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At least 235 records · Page 13Linked to original sources
USGS2022

Habitat management for stopover and breeding songbird communities along rights-of-way in forest-dominated landscapes

The proliferation of energy rights-of-way (pipelines and powerlines; ROWs) in the central Appalachian region has prompted wildlife management agencies to consider ways to use these features to manage and conserve at-risk songbird species. However, little empirical evidence exists regarding best management strategies to enhance habitat surrounding ROWs for the songbird community during stopover or breeding periods. We used a before-after-control-impact design to study cut-back border (linear tree cuttings along abrupt forest edges) harvest width (15 m, 30 m, and 45 m wide into the forest) and harvest intensity (14 m 2 /ha and 4.5 m 2 /ha basal area retention) prescriptions along ROWs and assessed their effects on mature forest and young forest songbird species and avian guilds (forest gap habitat, forest interior habitat, young forest habitat, and species of regional conservation priority) up to two years after treatment throughout West Virginia. Species richness during the spring stopover period initially decreased at one-year post-treatment but returned to pre-treatment levels by two-year post-treatment. Breeding season responses to cut-back border treatments varied across harvest width, harvest intensity, and time, but all responses of focal species abundance and guild richness were neutral or positive. Cut-back border harvest intensity had a stronger influence (i.e., more positive responses) than harvest width on breeding focal species abundances and guild richness. For harvest intensity, the more intense, 4.5 m 2 /ha retention treatment had a stronger influence (i.e., more positive responses) than the less intense, 14 m 2 /ha retention treatment. For harvest width, the narrowest treatment (15-m wide) had the strongest influence (i.e., more positive responses) of all width treatments, followed by the widest (45-m wide treatment) with the least influence from the 30-m wide treatment. Abundances and richness increased from pre-treatment to two-year post-treatment across all species and guilds that exhibited a response. These results suggest that cut-back borders increase breeding season habitat suitability along ROWs for the mature forest and young forest songbird community as well as for species of regional conservation priority in the short-term. These findings can aid development of management guidelines for the forest songbird community along abrupt forest edges of man-made habitat features in forest-dominated landscapes.

West Virginia↗
USGS2022

Plant effects on and response to soil microbes in native and non-native Phragmites australis

Plant–soil feedbacks (PSFs) mediate plant community dynamics and may plausibly facilitate plant invasions. Microbially mediated PSFs are defined by plant effects on soil microbes and subsequent changes in plant performance (responses), both positive and negative. For microbial interactions to benefit invasive plants disproportionately, native and invasive plants must either (1) have different effects on and responses to soil microbial communities or (2) only respond differently to similar microbial communities. In other words, invasive plants do not need to cultivate different microbial communities than natives if they respond differently to them. However, effects and responses are not often explored separately, making it difficult to determine the underlying causes of performance differences. We performed a reciprocal-transplant PSF experiment with multiple microbial inhibition treatments to determine how native and non-native lineages of Phragmites australis affect and respond to soil bacteria, fungi, and oomycetes. Non-native Phragmites is a large, fast-growing, cosmopolitan invasive plant, whereas the North American native variety is comparatively smaller, slower growing, and typically considered a desirable wetland plant. We identified the effects of each plant lineage on soil microbes using DNA meta-barcoding and linked plant responses to microbial communities. Both Phragmites lineages displayed equally weak, insignificant PSFs. We found evidence of slight differential effects on microbial community composition, but no significant differential plant responses. Soils conditioned by each lineage differed only slightly in bacterial community composition, but not in fungal composition. Additionally, native and non-native Phragmites lineages did not significantly differ in their response to similar soil microbial communities. Neither lineage appreciably differed when plant biomass was compared between those grown in sterile and live soils. Targeted microbial inhibitor treatments revealed both lineages were negatively impacted by soil bacteria, but the negative response was stronger in non-native Phragmites . These observations were opposite of expectations from invasion theory and imply that the success of non-native Phragmites , relative to the native lineage, does not result from its interaction with soil microorganisms. More broadly, quantifying plant effects on, and responses to soil microbes separately provides detailed and nuanced insight into plant-microbial interactions and their role in invasions, which could inform management outcomes for invasive plants.

Ecological Applications↗
USGS2022

Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata . We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

New Hampshire↗
USGS2022

Does large dam removal restore downstream riparian vegetation diversity? Testing predictions on the Elwha River, Washington, USA

Large dams and their removal can profoundly affect riparian ecosystems by altering flow and sediment regimes, hydrochory, and landform dynamics, yet few studies have documented these effects on downstream plant communities. Ecological theory and empirical results suggest that by altering disturbance regimes, reducing hydrochory, and shifting communities to later successional stages, dams reduce downstream plant diversity. Dam removal could reverse these processes, but the release of large volumes of sediment could have unexpected, transient effects. Two large dams were removed on the Elwha River in Washington State, USA, from 2011-2014, representing an unprecedented opportunity to study large dam removal effects on riparian plant communities. Our research objectives were to determine: 1) whether the Elwha River dams were associated with lower downstream plant diversity and altered species composition across riparian landforms pre-dam removal, and 2) whether dam removal has begun to restore downstream diversity and composition. To address these objectives, we compared plant species richness and community composition in river segments above, below, and between the two dams. Plant communities were sampled twice before (2005 and 2010) and four times after (2013, 2014, 2016, and 2017) the start of dam removal, with 2013 and 2014 sampled while the upstream dam removal was ongoing. Prior to dam removal, native species richness was 41% lower below dams compared to the upstream segment; six years after dam removal began, it increased ~31% between the dams, while nonnative species richness and cover were not apparently affected by dams or their removal. Deposition caused by large volumes of released reservoir sediment had mixed effects on native species richness (increased on floodplains, decreased elsewhere) in the lowest river segment. Plant community composition was also different downstream from dams compared to the upstream reference, and has changed in downstream floodplains and bars since dam removal. Long-term, we expect that diversity will continue to increase in downstream river segments. Our results provide evidence that 1) large dams reduce downstream native plant diversity, 2) dam removal may restore it, and 3) given the natural dynamics of riparian vegetation, long-term, multi-year before-and-after-monitoring is essential for understanding dam removal effects.

Washington↗
USGS2022

The wildland-urban interface in the United States based on 125 million building locations

The wildland-urban interface (WUI) is the focus of many important land management issues, such as wildfire, habitat fragmentation, invasive species, and human-wildlife conflicts. Wildfire is an especially critical issue, because housing growth in the WUI increases wildfire ignitions and the number of homes at risk. Identifying the WUI is important for assessing and mitigating impacts of development on wildlands and for protecting homes from natural hazards, but data on housing development for large areas are often coarse. We created new WUI maps for the conterminous U.S. based on 125 million individual building locations, offering higher spatial precision compared to existing maps based on U.S. census housing data. Building point locations were based on a building footprint dataset from Microsoft®. We classified WUI across the conterminous U.S. at 30-m resolution using a circular neighborhood mapping algorithm with a variable radius to determine thresholds of housing density and vegetation cover. We used our maps to (1) determine the total area of the WUI and number of buildings included, (2) assess the sensitivity of WUI area included and spatial pattern of WUI maps to choice of neighborhood size, (3) assess regional differences between building-based WUI maps and census-based WUI maps, and (4) determine how building location accuracy affected WUI map accuracy. Our building-based WUI maps identified 5.6% – 18.8% of the conterminous U.S. as being in the WUI, with larger neighborhoods increasing WUI area but excluding isolated building clusters. Building-based maps identified more WUI area relative to census-based maps for all but the smallest neighborhoods, particularly in the north-central states, and large differences were attributable to high numbers of non-housing structures in rural areas. Overall WUI classification accuracy was 98.0%. For wildfire risk mapping and for general purposes, WUI maps based on the 500-m neighborhood represent the original Federal Register definition of the WUI; these maps include clusters of buildings in and adjacent to wildlands and exclude remote, isolated buildings. Our approach for mapping the WUI offers flexibility and high spatial detail, and can be widely applied to take advantage of the growing availability of high-resolution building footprint datasets and classification methods.

Conterminous United States↗
USGS2022

Eyes on the herd: Quantifying ungulate density from satellite, unmanned aerial systems, and GPScollar data

Novel approaches to quantifying density and distributions could help biologists adaptively manage wildlife populations, particularly if methods are accurate, consistent, cost-effective, rapid, and sensitive to change. Such approaches may also improve research on interactions between density and processes of interest, such as disease transmission across multiple populations. We assess how satellite imagery, unmanned aerial system (UAS) imagery, and Global Positioning System (GPS) collar data vary in characterizing elk density, distribution, and count patterns across times with and without supplemental feeding at the National Elk Refuge (NER) in the US state of Wyoming. We also present the first comparison of satellite imagery data with traditional counts for ungulates in a temperate system. We further evaluate seven different aggregation metrics to identify the most consistent and sensitive metrics for comparing density and distribution across time and populations. All three data sources detected higher densities and aggregation locations of elk during supplemental feeding than non-feeding at the NER. Kernel density estimates (KDEs), KDE polygon areas, and the first quantile of interelk distances detected differences with the highest sensitivity and were most highly correlated across data sources. Both UAS and satellite imagery provide snapshots of density and distribution patterns of most animals in the area at lower cost than GPS collars. While satellite-based counts were lower than traditional counts, aggregation metrics matched those from UAS and GPS data sources when animals appeared in high contrast to the landscape, including brown elk against new snow in open areas. UAS counts of elk were similar to traditional ground-based counts on feed grounds and are the best data source for assessing changes in small spatial extents. Satellite, UAS, or GPS data can provide appropriate data for assessing density and changes in density from adaptive management actions. For the NER, where high elk densities are beneath controlled airspace, GPS collar data will be most useful for evaluating how management actions, including changes in the dates of supplemental feeding, influence elk density and aggregation across large spatial extents. Using consistent and sensitive measures of density may improve research on the drivers and effects of density within and across a wide range of species.

Wyoming↗
USGS2022

Precision and bias of spatial capture–recapture estimates: A multi-site, multi-year Utah black bear case study

Spatial capture–recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence the precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical data sets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear ( Ursus americanus ) capture–recapture data set, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 to 74.33 bears/100 km 2 . Increasing total detections decreased the uncertainty of density estimates, whereas an increasing number of total recaptures and individuals with recaptures decreased the uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 coefficient of variation [CV]). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when <30% of recaptured individuals were spatially recaptured, density estimates were unreliable and ranged widely, in some cases to >3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture–recapture data sets that can provide an early signal of the need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.

Utah↗
USGS2022

A comparison of monitoring designs to assess wildlife community parameters across spatial scales

Dedicated long-term monitoring at appropriate spatial and temporal scales is necessary to understand biodiversity losses and develop effective conservation plans. Wildlife monitoring is often achieved by obtaining data at a combination of spatial scales, ranging from local to broad, to understand the status, trends, and drivers of individual species or whole communities and their dynamics. However, limited resources for monitoring necessitates tradeoffs in the scope and scale of data collection. Careful consideration of the spatial and temporal allocation of finite sampling effort is crucial for monitoring programs that span multiple spatial scales. Here we evaluate the ability of five monitoring designs - stratified random, weighted effort, indicator unit, rotating panel, and split panel - to recover parameter values that describe the status (occupancy), trends (change in occupancy), and drivers (spatially-varying covariate and an autologistic term) of wildlife communities at two spatial scales. Using an amphibian monitoring program that spans a network of U.S. National Parks as a motivating example, we conducted a simulation study for a regional community occupancy sampling program to compare the monitoring designs across varying levels of sampling effort (ranging from 10 to 50%). We found that the stratified random design outperformed the other designs for most parameters of interest at both scales, and was thus generally preferable in balancing the estimation of status, trends, and drivers across scales. However, we found that other designs had improved performance in specific situations. For example, the rotating panel design performed best at estimating spatial drivers at a regional level. Thus, our results highlight the nuanced scenarios in which various design strategies may be preferred, and offer guidance as to how managers can balance common tradeoffs in large-scale and long-term monitoring programs in terms of the specific knowledge gained. Monitoring designs that improve accuracy in parameter estimates are needed to guide conservation policy and management decisions in the face of broad-scaled environmental challenges, but the preferred design is sensitive to the specific objectives of a monitoring program.

Ecological Applications↗
USGS2022

Fire-driven vegetation type conversion in Southern California

One consequence of global change causing widespread concern is the possibility of ecosystem conversions from one type to another. A classic example of this is vegetation type conversion (VTC) from native woody shrublands to invasive annual grasslands in the biodiversity hotspot of Southern California. Although the significance of this problem is well recognized, understanding where, how much, and why this change is occurring remains elusive owing to differences in results from studies conducted using different methods, spatial extents, and scales. Disagreement has arisen particularly over the relative importance of short-interval fires in driving these changes. Chronosequence approaches that use space for time to estimate changes have produced different results than studies of changes at a site over time. Here we calculated the percentage woody and herbaceous cover across Southern California using air photos from ~1950 to 2019. We assessed the extent of woody cover change and the relative importance of fire history, topography, soil moisture, and distance to human infrastructure in explaining change across a hierarchy of spatial extents and regions. We found substantial net decline in woody cover and expansion of herbaceous vegetation across all regions, but the most dramatic changes occurred in the northern interior and southern coastal areas. Variables related to frequent, short-interval fire were consistently top ranked as the explanation for shrub to grassland type conversion, but low soil moisture and topographic complexity were also strong correlates. Despite the consistent importance of fire, there was substantial geographical variation in the relative importance of drivers, and these differences resulted in different mapped predictions of VTC. This geographical variation is important to recognize for management decision-making and, in addition to differences in methodological design, may also partly explain differences in previous study results. The overwhelming importance of short-interval fire has management implications. It suggests that actions should be directed away from imposing fires to preventing fires. Prevention can be controlled through management actions that limit ignitions, fire spread, and the damage sustained in areas that do burn. This study also demonstrates significant potential for changing fire regimes to drive large-scale, abrupt ecological change.

California↗
USGS2022

Life and death in a dynamic environment: Invasive trout, floods, and intraspecific drivers of translocated populations

Understanding the relative strengths of intrinsic and extrinsic factors regulating populations is a long-standing focus of ecology and critical to advancing conservation programs for imperiled species. Conservation could benefit from an increased understanding of factors influencing vital rates (somatic growth, recruitment, survival) in small, translocated populations, which is lacking owing to difficulties in long-term monitoring of rare species. Translocations, here defined as the transfer of wild-captured individuals from source populations to new habitats, are widely used for species conservation, but outcomes are often minimally monitored, and translocations that are monitored often fail. To improve our understanding of how translocated populations respond to environmental variation, we developed and tested hypotheses related to intrinsic (density dependent) and extrinsic (introduced rainbow trout Oncorhynchus mykiss , stream flow and temperature regime) causes of vital rate variation in endangered humpback chub ( Gila cypha ) populations translocated to Colorado River tributaries in the Grand Canyon (GC), USA. Using biannual recapture data from translocated populations over 10 years, we tested hypotheses related to seasonal somatic growth, and recruitment and population growth rates with linear mixed-effects models and temporal symmetry mark–recapture models. We combined data from recaptures and resights of dispersed fish (both physical captures and continuously recorded antenna detections) from throughout GC to test survival hypotheses, while accounting for site fidelity, using joint live-recapture/live-resight models. While recruitment only occurred in one site, which also drove population growth (relative to survival), evidence supported hypotheses related to density dependence in growth, survival, and recruitment, and somatic growth and recruitment were further limited by introduced trout. Mixed-effects models explained between 67% and 86% of the variation in somatic growth, which showed increased growth rates with greater flood-pulse frequency during monsoon season. Monthly survival was 0.56–0.99 and 0.80–0.99 in the two populations, with lower survival during periods of higher intraspecific abundance and low flood frequency. Our results suggest translocations can contribute toward the recovery of large-river fishes, but continued suppression of invasive fishes to enhance recruitment may be required to ensure population resilience. Furthermore, we demonstrate the importance of flooding to population demographics in food-depauperate, dynamic, invaded systems.

Arizona↗
USGS2022

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter datasets versus pseudo-absence locations during migratory periods, and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and post-breeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations, when compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings, and thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach for integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Ecological Applications↗
USGS2022

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry

We use the Multiple Element Limitation (MEL) model to examine responses of twelve ecosystems to elevated carbon dioxide (CO 2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO 2 , warming, and decreased precipitation combined because higher water-use efficiency with elevated CO 2 and higher fertility with warming compensate for responses to drought. Response to elevated CO 2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO 2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO 2 and climate change.

Ecological Applications↗
USGS2022

Response of riparian vegetation to short- and long-term hydrologic variation

Increasing demand for river water now conflicts with an increasing desire to maintain riparian ecosystems. Efficiently managing river flows for riparian vegetation requires an understanding of the time scale of flow effects, but this information is limited by the absence of long-term studies of vegetation change in response to flow variation. To investigate the influence of short- and long-term flow variability and dam operation on riparian vegetation, we determined the occurrence of 107 plant species in 133 permanent plots of known inundating discharge along the Gunnison River in Colorado on five different occasions between 1990 and 2013. Individual species moved up and down the gradient of inundating discharge coincident with increases and decreases in mean annual flow, and the correlations between flow and species occurrence were strongest when flows were weighted by time before vegetation sampling with a median half-life of 1.5 years. Some tall, rhizomatous, perennial species, however, responded to flows on a longer time scale. Logistic regression of species occurrence showed a significant relation with inundation duration for 70 out of 107 species. Plot species richness and total vegetative cover decreased in association with desiccation at low inundation durations and with fluvial disturbance at high inundation durations. Within-plot similarity in species occurrence between years decreased strongly with increasing inundation duration. Moderate inundation durations were dominated by tall, rhizomatous, perennial herbs, including invasive Phalaris arundinacea (reed canary grass). Over the 23-year study period, species richness declined, and the proportion of rhizomatous perennials increased, consistent with the hypothesis that decreases in flow peaks and increases in low flows caused by flow regulation have decreased establishment opportunities for disturbance-dependent species. In summary, annual-scale changes in vegetation were strongly influenced by flow variation, and decadal-scale changes were influenced by decreases in fluvial disturbance from upstream flow regulation beginning decades prior to the onset of this study.

Colorado↗
USGS2022

The role of microtopography and resident species in post-disturbance recovery of arid habitats in Hawaiʻi

Habitat-suitability indices (HSI) have been employed in restoration to identify optimal sites for planting native species. Often, HSI are based on abiotic variables and do not include biotic interactions, even though similar abiotic conditions can favor both native and nonnative species. Biotic interactions such as competition may be especially important in invader-dominated habitats because invasive species often have fast growth rates and can exploit resources quickly. In this study, we test the utility of an HSI of microtopography derived from airborne LiDAR to predict post-disturbance recovery and native planting success in native shrub-dominated and nonnative, invasive grass-dominated dryland habitats in Hawaiʻi. The HSI uses high-resolution digital terrain models to classify sites' microtopography as high, medium, or low suitability, based on wind exposure and topographic position. We used a split-plot before-after-control-impact design to implement a disturbance experiment within native shrub ( Dodonaea viscosa ) and nonnative, invasive grass ( Cenchrus clandestinus )-dominated ecosystems across three microtopography categories. In contrast to previous studies using the same HSI, we found that microtopography was a poor predictor of pre-disturbance conditions for soil nutrients, organic matter content, or foliar C:N, within both Dodonaea and Cenchrus vegetation types. In invader-dominated Cenchrus plots, microtopography helped predict cover, but not as expected (i.e., highest cover would be in high-suitability plots): D. viscosa had the greatest cover in low-suitability and C. clandestinus had the greatest cover in medium-suitability plots. Similarly, in native-dominated Dodonaea plots, microtopography was a poor predictor of D. viscosa , C. clandestinus , and total plant cover. Although we found some evidence that microtopography helped inform post-disturbance plant recovery of D. viscosa and total plant cover, vegetation type was a more important predictor. Important for considering the success of plantings, percent cover of D. viscosa decreased while percent cover of C. clandestinus increased within both vegetation types 20 months after disturbance. Our results are evidence that HSIs based on topographic features may prove most useful for choosing planting sites in harsh habitats or those already dominated by native species. In more productive habitats, competition from resident species may offset any benefits gained from “better” suitability sites.

Hawaii↗
USGS2022

Modeling impacts of drought-induced salinity intrusion on carbon dynamics in tidal freshwater forested wetlands

Tidal freshwater forested wetlands (TFFW) provide critical ecosystem services including essential habitat for a variety of wildlife species and significant carbon sinks for atmospheric carbon dioxide. However, large uncertainties remain concerning the impacts of climate change on the magnitude and variability of carbon fluxes and storage across a range of TFFW. In this study, we developed a process-driven Tidal Freshwater Wetlands DeNitrification-DeComposition model (TFW-DNDC) that has integrated new features, such as soil salinity effects on plant productivity and soil organic matter decomposition to explore carbon dynamics in TFFW in response to drought-induced saltwater intrusion. Eight sites along the floodplains of the Waccamaw River (USA) and the Savannah River (USA) were selected to represent TFFW transition from healthy to moderately and highly salt-impacted forests, and eventually to oligohaline marshes. TFW-DNDC was calibrated and validated using field observed annual litterfall, stem growth, root growth, soil heterotrophic respiration and soil organic carbon storage. Analyses indicate that plant productivity and soil carbon sequestration in TFFW could change substantially in response to increased soil porewater salinity and reduced soil water table due to drought, but in interactive ways dependent on the river simulated. Such responses are variable due to non-linear relationships between carbon cycling processes and environmental drivers. Plant productivity, plant respiration, soil organic carbon sequestration rate and storage in the highly salt-impacted forest sites decreased significantly under drought conditions compared to normal conditions. Considering the high likelihood of healthy and moderately salt-impacted forests becoming highly salt-impacted forests under future climate change and sea-level rise, it is very likely that TFFW will lose their capacity as carbon sinks without up-slope migration.

Georgia, South Carolina↗
USGS2022

Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam

The brown treesnake (BTS) ( Boiga irregularis ) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird's perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan's birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan's forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek ( Todiramphus cinnamominus ) and Såli ( Aplonis opaca ), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (>0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts.

Ecological Applications↗
USGS2022

Range-wide sources of variation in reproductive rates of northern spotted owls

We conducted a range-wide investigation of the dynamics of site level reproductive rate of northern spotted owls using survey data from 11 study areas across the sub-species geographic range collected during 1993–2018. Our analytical approach accounted for imperfect detection of owl pairs and misclassification of successful reproduction (i.e., at least one young fledged) and contributed further insights into northern spotted owl population ecology and dynamics. Both nondetection and state misclassification were important, especially because factors affecting these sources of error also affected focal ecological parameters. Annual probabilities of site occupancy were greatest at sites with successful reproduction in the previous year and lowest for sites not occupied by a pair in the previous year. Site-specific occupancy transition probabilities declined over time and were negatively affected by barred owl presence. Overall, the site-specific probability of successful reproduction showed substantial year-to-year fluctuations and was similar for occupied sites that did and did not experience successful reproduction the previous year. Site-specific probabilities for successful reproduction were very small for sites that were unoccupied the previous year. Barred owl presence negatively affected the probability of successful reproduction by northern spotted owls in Washington and California, as predicted, but the effect in Oregon was mixed. The proportions of sites occupied by northern spotted owl pairs showed steep, near-monotonic declines over the study period, with all study areas showing the lowest observed levels of occupancy to date. If trends continue it is likely that northern spotted owls will become extirpated throughout large portions of their range in the coming decades.

Ecological Applications↗
USGS2022

Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics

Sea ice loss is fundamentally altering the Arctic marine environment. Yet there is a paucity of data on the adaptability of food webs to ecosystem change, including predator-prey interactions. Polar bears ( Ursus maritimus ) are an important subsistence resource for Indigenous people and an apex predator that relies entirely on the under-ice food web to meet their energy needs. Here, we assessed whether polar bears maintained dietary energy density by prey switching in response to spatial-temporal variation in prey availability. We compared the macronutrient composition of diets inferred from stable carbon and nitrogen isotopes in polar bear guard hair (primarily representing summer/fall diet) during periods when bears had low and high survival 2004-2016, between bears that summered on land versus pack ice, and between bears occupying different regions of the Alaskan and Canadian Beaufort Sea. Polar bears consumed diets with lower energy density during periods of low survival suggesting that concurrent increased dietary proportions of beluga whales ( Delphinapterus leucas ) did not offset reduced proportions of ringed seals ( Pusa hispida ). Diets with the lowest energy density and proportions from ringed seal blubber were consumed by bears in the western Beaufort Sea (Alaska) during a period when polar bear abundance declined. Intake required to meet energy requirements of an average free-ranging adult female polar bear was 2.1 kg/day on diets consumed during years with high survival but rose to 3.0 kg/day when survival was low. Although bears that summered onshore in the Alaskan Beaufort Sea had higher fat diets than bears that summered on the pack ice, access to the remains of subsistence-harvested bowhead whales ( Balaena mysticetus ) contributed little to improving diet energy density. Because most bears in this region remain with the sea ice year-round, prey-switching and consumption of whale carcasses onshore appear insufficient to augment diets when availability of their primary prey, ringed seals, is reduced. Our results show that a strong predator-prey relationship between polar bears and ringed seals continues in the Beaufort Sea. The method of estimating dietary blubber using predator hair, demonstrated here, provides a new metric to monitor predator-prey relationships that affect individual health and population demographics.

Ecological Applications↗