Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data ...types to achieve effective species management. Greater sage‐grouse Centrocercus urophasianus, hereafter ‘sage‐grouse’ populations are declining throughout sagebrush‐steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information. Herein, we improve upon existing species distribution models by combining information about sage‐grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage‐grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region‐wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. We also employed a novel index to describe landscape patterns of sage‐grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year‐round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and applications. Using the example of sage‐grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage‐grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage‐grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage‐grouse are an umbrella species, our joint‐index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central‐placed breeding.
Managers require quantitative yet tractable tools that identify areas for restoration yielding effective benefits for targeted wildlife species and the ecosystems they inhabit. As a contemporary ...example of high national significance for conservation, the persistence of Greater Sage-grouse (Centrocercus urophasianus) in the Great Basin is compromised by strongly interacting stressors of conifer expansion, annual grass invasion, and more frequent wildfires occurring in sagebrush ecosystems. Associated restoration treatments to a sagebrush-dominated state are often costly and may yield relatively little ecological benefit to sage-grouse if implemented without estimating how Sage-grouse may respond to treatments, or do not consider underlying processes influencing sagebrush ecosystem resilience to disturbance and resistance to invasive species. Here, we describe example applications of a spatially explicit conservation planning tool (CPT) to inform prioritization of: (1) removal of conifers (i.e., pinyon-juniper); and (2) wildfire restoration aimed at improving habitat conditions for the Bi-State Distinct Population Segment of Sage-grouse along the California–Nevada state line. The CPT measures ecological benefits to sage-grouse for a given management action through a composite index comprised of resource selection functions and estimates of abundance and space use. For pinyon-juniper removal, we simulated changes in land-cover composition following the removal of sparse trees with intact understories, and ranked treatments on the basis of changes in ecological benefits per dollar-unit of cost. For wildfire restoration, we formulated a conditional model to simulate scenarios for land cover changes (e.g., sagebrush to annual grass) given estimated fire severity and underlying ecosystem processes influencing resilience to disturbance and resistance to invasion by annual grasses. For both applications, we compared CPT rankings to land cover changes along with sagebrush resistance and resilience metrics. Model results demonstrated how the CPT can be an important step in identifying management projects that yield the highest quantifiable benefit to Sage-grouse while avoiding costly misallocation of resources, and highlight the importance of considering changes in sage-grouse ecological response and factors influencing sagebrush ecosystem resilience to disturbance and resistance to invasion. This unique framework can be adopted to help inform other management questions aimed at improving habitat for other species across sagebrush and other ecosystems.
Fine-scale spatiotemporal studies can better identify relationships between individual survival and habitat fragmentation so that mechanistic interpretations can be made at the population level. ...Recent advances in Global Positioning System (GPS) technology and statistical models capable of deconstructing high-frequency location data have facilitated interpretation of animal movement within a behaviorally mechanistic framework. Habitat fragmentation due to singleleaf pinyon (Pinus monophylla; hereafter pinyon) and Utah juniper (Juniperus osteosperma; hereafter juniper) encroachment into sagebrush (Artemisia spp.) communities is a commonly implicated perturbation that can adversely influence greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) demographic rates. Using an extensive GPS data set (233 birds and 282,954 locations) across 12 study sites within the Great Basin, we conducted a behavioral change point analysis and constructed Brownian bridge movement models from each behaviorally homogenous section. We found the probability of encountering pinyon-juniper among adults was two and three times greater than that of yearlings and juveniles, respectively. However, the movement rate in response to the probability of encountering pinyon-juniper trees was 1.5 times greater for juveniles. Parameter estimates indicated a 6.1% increase in the probability of encountering pinyon-juniper coupled with a 6.2 km/hour increase in movement speed resulted in a 56%, 42% and 16% increase in risk of daily mortality, for juveniles, yearlings, and adults, respectively. The effect of pinyon-juniper encounters on survival was dependent on movement rate and differed among age class. Under fast speed movements (i.e., flight), mortality risk increased as encountering pinyon-juniper increased across all age classes. In contrast, slower speeds (i.e., average) yielded similar adverse effects for juveniles and yearlings but not for adults. This analytical framework supports a behavioral mechanism that explains reduced survival related to pinyon-juniper within sagebrush environments, whereby encountering pinyon-juniper stimulates riskier movements that likely increase vulnerability to visually acute predators.
Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and ...precisely depict tree location and degree of woodland development so managers can target restoration efforts for early stages of pinyon and juniper expansion. However, available remotely sensed layers that cover a regional spatial extent lack the spatial resolution or accuracy to meet this need. Accuracy can be improved using object-based image analysis methods such as automated feature extraction, which has proven successful in accurately classifying land cover at the site-level but to date has yet to be applied to regional extents due to time and computational limitations. Using Feature Analyst™, we implement our framework with 1-m2 reference imagery provided by National Agricultural Imagery Program to classify conifers across Nevada and northeastern California. Our resulting binary conifer map has an overall accuracy of 86%. We discuss the advantages to accuracy and precision our framework provides compared to other classification methods.
● This framework allows automated feature extraction for large quantities of data and very high spatial resolution imagery
● It leverages supervised learning
● It results in high accuracy maps for regional spatial extents
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This study seeks to improve election forecasting by supplementing polling data with online information-seeking behavior trends as an indicator of public opinion. Aggregate trends of demonstrations of ...interest or engagement have been shown to accurately predict behavior trends and reflect public opinion. Further, because traditional poll-based predictions are inherently undermined by self-reporting biases and the intention-behavior disconnect, we can expect that information-seeking trends on widely used social media—as an autonomous and unobtrusive indicator of relative levels of public opinion—can help correct for some of this error and explain unique, additional variance in election results. We advance the literature by using data from Wikipedia pageviews along with polling data in a synthesized model based on the results of the 2008, 2010, and 2012 US Senate general elections. Results show that Wikipedia pageviews data significantly add to the ability of polland fundamentals-based projections to predict election results up to 28 weeks prior to Election Day, and benefit predictions most at those early points, when poll-based predictions are weakest.
Abstract
This study seeks to improve election forecasting by supplementing polling data with online information-seeking behavior trends as an indicator of public opinion. Aggregate trends of ...demonstrations of interest or engagement have been shown to accurately predict behavior trends and reflect public opinion. Further, because traditional poll-based predictions are inherently undermined by self-reporting biases and the intention-behavior disconnect, we can expect that information-seeking trends on widely used social media—as an autonomous and unobtrusive indicator of relative levels of public opinion—can help correct for some of this error and explain unique, additional variance in election results. We advance the literature by using data from Wikipedia pageviews along with polling data in a synthesized model based on the results of the 2008, 2010, and 2012 US Senate general elections. Results show that Wikipedia pageviews data significantly add to the ability of poll- and fundamentals-based projections to predict election results up to 28 weeks prior to Election Day, and benefit predictions most at those early points, when poll-based predictions are weakest.
Rice seed remaining in commercial fields after harvest (waste rice) is a critical food resource for wintering waterfowl in rice-growing regions of North America. Accurate and precise estimates of the ...seed mass density of waste rice are essential for planning waterfowl wintering habitat extents and management. In the Sacramento Valley of California, USA, the existing method for obtaining estimates of availability of waste rice in harvested fields produces relatively precise estimates, but the labor-, time-, and machinery-intensive process is not practical for routine assessments needed to examine long-term trends in waste rice availability. We tested several experimental methods designed to rapidly derive estimates that would not be burdened with disadvantages of the existing method. We first conducted a simulation study of the efficiency of each method and then conducted field tests. For each approach, methods did not vary in root mean squared error, although some methods did exhibit bias for both simulations and field tests. Methods also varied substantially in the time to conduct each sample and in the number of samples required to detect a standard trend. Overall, modified line-intercept methods performed well for estimating the density of rice seeds. Waste rice in the straw, although not measured directly, can be accounted for by a positive relationship with density of rice on the ground. Rapid assessment of food availability is a useful tool to help waterfowl managers establish and implement wetland restoration and agricultural habitat-enhancement goals for wintering waterfowl.
•We used OBIA to map conifers at a 1-m2 resolution across Nevada and California.•Accuracy assessment from reference imagery revealed overall accuracy of 86.38%.•Ground referenced accuracy of conifer ...classification was 87%.•Our products improve upon and complement existing conifer maps.•Maps aid multi-scale grouse and conifer management across much of the Great Basin.
Distributional expansion and infill of pinyon (Pinus monophylla) and juniper (Juniperus osteosperma, J. occidentalis) trees (hereinafter, "pinyon-juniper") into sagebrush ecosystems alters the ecological function and economic viability of these ecosystems and represents a major contemporary challenge facing land and wildlife managers. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance across broad geographic extents would facilitate science that quantifies ecological effects of pinyon-juniper expansion and help guide land management decisions that better target areas for pinyon-juniper treatment projects. We mapped conifers at a high (1- m2; i.e., 1 × 1-m) resolution across the majority of Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (USDA, 2013) to classify conifers using automated feature extraction (AFE) with the program Feature Analyst™ (Overwatch, 2013). Overall accuracy was >86% across all mapped areas for ground referencing methods. We provide five sets of full-extent maps for land managers: (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1-m2 resolution; (3) a 900-m2 resolution raster representing percentages of conifer canopy cover within each cell; (4) 1-m2 resolution canopy cover classification rasters derived from a 50-m radius moving window analysis; and (5) an example map derived from our canopy cover product that prioritizes pinyon-juniper treatment by significance to sage-grouse habitat improvement. Importantly, the canopy cover maps were developed to allow user-specified flexibility based on their own objectives (i.e., develop phases of expansion). These products improve upon or complement existing conifer maps for the Western United States and will help facilitate habitat management and sagebrush ecosystem restoration through an accurate understanding of conifer distribution and abundance at multiple spatial scales.
1. Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data ...types to achieve effective species management. 2. Greater sage-grouse Centrocercus urophasianus, hereafter 'sage-grouse' populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information. 3. Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. 4. We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. 5. Synthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.
Fine-scale spatiotemporal studies can better identify relationships between individual survival and habitat fragmentation so that mechanistic interpretations can be made at the populations level. ...Recent advances in GPS technology and statistical models capable of deconstructing high-frequency location data have facilitated interpretation of animal movement within a behaviorally mechanistic framework. Habitat fragmentation due to singleleaf pinyon (Pinus monophylla; hereafter pinyon) and Utah juniper (Juniperus osteosperma; hereafter juniper) encroachment into sagebrush (Artemisia spp.) communities is a commonly implicated perturbation that can adversely influencing greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) demographic rates. Using an extensive GPS data set (233 birds and 282,954 locations) across 12 study sites within the Great Basin, we conducted a behavioral change point analysis (BCPA) and subsequently constructed Brownian bridge movement models (BBMM) from each behaviorally homogenous section. We then modeled mean rate of travel as a function of probability of encountering pinyon-juniper and found a positive relationship between movement rate and probability of encountering pinyon-juniper with significant variation among age classes. The probability of encountering pinyon-juniper among adults was two and three times greater than that of yearlings and juveniles, respectively. However, the behavioral response to pinyon-juniper encroachment was 1.5 times greater for juveniles. We then assessed the risk of mortality associated with an interaction between movement rate and the probability of encountering pinyon-juniper using shared frailty models. During pinyon-juniper encounters, on average, juvenile, yearling, and adult birds experienced a 10.4, 0.2, and 0.3% reduction in annual survival probabilities. Populations that utilized pinyon-juniper habitats with greater frequency experienced decreases in annual survival probabilities of 71.1, 0.9, and 0.9%. This analytical framework identifies a likely behavioral mechanism behind how pinyon-juniper encroachment decreases habitat suitability for sage-grouse, whereby encountering pinyon-juniper stimulates faster yet riskier movements that may make sage-grouse more vulnerable to visually acute predators.
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