Application of multiple-population viability analysis to evaluate species recovery alternatives.

Population viability analysis (PVA) is a powerful conservation tool, but it remains impractical for many species, particularly species with multiple, broadly distributed populations for which collecting suitable data can be challenging. A recently developed method of multiple-population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We built on previous development of MPVA for Lahontan cutthroat trout (LCT) (Oncorhynchus clarkii henshawi), a species listed under the U.S. Endangered Species Act, that is distributed broadly across habitat fragments in the Great Basin (U.S.A.). We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams, where LCT exist or may be reintroduced. Conservation populations (those managed for recovery) tended to have lower extinction risks than nonconservation populations (mean = 19.8% vs. 52.7%), but not always. Active management or reprioritization may be warranted in some cases. Eliminating non-native trout had a strong positive effect on overall carrying capacities for LCT populations but often did not translate into lower extinction risks unless simulations also reduced associated stochasticity (to the mean for populations without non-native trout). Sixty fish or 5-10 fish/km was the minimum reintroduction number and density, respectively, that provided near-maximum reintroduction success. This modeling framework provided crucial insights and empirical justification for conservation planning and specific adaptive management actions for this threatened species. More broadly, MPVA is applicable to a wide range of species exhibiting geographic rarity and limited availability of abundance data and greatly extends the potential use of empirical PVA for conservation assessment and planning.

Aplicación de un Análisis de Viabilidad Multi-Poblacional para Evaluar Alternativas de Recuperación de Especies Resumen El análisis de viabilidad poblacional (AVP) es una herramienta poderosa de conservación, que desafortunadamente sigue siendo impráctica para muchas especies, en particular para aquellas con poblaciones múltiples distribuidas ampliamente, para las cuales puede ser un reto la recolección de datos apropiados. Sin embargo, un método recientemente desarrollado de análisis de viabilidad multi-poblacional (AVMP) aborda muchas de las limitaciones de los AVP tradicionales. Partimos del desarrollo previo de un AVMP para la trucha degollada lahontana (LCT, en inglés) (Oncorhynchus clarkii henshawi), una especie enlistada bajo el Acta de Especies en Peligro de los Estados Unidos, la cual está distribuida ampliamente a lo largo de los fragmentos de hábitat que se encuentran en la Gran Cuenca (E.U.A.). Simulamos los escenarios potenciales de manejo y evaluamos sus efectos sobre el tamaño de las poblaciones y los riesgos de extinción en 211 arroyos en donde existe la LCT o en donde podría ser reintroducida. Las poblaciones de conservación (aquellas manejadas para su recuperación) tuvieron una tendencia hacia un riesgo de extinción más bajo que las poblaciones sin conservación (media = 19.8% vs. 52.7%), pero no en todos los casos. El manejo activo o la repriorización podrían ser justificadas en algunos casos. La eliminación de las truchas no nativas tuvo un fuerte efecto positivo generalizado sobre las capacidades de carga de las poblaciones de LCT, aunque frecuentemente esto no se transformó en un riesgo de extinción más bajo a menos que las simulaciones también redujeran la estocasticidad asociada (para la media de las poblaciones sin truchas no nativas). Para proporcionar un éxito de reintroducción cercano al máximo, el número mínimo de reintroducción debió ser de 60 peces o una densidad de 5-10 peces/km. Este marco de trabajo para el modelo proporcionó una percepción muy importante y una justificación empírica para la planeación de la conservación y para las acciones de manejo adaptativo para esta especie amenazada. En términos más generales, el AVMP puede aplicarse a una gama amplia de especies que exhiban una rareza geográfica y una disponibilidad limitada de datos de abundancia, además de que expande enormemente el uso potencial de AVP empíricos para la evaluación y planeación de la conservación.

Hierarchical multi-population viability analysis.

Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985-2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties.

Livestock management, beaver, and climate influences on riparian vegetation in a semi-arid landscape.

Riparian and aquatic habitats support biodiversity and key environmental processes in semi-arid and arid landscapes, but stressors such as conventional livestock grazing, wildfire, and drought can degrade their condition. To enhance habitat for fish and wildlife and increase resiliency in these critical areas, land managers in the interior western United States increasingly use alternative grazing strategies, beaver management, or beaver dam surrogates as low-effort, low-expense restoration approaches. In this study we used historical archives of satellite and aerial imagery spanning three decades to characterize riparian vegetation productivity and document beaver dam occurrences, then evaluated vegetation productivity relative to land management associated with livestock grazing and beaver dam densities while accounting for climate and wildfire. After controlling for stream characteristics such as stream size, elevation, and stream slope, we demonstrate a positive response of riparian area vegetation to conservation-oriented grazing approaches and livestock exclosures, extensive beaver dam development, increased precipitation, and lack of wildfire. We show that livestock management which emphasizes riparian recovery objectives can be an important precursor to beaver activity and describe 11-39% increases in floodplain vegetation productivity where conservation-oriented grazing approaches or livestock exclosures and high beaver activity occur together on low-gradient sites. Land management decisions can therefore potentially confer resiliency to riparian areas under changing and variable climate conditions-the increased vegetation productivity resulting from conservation-oriented grazing or exclosures and high amounts of beaver activity at our sites is the equivalent to moving conventionally-grazed, low-gradient sites without beaver up at least 250 m in elevation or increasing water year precipitation by at least 250 mm.

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change.

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1-42.5 thousand km; this was predicted to decline to 0.5-7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change.

Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout across the interior western United States (1.01 million km(2)), based on empirical statistical models built from fish surveys at 9,890 sites. Projections under the 2080s A1B emissions scenario forecast a mean 47% decline in total suitable habitat for all trout, a group of fishes of major socioeconomic and ecological significance. We project that native cutthroat trout Oncorhynchus clarkii, already excluded from much of its potential range by nonnative species, will lose a further 58% of habitat due to an increase in temperatures beyond the species' physiological optima and continued negative biotic interactions. Habitat for nonnative brook trout Salvelinus fontinalis and brown trout Salmo trutta is predicted to decline by 77% and 48%, respectively, driven by increases in temperature and winter flood frequency caused by warmer, rainier winters. Habitat for rainbow trout, Oncorhynchus mykiss, is projected to decline the least (35%) because negative temperature effects are partly offset by flow regime shifts that benefit the species. These results illustrate how drivers other than temperature influence species response to climate change. Despite some uncertainty, large declines in trout habitat are likely, but our findings point to opportunities for strategic targeting of mitigation efforts to appropriate stressors and locations.

Patch size and shape influence the accuracy of mapping small habitat patches with a global positioning system.

Global positioning systems (GPS) are increasingly being used for habitat mapping because they provide spatially referenced data that can be used to characterize habitat structure across the landscape and document habitat change over time. We evaluated the accuracy of using a GPS for determining the size and location of habitat patches in a riverine environment. We simulated error attributable to a mapping-grade GPS receiver capable of achieving sub-meter accuracy onto discrete macrophyte bed and wood habitat patches (2 to 177 m(2)) that were digitized from an aerial photograph of the Laramie River, Wyoming, USA in a way that emulated field mapping. Patches with simulated error were compared to the original digitized patches. The accuracy in measuring habitat patches was affected most by patch size and less by patch shape and complexity. Perimeter length was consistently overestimated but was less biased for large, elongate patches with complex shapes. Patch area was slightly overestimated for small patches but was unbiased for large patches. Precision of area estimates was highest for large (>100 m(2)), elongate patches. Percent spatial overlap, a measure of the spatial accuracy of patch location, was low and variable for the smallest patches (2 to 5 m(2)). Mean percent spatial overlap was not related to patch shape but the precision of overlap was lower for small, elongate, and complex patches. Mapping habitat patches with a mapping-grade GPS can yield useful data, but research objectives will determine the acceptable amount of error and the smallest habitats that can be reliably measured.

Design to monitor trend in abundance and presence of American beaver (Castor canadensis) at the national forest scale.

Wildlife conservationists design monitoring programs to assess population dynamics, project future population states, and evaluate the impacts of management actions on populations. Because agency mandates and conservation laws call for monitoring data to elicit management responses, it is imperative to design programs that match the administrative scale for which management decisions are made. We describe a program to monitor population trends in American beaver (Castor canadensis) on the US Department of Agriculture, Black Hills National Forest (BHNF) in southwestern South Dakota and northeastern Wyoming, USA. Beaver have been designated as a management indicator species on the BHNF because of their association with riparian and aquatic habitats and its status as a keystone species. We designed our program to monitor the density of beaver food caches (abundance) within sampling units with beaver and the proportion of sampling units with beavers present at the scale of a national forest. We designated watersheds as sampling units in a stratified random sampling design that we developed based on habitat modeling results. Habitat modeling indicated that the most suitable beaver habitat was near perennial water, near aspen (Populus tremuloides) and willow (Salix spp.), and in low gradient streams at lower elevations. Results from the initial monitoring period in October 2007 allowed us to assess costs and logistical considerations, validate our habitat model, and conduct power analyses to assess whether our sampling design could detect the level of declines in beaver stated in the monitoring objectives. Beaver food caches were located in 20 of 52 sampled watersheds. Monitoring 20 to 25 watersheds with beaver should provide sufficient power to detect 15-40% declines in the beaver food cache index as well as a twofold decline in the odds of beaver being present in watersheds. Indices of abundance, such as the beaver food cache index, provide a practical measure of population status to conduct long-term monitoring across broad landscapes such as national forests.

Mapping stream habitats with a global positioning system: accuracy, precision, and comparison with traditional methods.

We tested the precision and accuracy of the Trimble GeoXTtrade mark global positioning system (GPS) handheld receiver on point and area features and compared estimates of stream habitat dimensions (e.g., lengths and areas of riffles and pools) that were made in three different Oklahoma streams using the GPS receiver and a tape measure. The precision of differentially corrected GPS (DGPS) points was not affected by the number of GPS position fixes (i.e., geographic location estimates) averaged per DGPS point. Horizontal error of points ranged from 0.03 to 2.77 m and did not differ with the number of position fixes per point. The error of area measurements ranged from 0.1% to 110.1% but decreased as the area increased. Again, error was independent of the number of position fixes averaged per polygon corner. The estimates of habitat lengths, widths, and areas did not differ when measured using two methods of data collection (GPS and a tape measure), nor did the differences among methods change at three stream sites with contrasting morphologies. Measuring features with a GPS receiver was up to 3.3 times faster on average than using a tape measure, although signal interference from high streambanks or overhanging vegetation occasionally limited satellite signal availability and prolonged measurements with a GPS receiver. There were also no differences in precision of habitat dimensions when mapped using a continuous versus a position fix average GPS data collection method. Despite there being some disadvantages to using the GPS in stream habitat studies, measuring stream habitats with a GPS resulted in spatially referenced data that allowed the assessment of relative habitat position and changes in habitats over time, and was often faster than using a tape measure. For most spatial scales of interest, the precision and accuracy of DGPS data are adequate and have logistical advantages when compared to traditional methods of measurement.

A provisional fish index of biotic integrity for assessing Ouachita Mountains streams in Arkansas, U.S.A.

Multimetric indices are often used to monitor aquatic-resource conditions. We used existing fish-collection data from streams to develop an Index of Biotic Integrity (IBI), which is a multimetric index, for the Ouachita Mountains ecoregion in Arkansas, U.S.A. Each fish-collection site was categorized as reference or non-reference. We examined 62 candidate IBI metrics, and selected 12 non-redundant metrics that differentiated best between reference and non-reference sites. The selected metrics were: Percent (of individuals) as Black Bass; Percent as Benthic Feeders; Percent as Centrarchids; Percent as Cyprinids; Percent as Ictalurids; Percent as Mineral, Site-Prep Spawners; Percent as Mineral, Site-Prep, Parental-Care Spawners; Percent as Simple, Mineral Substrate Spawners; Percent as Miscellaneous, Site-Prep, Parental-Care Spawners; Total Number of Centrarchid Species; Total Number of Arkansas Department of Environmental Quality (ADEQ) Ouachita Mountains Indicator Species; and Total Number of ADEQ Ouachita Mountains Key Species. We standardized each metric to score from 0 to 10 by using linear equations and threshold limits. Some selected IBI metrics had their scoring criteria adjusted to account for watershed size (i.e., stream size). We standardized the IBI to score from 0 to 100. In addition, we determined that our Percent as Black Bass and Percent as Benthic Feeders metrics contributed most to IBI scores in reference conditions, but their contributions decreased with decreasing stream conditions. Reproductive metrics contributed most in degraded stream conditions. Furthermore, we identified relations between IBI metrics and water-quality and land-use variables; some relations were counterintuitive. Unexpected relations may be random observations explained by limited ranges of land-use and water-quality variables. When select water-quality and land-use variables were included in a principal component analysis, a composite Land Use Intensity variable explained most of the model variance. Although the IBI has not been independently validated, the PCA, as well as other superficial analyses, indicated that the IBI should be able to differentiate stream conditions.