level perspective on wetland integrity and provides a context for future evaluations and investigations. It also suggests scientifically supported natural resource management strategies that can assist in the National Park Service mission of maintaining or, when indicated, restoring ecological integrity “unimpaired for future generations.”

Colorado↗
USGS2017

Full annual cycle climate change vulnerability assessment for migratory birds

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Ecological Applications↗
USGS2017

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Ecosphere↗
USGS2017

Optimal control of an invasive species using a reaction-diffusion model and linear programming

Managing an invasive species is particularly challenging as little is generally known about the species’ biological characteristics in its new habitat. In practice, removal of individuals often starts before the species is studied to provide the information that will later improve control. Therefore, the locations and the amount of control have to be determined in the face of great uncertainty about the species characteristics and with a limited amount of resources. We propose framing spatial control as a linear programming optimization problem. This formulation, paired with a discrete reaction-diffusion model, permits calculation of an optimal control strategy that minimizes the remaining number of invaders for a fixed cost or that minimizes the control cost for containment or protecting specific areas from invasion. We propose computing the optimal strategy for a range of possible model parameters, representing current uncertainty on the possible invasion scenarios. Then, a best strategy can be identified depending on the risk attitude of the decision-maker. We use this framework to study the spatial control of the Argentine black and white tegus ( Salvator merianae ) in South Florida. There is uncertainty about tegu demography and we considered several combinations of model parameters, exhibiting various dynamics of invasion. For a fixed one-year budget, we show that the risk-averse strategy, which optimizes the worst-case scenario of tegus’ dynamics, and the risk-neutral strategy, which optimizes the expected scenario, both concentrated control close to the point of introduction. A risk-seeking strategy, which optimizes the best-case scenario, focuses more on models where eradication of the species in a cell is possible and consists of spreading control as much as possible. For the establishment of a containment area, assuming an exponential growth we show that with current control methods it might not be possible to implement such a strategy for some of the models that we considered. Including different possible models allows an examination of how the strategy is expected to perform in different scenarios. Then, a strategy that accounts for the risk attitude of the decision-maker can be designed.

Florida↗
USGS2018

Strategies for effective collaborative manuscript development in interdisciplinary science teams

Science is increasingly being conducted in large, interdisciplinary teams. As team size increases, challenges can arise during manuscript development, where achieving one team goal (e.g., inclusivity) may be in direct conflict with other goals (e.g., efficiency). Here, we present strategies for effective collaborative manuscript development that draw from our experiences in an interdisciplinary science team writing collaborative manuscripts for six years. These strategies are rooted in six guiding principles that were important to our team: to create a transparent, inclusive, and accountable research team that promotes and protects team members who have less power to influence decision‐making while fostering creativity and productivity. To help alleviate the conflicts that can arise in collaborative manuscript development, we present the following strategies: understand your team composition, create an authorship policy and discuss authorship early and often, openly announce manuscript ideas, identify and communicate the type of manuscript and lead author management style, and document and describe authorship contributions. These strategies can help reduce the probability of group conflict, uphold individual and team values, achieve fair authorship practices, and increase science productivity.

Ecosphere↗
USGS2018

Spatial decision‐support tools to guide restoration and seed‐sourcing in the Desert Southwest

Altered disturbance regimes and shifting climates have increased the need for large‐scale restoration treatments across the western United States. Seed‐sourcing remains a considerable challenge for revegetation efforts, particularly on public lands where policy favors the use of native, locally sourced plant material to avoid maladaptation. An important area of emphasis for public agencies has been the development of spatial tools to guide selection of genetically appropriate seed. When genetic information is not available, current seed transfer guidelines stipulate use of climate‐based or provisional seed transfer zones, which serve as a proxy for local adaptation by representing climate gradients to which plants are commonly adapted. Despite this guidance, little emphasis has been placed on identifying best practices for deriving provisional seed zones or on incorporating predictions from future climate. We describe a flexible, multivariate procedure for deriving such zones that incorporates a broad range of climatic characteristics while accounting for covariation among climate variables. With this approach, we derive provisional seed zones for four regions in the Desert Southwest (the Mojave Desert, Sonoran Desert, Colorado Plateau, and Southern Great Basin). To facilitate future‐resilient restoration designs, we project each zone into its relative position in the future climate based on near‐term, RCP4.5 and RCP8.5 emissions scenarios. Although provisional seed zones are useful in a variety of contexts, there are also situations in which site‐specific guidance is preferable. To meet this need, we implement Climate Distance Mapper, an interactive decision‐support tool designed to help practitioners match seed sources with restoration sites through an accessible online interface. The application allows users to rank the suitability of seed sources anywhere on the landscape based on multivariate climate distances. Users can perform calculations for either the current or future climates. Additionally, tools are available to guide sample effort in regional‐scale seed collections or to partition the landscape into climate clusters representing suitable planting sites for different seed sources. Our tools and analytic procedures represent a flexible and reproducible framework for advancing native plant development programs in the Desert Southwest and beyond.

Ecosphere↗
USGS2019

River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics

Inundation dynamics are a key driver of ecosystem form and function in river‐valley bottoms. Inundation itself is an outcome of multi‐scalar interactions and can vary strongly within and among river reaches. As a result, establishing to what degree and how inundation dynamics vary spatially both within and among river reaches can be challenging. The objective of this study was to understand how river‐valley morphology, basin size, and flow‐event magnitude interact to affect inundation dynamics in river‐valley bottoms. We used 2D hydraulic models to simulate inundation in four river reaches from Maryland's Piedmont physiographic province, and qualitatively and quantitatively summarized within‐ and among‐reach patterns of inundation extent, duration, depth, shear stress, and wetting frequencies. On average, reaches from confined valley settings experienced less extensive flooding, shorter durations and shallower depths, stronger gradients of maximum shear stress, and relatively infrequent wetting compared to reaches from unconfined settings. These patterns were generally consistent across flow‐event magnitudes. Patterns of within‐reach flooding across event magnitudes revealed complex interactions between hydrology and surface topography. We concluded that valley morphology had a greater impact on flooding patterns than basin size: Inundation patterns were more consistent across reaches of similar morphology than similar basin size, but absolute values of inundation characteristics varied between large and small basins. Our results showed that the manifestation of out‐of‐bank flows in valley floors can vary widely depending on geomorphic context, even within a single physiographic province, which suggests that hydrologic and hydraulic conditions experienced on the valley floor may not be well represented by existing hydrologic metrics derived from discharge data alone. We thus support the notion that 2D hydraulic models can be useful hydrometric tools for cross‐scale investigations of floodplain ecosystems.

Maryland↗
USGS2019

Quantifying risk of whale–vessel collisions across space, time, and management policies

Transportation industries can negatively impact wildlife populations, including through increased risk of mortality. To mitigate this risk successfully, managers and conservationists must estimate risk across space, time, and alternative management policies. Evaluating this risk at fine spatial and temporal scales can be challenging, especially in systems where wildlife–vehicle collisions are rare or imperfectly detected. The sizes and behaviors of wildlife and vehicles influence collision risk, as well as how much they co‐occur in space and time. We applied a modeling framework based on encounter theory to quantify the risk of lethal collisions between endangered North Atlantic right whales and vessels. Using Automatic Identification System vessel traffic data and spatially explicit estimates of right whale abundance that account for imperfect detection, we modeled risk at fine spatiotemporal scales before and after implementation of a vessel speed rule in the southeastern United States. The expected seasonal mortality rates of right whales decreased by 22% on average after the speed rule was implemented, indicating that the rule is effective at reducing lethal collisions. The rule's effect on risk was greatest where right whales were abundant and vessel traffic was heavy, and its effect varied considerably across time and space. Our framework is spatiotemporally flexible, process‐oriented, computationally efficient and accounts for uncertainty, making it an ideal approach for evaluating many wildlife management policies, including those regarding collisions between wildlife and vehicles and cases in which wildlife may encounter other dangerous features such as wind farms, seismic surveys, or fishing gear.

Georgia, Florida↗
USGS2019

Evaluating mechanisms of plant‐mediated effects on herbivore persistence and occupancy across an ecoregion

Contemporary climate change is rapidly creating one of the greatest challenges for management and conservation during the 21st century. Mountain ecosystems, which have a high degree of spatial heterogeneity and contain numerous habitat specialists, have been identified as particularly vulnerable. We used data from multiple years across sites spanning a >40 million ha ecoregion to test hypotheses regarding how community‐level characteristics of vegetation may affect a mammalian generalist herbivore, the American pika ( Ochotona princeps ). We examined patterns of pika persistence across sites in the hydrographic Great Basin, and occupancy within a subset of these sites. We used mixed‐effects logistic regression models to compare evidence in support of competing explanations for each pattern within an information–theoretic framework (using Akaike's information criterion). Models reflected four hypothesized classes of mechanisms related to nutritional ecology, ecosystem function, indirect indication of climatic effects, and (synergistic) combinations of these three classes. At the site level, models reflecting synergistic effects received the most support. At the within‐site level, support appeared to be split equally among hypotheses containing predictors related to either nutritional ecology or indirect climate effects. Well‐supported predictors included cover of invasive plant species, cover of more‐xeric plant species, species evenness, and proportion of graminoid species. Our results both (1) identify important aspects of vegetation communities that may influence herbivore distribution in mountainous areas across a large, diverse geographic region, and (2) contribute to an improved understanding of how mountain ecosystems may be affected by ongoing climate change, more broadly.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗
USGS2019

Floodplains provide important amphibian habitat despite multiple ecological threats

Floodplain ponds and wetlands are productive and biodiverse ecosystems, yet they face multiple threats including altered hydrology, land use change, and non‐native species. Protecting and restoring important floodplain ecosystems requires understanding how organisms use these habitats and respond to altered environmental conditions. We developed Bayesian models to evaluate occupancy of six amphibian species across 103 off‐channel aquatic habitats in the Chehalis River floodplain, Washington State, USA. The basin has been altered by changes in land use, reduced river–wetland connections, and the establishment of non‐native American bullfrogs ( Rana catesbeiana = Lithobates catesbeianus ) and centrarchid fishes, all of which we hypothesized could influence native amphibian occupancy. Despite potential threats, the floodplain habitats had relatively high rates of native amphibian occupancy, particularly when compared to studies from non‐floodplain habitats within the species’ native ranges. The biggest challenge for native amphibians appears to be non‐native centrarchid fishes, which strongly reduced occupancy of two native amphibians: the northern red‐legged frog ( Rana aurora ) and the northwestern salamander ( Ambystoma gracile ). Emergent vegetative cover increased occupancy probability for all five native amphibian species, indicating that plant management may offer a strategy to counter the negative effect of centrarchids by providing refuge from predation. We found that temporary and permanent hydroperiod sites supported different species; hence, both should be conserved on the landscape. Lastly, human‐created and natural ponds had similar amphibian occupancy patterns, suggesting that pond construction offers a viable strategy for adding habitats to the floodplain landscape. Overall, floodplain ponds and wetlands provide important amphibian habitat, and we offer management strategies that will bolster amphibian occupancy in an altered floodplain landscape.

Washington↗
USGS2019

A mechanistic understanding of ecological responses to land-use change in headwater streams

Anthropogenic activities, such as oil and natural gas development (ONGD), have significantly altered the landscape. It is often challenging to identify the mechanistic processes underlying ecological responses to land-use change (LUC). In aquatic ecosystems, alterations to habitat and food availability and water quality associated with increased LUC are key mechanistic pathways that deserve management consideration. We used structural equation modeling to evaluate how LUC associated with ONGD could influence macroinvertebrate and fish across 40 sites in six headwater streams in the Wyoming Range of the Upper Green River Basin, Wyoming. The most important mechanistic pathway varied, but responses were frequently driven by a direct effect of LUC or related to changes in food availability and water quality. Habitat complexity was the least important mechanistic pathway in our models. Our results also highlight that responses may reflect an organism's degree of habitat or resource specialization and/or sensitivity to changes in water quality. Habitat pathways were more important for habitat specialists (e.g., Mottled Sculpin, Cottus bairdii ), food pathways were more important for food specialists (e.g., Colorado River Cutthroat Trout, Oncorhynchus clarki pleuriticus ; Mountain Sucker, Catostomus platyrhynchus ), and sensitivity to increased salinity was important for intolerant species (e.g., O. clarki , C. bairdii , and predatory macroinvertebrates). Continued identification of the specific mechanisms underlying species’ responses to increased LUC will aid in the conservation of ecologically and economically important species.

Wyoming↗
USGS2019

Sequence analysis and acoustic tracking individual lake sturgeon identifies multiple patterns of river-lake habitat use

Understanding the spatial ecology of sturgeon (Acipenseridae) has proven to be a challenge due to the life history characteristics of these fish, especially their long life span, intermittent spawning, and long‐distance migrations. Within the Huron‐Erie Corridor (HEC) of the Laurentian Great Lakes, habitat use of 247 lake sturgeon ( Acipenser fulvescens ) was monitored over a three‐year period (2015–2017) with acoustic transmitters. Extensive spatial coverage of receivers throughout the St. Clair River, Lake St. Clair, and Detroit River between Lake Huron and Lake Erie (~150 km) allowed for continuous monitoring of the movements of acoustic‐tagged individuals. Sequence analysis of individual detection histories was used to describe lake sturgeon habitat use and to determine (1) whether distinct habitat‐use patterns occurred within the HEC; (2) whether the range of habitats occupied varied across seasons among sturgeon grouped by common patterns; and (3) whether variation identified was related to tagging sites in the two rivers or sex. Lake sturgeon were active throughout the HEC, but five distinct habitat‐use patterns were identified. River residents were not broadly distributed across entire rivers, but rather associated with particular segments (middle Detroit River, St. Clair River delta). Variations in habitat‐use sequences were in part related to three river tagging sites, but not sex, and did not produce groups with sequences that reflected all five habitat‐use patterns derived from cluster analysis. Lake sturgeon distribution was reduced to fewer habitat segments during winter and expanded to the maximum extent during the spring and summer. Conservation planning that incorporates behavioral diversity of habitat use is relatively rare due to a lack of observations on movements of individuals at biologically relevant spatial and temporal scales, but using telemetry and sequence analysis methods may promote the success of conservation and restoration efforts.

St. Clair River, Lake St. Clair, Detroit River↗
USGS2020

Dynamic Habitat Disturbance and Ecological Resilience (DyHDER): Modeling population responses to habitat condition

Understanding how populations respond to spatially heterogeneous habitat disturbance is as critical to conservation as it is challenging. Here, we present a new, free, and open-source metapopulation model: Dynamic Habitat Disturbance and Ecological Resilience (DyHDER), which incorporates subpopulation habitat condition and connectivity into a population viability analysis framework. Modeling temporally dynamic and spatially explicit habitat disturbance of varying magnitude and duration is accomplished through the use of habitat time-series data and a mechanistic approach to adjusting subpopulation vital rates. Additionally, DyHDER uses a probabilistic dispersal model driven by site-specific habitat suitability, density dependence, and directionally dependent connectivity. In the first application of DyHDER, we explore how fragmentation and projected climate change are predicted to impact a well-studied Bonneville cutthroat trout metapopulation in the Logan River (Utah, USA). The DyHDER model predicts which subpopulations are most susceptible to disturbance, as well as the potential interactions between stressors. Further, the model predicts how populations may be expected to redistribute following disturbance. This information is valuable to conservationists and managers faced with protecting populations of conservation concern across landscapes undergoing changing disturbance regimes. The DyHDER model provides a valuable and generalizable new tool to explore metapopulation resilience to spatially and temporally dynamic stressors for a diverse range of taxa and ecosystems.

Ecosphere↗
USGS2020

Cooperatively improving tallgrass prairie with adaptive management

Adaptive management (AM) is widely recommended as an approach for learning to improve resource management, but successful AM projects remain relatively uncommon, with few documented examples applied by natural resource management agencies. We used AM to make recommendations for the management of native tallgrass prairie plant communities in western Minnesota and eastern North and South Dakota, USA. After nine years of data collection and learning, we report on whether the condition of the prairie improved with management and which actions and frequency of action allowed improvement. Our approach to AM employed Bayesian updating to generate annual management recommendations at a site and state-dependent scale. We also used a logistic regression approach to complement the output from the AM model and evaluate the more general conditions which led to attaining management goals. Overall, the cover of native plants increased for low-quality sites, and among the management practices considered, we found that burning most effectively enhanced the native prairie plant community and increased the dominance of native indicator species. Contrary to expectations, the results also suggest that grazing on sites that started in a poor condition were less likely to show improvements in the native plant community. Complementing AM with more traditional statistical analyses can help inform the iterative doubleloop learning phase of the AM framework. AM has many challenges, but we demonstrate that multi-agency AM can be successful. Keys to success include starting the project with an in-person, in-depth workshop; standardized protocols and a centralized database; a core project team with multi-disciplinary backgrounds; stability in project leadership; and regular communication to meet annual deadlines.

Minnesota, North Dakota, South Dakota↗
USGS2020

Fish predation on a landscape scale

Predator–prey dynamics can have landscape-level impacts on ecosystems, and yet, spatial patterns and environmental predictors of predator–prey dynamics are often investigated at discrete locations, limiting our understanding of the broader impacts. At these broader scales, landscapes often contain multiple complex and heterogeneous habitats, requiring a spatially representative sampling design. This challenge is especially pronounced in California’s Sacramento–San Joaquin River Delta, where managers require information on the landscape-scale impacts of non-native fish predators on multiple imperiled native prey fish populations. We quantified relative predation risk in the southern half of the Delta (South Delta) in 2017 using floating baited tethers that record the exact time and location of predation events. We selected 20 study sites using a generalized random tessellation stratified survey design, which allowed us to infer relationships between key environmental covariates and predation across a broader spatial scale than previous studies. Covariates included distance-to-nearest predators, water temperature, turbidity, depth, bottom slope, bottom roughness, water velocity, and distance-to-nearest riverbank and nearest aquatic vegetation bed. Model selection determined the covariates that best predicted relative predation risk: water temperature, time of day, mean predator distance, and river bottom roughness. Using this model, we estimated predation risk for the South Delta landscape at a 1-day and 1-km resolution. This effort identified hot spots of predation risk and allowed us to generate predicted survival for migrating fish transiting the South Delta. This methodology can be applied to other systems to evaluate spatio-temporal dynamics in predation risk, and their biotic and abiotic predictors.

California↗