Multicriteria decisions and portfolio analysis: land acquisition for biological and social objectives.

Resource allocation for land acquisition is a common multiobjective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e., individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multicriteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multiobjective decisions. In this study, we present an alternative approach to developing land-acquisition portfolios using MCDA and modern portfolio theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land-acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

Broad-scale changes in lesser prairie-chicken habitat.

Lesser prairie-chicken (Tympanuchus pallidicinctus) populations of in the Sand Sagebrush Prairie Ecoregion of southwest Kansas and southeast Colorado, USA, have declined sharply since the mid-1980s. Decreased quality and availability of habitat are believed to be the main drivers of declines. Our objective was to reconstruct broad-scale change in the ecoregion since 1985 as a potential factor in population declines. We assessed temporal change from 1985-2015 in landcover types and calculated landscape metrics using Land Change Monitoring, Assessment, and Projection imagery layers. We also documented presence of anthropogenic structures including oil wells and electrical transmission lines. Landcover type composition changed little since 1990 across the Sand Sagebrush Prairie Ecoregion. However, anthropogenic structures (i.e., oil/gas wells, cell towers, wind farms, and transmission lines) notably increased, potentially causing functional habitat loss at a broad scale. Increased anthropogenic structures may have decreased habitat availability as well as the quality of existing habitat for lesser prairie-chickens, possibly contributing to recent population declines throughout the Sand Sagebrush Prairie Ecoregion.

Lesser prairie-chicken dispersal after translocation: Implications for restoration and population connectivity.

Conservation translocations are frequently inhibited by extensive dispersal after release, which can expose animals to dispersal-related mortality or Allee effects due to a lack of nearby conspecifics. However, translocation-induced dispersals also provide opportunities to study how animals move across a novel landscape, and how their movements are influenced by landscape configuration and anthropogenic features. Translocation among populations is considered a potential conservation strategy for lesser prairie-chickens (Tympanuchus pallidicinctus). We determined the influence of release area on dispersal frequency by translocated lesser prairie-chickens and measured how lesser prairie-chickens move through grassland landscapes through avoidance of anthropogenic features during their dispersal movements. We translocated 411 lesser prairie-chickens from northwest Kansas to southeastern Colorado and southwestern Kansas in 2016-2019. We used satellite GPS transmitters to track 115 lesser prairie-chickens throughout their post-release dispersal movements. We found that almost all lesser prairie-chickens that survived from their spring release date until June undergo post-translocation dispersal, and there was little variation in dispersal frequency by release area (96% of all tracked birds, 100% in Baca County, Colorado, 94% in Morton County, Kansas, n = 55). Dispersal movements (male: 103 ± 73 km, female: 175 ± 108 km, n = 62) led to diffusion across landscapes, with 69% of birds settling >5 km from their release site. During dispersal movements, translocated lesser prairie-chickens usually travel by a single 3.75 ± 4.95 km dispersal flight per day, selecting for steps that end far from roads and in Conservation Reserve Program (CRP) grasslands. Due to this "stepping stone" method of transit, landscape connectivity is optimized when <5 km separates grassland patches on the landscape. Future persistence of lesser prairie-chicken populations can be aided through conservation of habitat and strategic placement of CRP to maximize habitat connectivity. Dispersal rates suggest that translocation is better suited to objectives for regional, rather than site-specific, population augmentation for this species.

Accounting for location uncertainty in azimuthal telemetry data improves ecological inference.

BACKGROUND: Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models.We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference. RESULTS: We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation. CONCLUSION: The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development.

Fragmentation of the sagebrush (Artemisia spp.) ecosystem has led to concern about a variety of sagebrush obligates including the greater sage-grouse (Centrocercus urophasianus). Given the increase of energy development within greater sage-grouse habitats, mapping seasonal habitats in pre-development populations is critical. The North Park population in Colorado is one of the largest and most stable in the state and provides a unique case study for investigating resource selection at a relatively low level of energy development compared to other populations both within and outside the state. We used locations from 117 radio-marked female greater sage-grouse in North Park, Colorado to develop seasonal resource selection models. We then added energy development variables to the base models at both a landscape and local scale to determine if energy variables improved the fit of the seasonal models. The base models for breeding and winter resource selection predicted greater use in large expanses of sagebrush whereas the base summer model predicted greater use along the edge of riparian areas. Energy development variables did not improve the winter or the summer models at either scale of analysis, but distance to oil/gas roads slightly improved model fit at both scales in the breeding season, albeit in opposite ways. At the landscape scale, greater sage-grouse were closer to oil/gas roads whereas they were further from oil/gas roads at the local scale during the breeding season. Although we found limited effects from low level energy development in the breeding season, the scale of analysis can influence the interpretation of effects. The lack of strong effects from energy development may be indicative that energy development at current levels are not impacting greater sage-grouse in North Park. Our baseline seasonal resource selection maps can be used for conservation to help identify ways of minimizing the effects of energy development.