Record S.,Harvard University |
Fitzpatrick M.C.,University of Maryland Center for Environmental science |
Finley A.O.,Michigan State University |
Veloz S.,PRBO Conservation Science |
Ellison A.M.,Harvard University
Global Ecology and Biogeography | Year: 2013
Aim: The distributions of many organisms are spatially autocorrelated, but it is unclear whether including spatial terms in species distribution models (SDMs) improves projections of species distributions under climate change. We provide one of the first comparative evaluations of the ability of a purely spatial SDM, a purely non-spatial SDM and a SDM that combines spatial and environmental information to project species distributions across eight millennia of climate change. Location: Eastern North America. Methods: To distinguish between the importance of climatic versus spatial explanatory variables we fit three Bayesian SDMs to modern occurrence data for Fagus and Tsuga, two tree genera whose distributions can be reliably inferred from fossil pollen: a spatially varying intercept model, a non-spatial model with climatic variables and a spatially varying intercept plus climate model. Using palaeoclimate data with a high temporal resolution, we hindcasted the SDMs in 1000-year time steps for 8000 years, and compared model projections with palynological data for the same periods. Results: For both genera, spatial SDMs provided better fits to the calibration data, more accurate predictions of a hold-out validation dataset of modern trees and higher variance in current predictions and hindcasted projections than non-spatial SDMs. Performance of non-spatial and spatial SDMs according to the area under the receiver operating curve varied by genus. For both genera, false negative rates between non-spatial and spatial models were similar, but spatial models had lower false positive rates than non-spatial models. Main conclusions: The inclusion of computationally demanding spatial random effects in SDMs may be warranted when ecological or evolutionary processes prevent taxa from shifting their distributions or when the cost of false positives is high. © 2013 John Wiley & Sons Ltd.
Holmes A.L.,Oregon State University |
Miller R.F.,PRBO Conservation Science
Journal of Wildlife Management | Year: 2010
The combination of ecological site descriptions and state-and-transition models (STMs) describes potential vegetation, plant composition, and plant community dynamics and thus can be used to classify and understand dynamics of wildlife habitats across landscapes or home ranges. Numerous studies have evaluated effects of plant community dynamics on diversity and abundance of wildlife populations, but we could find no studies that examined changes in wildlife populations with respect to STMs. We compared abundance of grasshopper sparrows (Ammodramus savannarum) across 5 community phases representing 2 different ecological states in the Columbia Basin, Oregon, USA, to evaluate utility of STMs for understanding and predicting potential changes in habitat use by wildlife species. We measured grasshopper sparrow abundance in 165 100-m fixed-radius point counts distributed across 17 study plots within 5 plant community phases: native perennial grassland, sagebrush-steppe, depleted sagebrush-steppe, sagebrush-steppe with an annual grass understory, and annual grassland. We used a general estimating equation with a Poisson distribution to model relative abundance and estimate differences in this abundance index between linked pairs of community phases. Grasshopper sparrows showed clear differences in abundance among community phases and were most numerous in perennial grasslands and least abundant in depleted sagebrush and sagebrush annual grass community phases. As a management tool, STM provides information that predicts the direct and indirect cumulative impacts of various management actions on vegetation composition and structure (and thus habitat). Ecological site descriptions and STMs enable land managers and scientists to assess potential and current wildlife habitat suitability and to predict potential response of wildlife populations to vegetation dynamics based on the ecological potential of the site. © 2010 The Wildlife Society.
Wiens J.A.,PRBO Conservation Science |
Bachelet D.,Oregon State University |
Bachelet D.,Conservation Biology Institute
Conservation Biology | Year: 2010
To anticipate the rapidly changing world resulting from global climate change, the projections of climate models must be incorporated into conservation. This requires that the scales of conservation be aligned with the scales of climate-change projections. We considered how conservation has incorporated spatial scale into protecting biodiversity, how the projections of climate-change models vary with scale, and how the two do or do not align. Conservation planners use information about past and current ecological conditions at multiple scales to identify conservation targets and threats and guide conservation actions. Projections of climate change are also made at multiple scales, from global and regional circulation models to projections downscaled to local scales. These downscaled projections carry with them the uncertainties associated with the broad-scale models from which they are derived; thus, their high resolution may be more apparent than real. Conservation at regional or global scales is about establishing priorities and influencing policy. At these scales, the coarseness and uncertainties of global and regional climate models may be less important than what they reveal about possible futures. At the ecoregional scale, the uncertainties associated with downscaling climate models become more critical because the distributions of conservation targets on which plans are founded may shift under future climates. At a local scale, variations in topography and land cover influence local climate, often overriding the projections of broad-scale climate models and increasing uncertainty. Despite the uncertainties, ecologists and conservationists must work with climate-change modelers to focus on the most likely projections. The future will be different from the past and full of surprises; judicious use of model projections at appropriate scales may help us prepare. © 2009 Society for Conservation Biology.
Ainley D.G.,H.T. Harvey and Associates |
Ballard G.,PRBO Conservation Science
Polar Biology | Year: 2012
Recent research has clearly shown that the fear of predation, i. e. aversion to taking risks, among mesopredators or grazers, and not merely flight from an apex predator to avoid predation, is an important aspect of ecosystem structuring. In only a few, though well-documented cases, however, has this been considered in the marine environment. Herein, we review studies that have quantified behavioral responses of Adélie penguins Pygoscelis adeliae and emperor penguins Aptenodytes forsteri to the direct presence of predators, and question why the penguins avoid entering or exiting the water at night. We also show, through literature review and new analyses of Adélie penguin diving data, that Antarctic penguins are capable of successful prey capture in the dark (defined here as <3.4 lux). Finally, we summarize extensive data on seasonal migration relative to darkness and prey availability. On the basis of our findings, we propose that penguins' avoidance of foraging at night is due to fear of predation, and not to an inability to operate effectively in darkness. We further propose that, at polar latitudes where darkness is more a seasonal than a year-round, daily feature, this "risk aversion" affects migratory movements in both species, consistent with the "trade-off" hypothesis seen in other marine vertebrates weighing foraging success against predation risk in their choice of foraging habitat. Such non-consumptive, behavioral aspects of species interactions have yet to be considered as important in Southern Ocean food webs, but may help to explain enigmatic movement patterns and choice of foraging grounds in these penguin species. © 2011 Springer-Verlag.
Kelly M.,University of California at Berkeley |
Tuxen K.A.,P.O. Box 7092 |
Stralberg D.,PRBO Conservation Science
Ecological Indicators | Year: 2011
Tidal salt marshes in the San Francisco Estuary region display heterogeneous vegetation patterns that influence wetland function and provide adequate habitat for native or endangered wildlife. In addition to analyzing the extent of vegetation, monitoring the dynamics of vegetation pattern within restoring wetlands can offer valuable information about the restoration process. Pattern metrics, derived from classified remotely sensed imagery, have been used to measure composition and configuration of patches and landscapes, but they can be unpredictable across scales, and inconsistent across time. We sought to identify pattern metrics that are consistent across spatial scale and time - and thus robust measures of vegetation and habitat configuration - for a restored tidal marsh in the San Francisco Bay, CA, USA. We used high-resolution (20 cm) remotely sensed color infrared imagery to map vegetation pattern over 2 years, and performed a multi-scale analysis of derived vegetation pattern metrics. We looked at the influence on metrics of changes in grain size through resampling and changes in minimum mapping unit (MMU) through smoothing. We examined composition, complexity, connectivity and heterogeneity metrics, focusing on perennial pickleweed (Sarcocornia pacifica), a dominant marsh plant. At our site, pickleweed patches grew larger, more irregularly shaped, and closely spaced over time, while the overall landscape became more diverse. Of the two scale factors examined, grain size was more consistent than MMU in terms of identifying relative change in composition and configuration of wetland marsh vegetation over time. Most metrics exhibited unstable behavior with larger MMUs. With small MMUs, most metrics were consistent across grain sizes, from fine (e.g. 0.16 m2) to relatively large (e.g. 16m2) pixel sizes. Scale relationships were more variable at the landcover class level than at the landscape level (across all classes). This information may be useful to applied restoration practitioners, and adds to our general understanding of vegetation change in a restoring marsh. © 2010 Elsevier Ltd. All rights reserved.