Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Ecological Applications”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources
USGS2021

Improving the ability of a BACI design to detect impacts within a kelp‐forest community

Distinguishing between human impacts and natural variation in abundance remains difficult because most species exhibit complex patterns of variation in space and time. When ecological monitoring data are available, a before‐after‐control‐impact (BACI) analysis can control natural spatial and temporal variation to better identify an impact and estimate its magnitude. However, populations with limited distributions and confounding spatial‐temporal dynamics can violate core assumptions of BACI‐type designs. In this study, we assessed how such properties affect the potential to identify impacts. Specifically, we quantified the conditions under which BACI analyses correctly (or incorrectly) identified simulated anthropogenic impacts in a spatially and temporally replicated data set of fish, macroalgal, and invertebrate species found on nearshore subtidal reefs in southern California, USA. We found BACI failed to assess very localized impacts, and had low power but high precision when assessing region‐wide impacts. Power was highest for severe impacts of moderate spatial scale, and impacts were most easily detected in species with stable, widely distributed populations. Serial autocorrelation in the data greatly inflated false impact detection rates, and could be partly controlled for statistically, while spatial synchrony in dynamics had no consistent effect on power or false detection rates. Unfortunately, species that offer high power to detect real impacts were also more likely to detect impacts where none had occurred. However, considering power and false detection rates together can identify promising indicator species, and collectively analyzing data for similar species improved the net ability to assess impacts. These insights set expectations for the sizes and severities of impacts that BACI analyses can detect in real systems, point to the importance of serial autocorrelation (but not of spatial synchrony), and indicate how to choose the species, and groups of species, that can best identify impacts.

Ecological Applications↗
USGS2021

Migrating whooping cranes avoid wind-energy infrastructure when selecting stopover habitat

Electricity generation from renewable-energy sources has increased dramatically worldwide in recent decades. Risks associated with wind-energy infrastructure are not well understood for endangered whooping cranes or other vulnerable crane populations. From 2010 to 2016, we monitored 57 whooping cranes with remote-telemetry devices in the United States Great Plains to determine potential changes in migration distribution (i.e., avoidance) caused by presence of wind-energy infrastructure. During our study, the number of wind towers tripled in the whooping crane migration corridor and quadrupled in the corridor’s center. Median distance of whooping crane locations from nearest wind tower was 52.1 km, and 99% of locations were >4.3 km from wind towers. A habitat selection analysis revealed that whooping cranes used areas ≤5.0 km (95% CI = 4.8–5.4) from towers less than expected (i.e., zone of influence) and that whooping cranes were 20 times (95% CI: 14–64) more likely to use areas outside compared to adjacent to towers. Eighty percent of whooping crane locations and 20% of wind towers were located in areas with the highest relative probability of whooping crane use based on our model, which comprised 20% of the study area. Whooping cranes selected for these places, whereas developers constructed wind infrastructure at random relative to desirable whooping crane habitat. As of early 2020, 4.6% of the study area and 5.0% of the highest-selected whooping crane habitat were within the collective zone of influence. The affected area equates to habitat loss ascribed to wind-energy infrastructure; losses from other disturbances have not been quantified. Continued growth of the whooping crane population during this period of wind infrastructure construction suggests no immediate population-level consequences. Chronic or lag effects of habitat loss are unknown but possible for long-lived species. Preferentially constructing future wind infrastructure outside of the migration corridor or inside of the corridor at sites with low probability of whooping crane use would allow for continued wind-energy development in the Great Plains with minimal additional risk to highly selected habitat that supports recovery of this endangered species.

Kansas, Montana, Nebraska, North Dakota, Oklahoma,↗
USGS2021

Optimal allocation of law enforcement patrol effort to mitigate poaching activities

Poaching is a global problem causing the decline of species worldwide. Optimizing the efficiency of ranger patrols to deter poaching activity at the lowest possible cost is crucial for protecting species with limited resources. We applied decision analysis and spatial optimization algorithms to allocate efforts of ranger patrols throughout a national park. Our objective was to mitigate poaching activity at or below management risk targets for the lowest monetary cost. We examined this trade‐off by constructing a Pareto efficiency frontier using integer linear programming. We used data from a ranger‐based monitoring program in Nyungwe National Park, Rwanda. Our measure of poaching risk is based on dynamic occupancy models that account for imperfect detection of poaching activities. We found that in order to achieve a 5% reduction in poaching risk, 622 ranger patrol events (each corresponding to patrolling 1‐km 2 sites) were needed within a year at a cost of US$49,760. In order to attain a 60% reduction in poaching risk, 15,560 patrol events were needed at a cost of US \$ 1,244,800. We evaluated the trade‐off between patrol cost and poaching risk based on our model by constructing a Pareto efficiency frontier and park managers found the solution for a 50% risk reduction to be a practical trade‐off based on funding constraints (comparable to recent years) and the diminishing returns between risk mitigation and cost. This expected reduction in risk required 8,558 patrol events per year at a cost of US \$ 684,640. Our results suggest that optimal solutions could increase efficiency compared to the actual effort allocations from 2006 to 2016 in Nyungwe National Park (e.g., risk reductions of ~30% under recent budgets compared to ~50% reduction in risk under the optimal strategy). The modeling framework in this study took into account imperfect detection of poaching risk as well as the directional and conditional nature of ranger patrol events given the spatial adjacency relationships of neighboring sites and access points. Our analyses can help to improve the efficiency of ranger patrols, and the modeling framework can be broadly applied to other spatial conservation planning problems with conditional, multilevel, site selection.

Nyungwe National Park↗
USGS2021

Large-scale variation in wave attenuation of oyster reef living shorelines and the influence of inundation duration

One of the paramount goals of oyster reef living shorelines is to achieve sustained and adaptive coastal protection, which requires meeting ecological (i.e., develop a self-sustaining oyster population) and engineering (i.e., provide coastal defense) targets. In a large-scale comparison along the Atlantic and Gulf coasts of the United States, the efficacy of various designs of oyster reef living shorelines at providing wave attenuation was evaluated accounting for the ecological limitations of oysters with regard to inundation duration. A critical threshold for intertidal oyster reef establishment is 50% inundation duration. Living shorelines that spent less than one-half of the time (<50%) inundated were not considered suitable habitat for oysters, however, were effective at wave attenuation (68% reduction in wave height). Reefs that experienced >50% inundation were considered suitable habitat for oysters, but wave attenuation was similar to controls (no reef; ~5% reduction in wave height). Many of the oyster reef living shoreline approaches therefore failed to optimize the ecological and engineering goals. In both inundation regimes, wave transmission decreased with an increasing freeboard (difference between reef crest elevation and water level), supporting its importance in the wave attenuation capacity of oyster reef living shorelines. However, given that the reef crest elevation (and thus freeboard) should be determined by the inundation duration requirements of oysters, research needs to be refocused on understanding the implications of other reef parameters (e.g., width) for optimizing wave attenuation. A broader understanding of the reef characteristics and seascape contexts that result in effective coastal defense by oyster reefs is needed to inform appropriate design and implementation of oyster-based living shorelines globally.

Alabama, Florida, Louisiana, New Jersey, Virginia↗
USGS2021

Mapping the vulnerability of giant sequoias after extreme drought in California using remote sensing

Between 2012 and 2016, California suffered one of the most severe droughts on record. During this period Sequoiadendron giganteum (giant sequoias) in the Sequoia and Kings Canyon National Parks (SEKI), California, USA experienced canopy water content (CWC) loss, unprecedented foliage senescence, and, in a few cases, death. We present an assessment of the vulnerability of giant sequoia populations to droughts that is currently lacking and needed for management. We used a temporal trend of remotely sensed CWC obtained between 2015 and 2017, and recently georeferenced giant sequoia crowns to quantify the vulnerability of 7,408 individuals in 10 groves in the northern portion of SEKI. CWC is sensitive to changes in liquid water in tree canopies; therefore, it is a useful metric for quantifying the response of sequoia trees to drought. Temporal trends indicated that 9% of giant sequoias had a significant decline or consistently low CWC, suggesting these trees were likely operating at low photosynthetic capacity and potentially at high risk to drought stress. We also found that 20% of the giant sequoias had an increase or consistently high level of CWC, indicating these trees were at low risk to drought stress. These vulnerability categories were used in a random forest model with a combination of topographic, fire-related, and climate variables to generate high-resolution vulnerability risk maps. These maps show that higher risk is associated with lower elevation and higher climate water deficit. We also found that sequoias at higher elevations but located near meadows had higher vulnerability risk. These results and the vulnerability maps can identify vulnerable sequoias that may be difficult to save or locations of refugia to be protected, and thus may aid forest managers in preparation for future droughts.

California↗
USGS2021

Conspecific and congeneric interactions shape increasing rates of breeding dispersal of northern spotted owls

Breeding dispersal, the movement from one breeding territory to another, is rare for philopatric species that evolved within relatively stable environments, such as the old-growth coniferous forests of the Pacific Northwest. Although dispersal is not inherently maladaptive, the consequences of increased dispersal on population dynamics in populations whose historical dispersal rates are low could be significant, particularly for a declining species. We examined rates and possible causes of breeding dispersal based on a sample of 4,118 northern spotted owls ( Strix occidentalis caurina ) monitored in seven study areas over 28 yr, 1990–2017, in Oregon and Washington, USA. Using a multistate mark–resight analysis, we investigated the potential impacts of an emergent congeneric competitor (barred owl Strix varia ) and forest alteration (extrinsic factors), and social and individual conditions (intrinsic factors) on 408 successive and 1,372 nonsuccessive dispersal events between years. The annual probability of breeding dispersal increased for individual owls that had also dispersed in the previous year and decreased for owls on territories with historically high levels of reproduction. Intrinsic factors including pair status, prior reproductive success, and experience at a site, were also associated with breeding dispersal movements. The percent of monitored owls dispersing each year increased from ˜7% early in the study to ˜25% at the end of the study, which coincided with a rapid increase in numbers of invasive and competitively dominant barred owls. We suggest that the results presented here can inform spotted owl conservation efforts as we identify factors contributing to changing rates of demographic parameters including site fidelity and breeding dispersal. Our study further shows that increasing rates of breeding dispersal associated with population declines contribute to population instability and vulnerability of northern spotted owls to extinction, and the prognosis is unlikely to change unless active management interventions are undertaken.

California, Oregon, Washington↗
USGS2021

Mixed-conifer forest reference conditions for privately owned timberland in the southern Cascade Range

The overwhelming majority of information on historical forest conditions in western North America comes from public lands, which may provide an incomplete description of historical landscapes. In this study we made use of an archive containing extensive timber survey data collected in the early 1920s from privately owned forestland. These data covered over 50,000 ha and effectively represent a 19% sample of the entire area. The historical forest conditions reconstructed from these data fit the classic model of frequent-fire forests: large trees, low density, and pine-dominated. However, unlike other large-scale forest reconstructions, our study area exhibited relatively low overall variability in forest structure and composition across the historical landscape. Despite having low variability, our analyses revealed evidence of biophysical controls on tree density and pine fraction. Annual climatic variables most strongly explained the range in historical tree densities, whereas historical pine fraction was explained by a combination of topographic and climatic variables. Contemporary forest inventory data collected from both public and private lands within the same general area, albeit not a direct remeasurement, revealed substantial increases in tree density and greatly reduced pine fractions relative to historical conditions. Contemporary forests exhibited a far greater range in these conditions than what existed historically. These findings suggest that private forestland managed with multiaged silviculture may be similar to public forestland with respect to departure in forest structure and compositions from that of historical forests. However, there may be differences between management objectives that favor timber production, more typical on private lands, vs. those that favor restoration, increasingly supported on public lands.

California↗
USGS2021

Evaluation of camera trap-based abundance estimators for unmarked populations

Estimates of species abundance are critical to understand population processes and to assess and select management actions. However, capturing and marking individuals for abundance estimation, while providing robust information, can be economically and logistically prohibitive, particularly for species with cryptic behavior. Camera traps can be used to collect data at temporal and spatial scales necessary for estimating abundance, but the use of camera traps comes with limitations when target species are not uniquely identifiable (i.e., “unmarked”). Abundance estimation is particularly useful in the management of invasive species, with herpetofauna being recognized as some of the most pervasive and detrimental invasive vertebrate species. However, the use of camera traps for these taxa presents additional challenges with relevancy across multiple taxa. It is often necessary to use lures to attract animals in order to obtain sufficient observations, yet lure attraction can influence species’ landscape use and potentially induce bias in abundance estimators. We investigated these challenges and assessed the feasibility of obtaining reliable abundance estimates using camera-trapping data on a population of invasive brown treesnakes ( Boiga irregularis ) in Guam. Data were collected using camera traps in an enclosed area where snakes were subject to high-intensity capture–recapture effort, resulting in presumed abundance of 116 snakes (density = 23/ha). We then applied spatial count, random encounter and staying time, space to event, and instantaneous sampling estimators to photo-capture data to estimate abundance and compared estimates to our presumed abundance. We found that all estimators for unmarked populations performed poorly, with inaccurate or imprecise abundance estimates that limit their usefulness for management in this system. We further investigated the sensitivity of these estimators to the use of lures (i.e., violating the assumption that animal behavior is unchanged by sampling) and camera density in a simulation study. Increasing the effective distances of a lure (i.e., lure attraction) and camera density both resulted in biased abundance estimates. Each estimator rarely recovered truth or suffered from convergence issues. Our results indicate that, when limited to unmarked estimators and the use of lures, camera traps alone are unlikely to produce abundance estimates with utility for brown treesnake management.

Ecological Applications↗
USGS2021

Experimental evaluation of spatial capture–recapture study design

A principal challenge impeding strong inference in analyses of wild populations is the lack of robust and long-term data sets. Recent advancements in analytical tools used in wildlife science may increase our ability to integrate smaller data sets and enhance the statistical power of population estimates. One such advancement, the development of spatial capture–recapture (SCR) methods, explicitly accounts for differences in spatial study designs, making it possible to equate multiple study designs in one analysis. SCR has been shown to be robust to variation in design as long as minimal sampling guidance is adhered to. However, these expectations are based on simulation and have yet to be evaluated in wild populations. Here we conduct a rigorously designed field experiment by manipulating the arrangement of artificial cover objects (ACOs) used to collect data on red-backed salamanders ( Plethodon cinereus ) to empirically evaluate the effects of design configuration on inference made using SCR. Our results suggest that, using SCR, estimates of space use and detectability are sensitive to study design configuration, namely the spacing and extent of the array, and that caution is warranted when assigning biological interpretation to these parameters. However, estimates of population density remain robust to design except when the configuration of detectors grossly violates existing recommendations.

Massachusetts↗
USGS2021

Limited shifts in the distribution of migratory bird breeding habitat density in response to future changes in climate

Grasslands, and the depressional wetlands that exist throughout them, are endangered ecosystems that face both climate and land-use change pressures. Tens of millions of dollars are invested annually to manage the existing fragments of these ecosystems to serve as critical breeding habitat for migratory birds. The North American Prairie Pothole Region (PPR) is a region that contains millions of depressional wetlands that produce between 50 and 80% of the continent’s waterfowl population and. Previous modeling efforts suggested that climate change would result in a shift of suitable waterfowl breeding habitat from the central to the southeast portion of the PPR, an area where over half of the wetlands have been drained. The implications of these projections suggest a massive investment in wetland restoration in the southeastern PPR would be needed to sustain waterfowl populations at harvestable levels. We revisited these modeled results indicating how future climate may impact the distribution of waterfowl-breeding habitat using up-to-date climate model projections and a newly developed model for simulating prairie-pothole wetland hydrology. We also presented changes to the number of “May ponds,” a metric used by U.S. Fish and Wildlife Service to estimate waterfowl breeding populations and establish harvest regulations. Based on the output of 32 climate models and 2 emission scenarios, we found no evidence that the distribution of May ponds would shift in the future. However, our results projected a 17% decrease to 5% increase in May-pond numbers when comparing the most recent climate period (1989–2018) to the end of the 21st century (2070–2099). When combined, our results suggest areas in the PPR that that currently support the highest densities of intact wetland basins, and thus support the largest numbers of breeding-duck pairs, will likely also be the places most critical to maintaining continental waterfowl populations in an uncertain future.

Prairie Potholes Region↗
USGS2021

Evidence for widespread changes in the structure, composition, and fire regimes of western North American forests

Implementation of wildfire- and climate-adaptation strategies in seasonally dry forests of western North America is impeded by numerous constraints and uncertainties. After more than a century of resource and land use change, some question the need for proactive management, particularly given novel social, ecological, and climatic conditions. To address this question, we first provide a framework for assessing changes in landscape conditions and fire regimes. Using this framework, we then evaluate evidence of change and lack of change in contemporary conditions following more than a century of fire exclusion. The cumulative results of more than a century of research document a persistent and substantial fire deficit and widespread alterations to the ecological structures and functions maintained by active fire regimes, i.e., those uninterrupted by a century or more of fire exclusion. These changes are not necessarily apparent at all spatial scales or in all dimensions of fire regimes and forest and nonforest conditions. Nonetheless, loss of the once abundant influence of low- and moderate-severity fires suggests that while some ecosystems within these landscapes may not be directly altered by fire exclusion, even the least fire-prone among them may be affected by alteration of the surrounding landscape and, consequently, ecosystem functions. Vegetation spatial patterns in fire-excluded forested landscapes no longer reflect the heterogeneity maintained by interacting fires of active fire regimes. Live and dead vegetation (surface and canopy fuels) is generally more abundant and continuous than before European colonization. As a result, current conditions are more vulnerable to the direct and indirect effects of seasonal and episodic increases in fire and drought, especially under a rapidly warming climate. Long-term fire exclusion and contemporaneous social-ecological influences continue to extensively modify seasonally dry forested landscapes. Management that realigns or adapts fire-excluded conditions to seasonal and episodic increases in fire and drought can moderate ecosystem transitions as forests and human communities adapt to changing climatic and disturbance regimes. As adaptation strategies are developed, evaluated, and implemented, objective scientific evaluation of ongoing research and monitoring can aid differentiation between warranted and unwarranted uncertainties.

Ecological Applications↗
USGS2021

Adapting western North American forests to climate change and wildfires: Ten common questions

We review science-based adaptation strategies for western North American (wNA) forests that include restoring active fire regimes and fostering resilient structure and composition of forested landscapes. As part of the review, we address common questions associated with climate adaptation and realignment treatments that run counter to a broad consensus in the literature. These include the following: (1) Are the effects of fire exclusion overstated? If so, are treatments unwarranted and even counterproductive? (2) Is forest thinning alone sufficient to mitigate wildfire hazard? (3) Can forest thinning and prescribed burning solve the problem? (4) Should active forest management, including forest thinning, be concentrated in the wildland urban interface (WUI)? (5) Can wildfires on their own do the work of fuel treatments? (6) Is the primary objective of fuel reduction treatments to assist in future firefighting response and containment? (7) Do fuel treatments work under extreme fire weather? (8) Is the scale of the problem too great? Can we ever catch up? (9) Will planting more trees mitigate climate change in wNA forests? And (10) is post-fire management needed or even ecologically justified? Based on our review of the scientific evidence, a range of proactive management actions are justified and necessary to keep pace with changing climatic and wildfire regimes and declining forest heterogeneity after severe wildfires. Science-based adaptation options include the use of managed wildfire, prescribed burning, and coupled mechanical thinning and prescribed burning as is consistent with land management allocations and forest conditions. Although some current models of fire management in wNA are averse to short-term risks and uncertainties, the long-term environmental, social, and cultural consequences of wildfire management primarily grounded in fire suppression are well documented, highlighting an urgency to invest in intentional forest management and restoration of active fire regimes.

Ecological Applications↗
USGS2021

Demographic risk assessment for a harvested species threatened by climate change: Polar bears in the Chukchi Sea

Climate change threatens global biodiversity. Many species vulnerable to climate change are important to humans for nutritional, cultural, and economic reasons. Polar bears Ursus maritimus are threatened by sea-ice loss and represent a subsistence resource for Indigenous people. We applied a novel population modeling-management framework that is based on species life history and accounts for habitat loss to evaluate subsistence harvest for the Chukchi Sea (CS) polar bear subpopulation. Harvest strategies followed a state-dependent approach under which new data were used to update the harvest on a predetermined management interval. We found that a harvest strategy with a starting total harvest rate of 2.7% (˜85 bears/yr at current abundance), a 2:1 male-to-female ratio, and a 10-yr management interval would likely maintain subpopulation abundance above maximum net productivity level for the next 35 yr (approximately three polar bear generations), our primary criterion for sustainability. Plausible bounds on starting total harvest rate were 1.7–3.9%, where the range reflects uncertainty due to sampling variation, environmental variation, model selection, and differing levels of risk tolerance. The risk of undesired demographic outcomes (e.g., overharvest) was positively related to harvest rate, management interval, and projected declines in environmental carrying capacity; and negatively related to precision in population data. Results reflect several lines of evidence that the CS subpopulation has been productive in recent years, although it is uncertain how long this will last as sea-ice loss continues. Our methods provide a template for balancing trade-offs among protection, use, research investment, and other factors. Demographic risk assessment and state-dependent management will become increasingly important for harvested species, like polar bears, that exhibit spatiotemporal variation in their response to climate change.

Chukchi Sea↗
USGS2021

Can the impact of canopy trees on soil and understory be altered using litter additions?

Trees can have large effects on soil nutrients in ways that alter succession, particularly in the case of nitrogen-(N)-fixing trees. In Hawaiʻi, forest restoration relies heavily on use of a native N-fixing tree, Acacia koa (koa), but this species increases soil-available N and likely facilitates competitive dominance of exotic pasture grasses. In contrast, Metrosideros polymorpha (‘ōhi‘a), the dominant native tree in Hawaiʻi, is less often planted because it is slow growing; yet it is typically associated with lower soil N and grass biomass, and greater native understory recruitment. We experimentally tested whether it is possible to reverse high soil N under koa by adding ‘ōhi‘a litter, using additions of koa litter or no litter as controls, over 2.5 yr. We then quantified natural litterfall and decomposition rates of ‘ōhi‘a and koa litter to place litter additions in perspective. Finally, we quantified whether litter additions altered grass biomass and if this had effects on native outplants. Adding ‘ōhi‘a litter increased soil carbon, but increased rather than decreased inorganic soil N pools. Contrary to expectations, koa litter decomposed more slowly than ‘ōhi‘a, although it released more N per unit of litter. We saw no reduction in grass biomass due to ‘ōhi‘a litter addition, and no change in native outplanted understory survival or growth. We conclude that the high N soil conditions under koa are difficult to reverse. However, we also found that outplanted native woody species were able to decrease exotic grass biomass over time, regardless of the litter environment, making this a better strategy for lowering exotic species impacts.

Ecological Applications↗
USGS2022

Crowding, climate, and the case for social distancing among trees

In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate–vegetation–disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets—each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence—in a post-hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk ( P m ) was higher in crowded local neighborhoods that burned in wet years ( P m = 42%) compared with sparse neighborhoods that burned during drought ( P m = 30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought-related mortality over short timespans (<7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought.

California↗
USGS2022

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecological Applications↗
USGS2022

Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada

Severe droughts are predicted to become more frequent in the future, and the consequences of such droughts on forests can be dramatic, resulting in massive tree mortality, rapid change in forest structure and composition, and substantially increased risk of catastrophic fire. Forest managers have tools at their disposal to try to mitigate these effects but are often faced with limited resources, forcing them to make choices about which parts of the landscape to target for treatment. Such planning can greatly benefit from landscape vulnerability assessments, but many existing vulnerability analyses are unvalidated and not grounded in robust empirical datasets. We combined robust sets of ground-based plot and remote sensing data, collected during the 2012–2016 California drought, to develop rigorously validated tools for assessing forest vulnerability to drought-related canopy tree mortality for the mixed conifer forests of the Sequoia and Kings Canyon national parks and potentially for mixed conifer forests in the Sierra Nevada as a whole. Validation was carried out using a large external dataset. The best models included normalized difference vegetation index (NDVI), elevation, and species identity. Models indicated that tree survival probability decreased with greenness (as measured by NDVI) and elevation, particularly if trees were growing slowly. Overall, models showed good calibration and validation, especially for Abies concolor , which comprise a large majority of the trees in many mixed conifer forests in the Sierra Nevada. Our models tended to overestimate mortality risk for Calocedrus decurrens and underestimate risk for pine species, in the latter case probably due to pine bark beetle outbreak dynamics. Validation results indicated dangers of overfitting, as well as showing that the inclusion of trees already under attack by bark beetles at the time of sampling can give false confidence in model strength, while also biasing predictions. These vulnerability tools should be useful to forest managers trying to assess which parts of their landscape were vulnerable during the 2012–2016 drought, and, with additional validation, may prove useful for ongoing assessments and predictions of future forest vulnerability.

California↗
USGS2022

Leveraging community science data for population assessments during a pandemic

The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in population distribution. We fit our integrated model to 10 years of eBird (2010-2020) and 9 years of aerial survey (2010-2019) mottled duck count data to forecast 2020 population size along the western Gulf Coast of Texas and Louisiana. Estimates of mottled duck abundance were similar in magnitude to estimates calculated using previous methods, but were more precise and showed evidence of a declining population. The spatial distribution for mottled ducks each year was characterized by several concentrations of relatively high abundance, although the location of these abundance ‘hotspots’ varied over time. Expected abundance was higher for areas with a higher proportion of area covered by marsh habitat. By leveraging large-scale community science data, we were able to conduct a population assessment despite the disruption in structured surveys caused by the pandemic. As participation in community science platforms continues to increase, we anticipate modeling frameworks, like the integrated model we developed here, will become increasingly useful for informing conservation and management decision-making.

Louisiana, Texas↗