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Aim: Predicting distributions is fundamental to ecology, yet hindered by spatially restricted sampling, scale‐dependent relationships and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi‐scale data and used it to develop range‐wide breeding‐season SDMs for 14 marsh bird species of concern. Location: USA. Methods: We built SDMs using data from range‐wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out‐of‐sample prediction, range‐wide sampling over broad conditions, multi‐scale analyses and scale optimization, and species‐specific detectability for a suite of wide‐ranging species. Results: Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban and hydrologic disturbances operating from local scales (100–500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at >1 scale. Five species showed evidence for continental‐scale range contraction during the study. Main conclusions: We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data‐driven, empirical SDMs built at the range‐wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine‐scale wetland vegetation missed important broadscale drivers of occupancy for marsh birds. [ABSTRACT FROM AUTHOR]

Aim : Changes in abundance and shifts in distribution as a result of a warming climate have been documented for many marine species, but opportunities to test our ability to forecast such changes have been limited. This study evaluates the ability of habitat‐based density models to accurately forecast cetacean abundance and distribution during a novel year with unprecedented warm ocean temperatures caused by a sustained marine heatwave. Location : California Current Ecosystem, USA. Methods : We constructed generalized additive models based on cetacean sighting and environmental data from 1991 to 2009 for eight species with a diverse range of habitat associations. Models were built with three different sets of predictor variables to compare performance. Models were then used to forecast species abundance and distribution patterns during 2014, a year with anomalously warm ocean temperatures. Cetacean sighting data collected during 2014 were used to assess model forecasts. Results: Ratios of model‐predicted abundance to observed abundance were close to 1:1 for all but one species and accurately captured changes in the number of animals in the study area during the anomalous year. Predicted distribution patterns also showed good concordance with the 2014 survey observations. Our results indicate that habitat relationships were captured sufficiently to predict both changes in abundance and shifts in distribution when conditions warmed, for both cool‐ and warm‐temperate species. Main conclusions: Models built with multidecadal datasets were able to forecast abundance and distribution in a novel warm year for a diverse set of cetacean species. Models with the best explanatory power did not necessarily have the best predictive power. Also, they revealed species‐specific responses to warming ocean waters. Results have implications for modelling effects of climate change on cetaceans and other marine predators. [ABSTRACT FROM AUTHOR]

Restoration and conservation may be enhanced by using ecologically-based methods for prioritizing actions. Efforts are currently underway to restore river flows to the San Joaquin River in California's Central Valley. Although fish are the primary restoration target for restored flows, comple-mentary efforts are being designed to protect, enhance, and restore riparian and floodplain habitats to benefit the larger ecological community. We describe our efforts to use bird habitat distribution models to inform and prioritize conservation activities along the San Joaquin River. We demonstrate the integra-tion of habitat distribution models into an established conservation planning process that illustrates the synergies and tradeoffs of protecting high quality habitat for multiple species-groups and other restoration opportunities on the San Joaquin River. We used quantitative models to develop habitat quality indices for marsh birds, early-successional riparian birds, and mid/late-successional riparian birds, and used these indices to rank 18 sites under consideration along the San Joaquin River. We found little evidence that the rankings of the 18 sites for the three habitats were correlated, suggesting that any prioritiza-tion decisions will need to consider the quality of all three habitats, rather than one habitat acting as a surrogate for the others. Considering the habitat model rankings together with expert opinion rankings based on existing habitat quality, restoration potential, and flood management opportunities allowed us to identify sites that ranked high across multiple criteria. These results illustrate a simple process by which quantitative information from habitat models can be combined with expert opinion to inform priorities for protection and restoration. [ABSTRACT FROM AUTHOR]

We developed predictive habitat models for a bighorn sheep (Ovis canadensis) population in the Peninsular Ranges of southern California, USA, using 2 Geographic Information System modeling techniques, Ecological Niche Factor Analysis (ENFA) and Genetic Algorithm for Rule-set Production (GARP). We used .16,000 Global Positioning System locations from 34 animals in 5 subpopulations to develop and test ENFA and GARP models, and we then compared these models to each other and to the expert-based model presented in the United States Fish and Wildlife Service's Recovery Plan for this population. Based on a suite of evaluation methods, we found both ENFA and GARP to provide useful predictions of habitat; however, models developed with GARP appeared to have higher predictive power. Habitat delineations resulting from GARP models were similar to the expert-based model, affirming that the expert-based model provided a useful delineation of bighorn sheep habitat in the Peninsular Ranges. In addition, all 3 models identified continuous bighorn sheep habitat from the northern to southern extent of our study area, indicating that the Recovery Plan's recommendation of maintaining habitat connectivity throughout the range is an appropriate goal. [ABSTRACT FROM AUTHOR]

This article reports that the natural resources management at large spatial and temporal scales requires tools for projecting the effects of natural and anthropogenic disturbances on population, community, and ecosystem processes. Computer simulation allows modeling of scenarios to test the effect of disturbance regimes on landscape patterns and, in turn, on population dynamics of wildlife species of management concern. In many cases, these simulations use metapopulation models that incorporate aspects of a dynamic landscape, such as changing carrying capacities of habitat patches through time. The U.S. Forest Service identified Bell's Sage Sparrow, a California Species of Special Concern, as currently at moderate risk of population decline, although population trends are unknown. It was also designated as a species best conserved though landscape-level habitat management. The Bell's Sage Sparrow is associated with coastal sage scrub vegetation, a plant formation dominated by small, drought-deciduous shrubs, as well as open chaparral habitats in the interior foothills, especially young-aged, recently burned chaparral.