Composite estimation to combine spatially overlapping environmental monitoring surveys.

Long-term environmental monitoring surveys are designed to achieve a desired precision (measured by variance) of resource conditions based on natural variability information. Over time, increases in resource variability and in data use to address issues focused on small areas with limited sample sizes require bolstering of attainable precision. It is often prohibitive to do this by increasing sampling effort. In cases with spatially overlapping monitoring surveys, composite estimation offers a statistical way to obtain a precision-weighted combination of survey estimates to provide improved population estimates (more accurate) with improved precisions (lower variances). We present a composite estimator for overlapping surveys, a summary of compositing procedures, and a case study to illustrate the procedures and benefits of composite estimation. The study uses the two terrestrial monitoring surveys administered by the Bureau of Land Management (BLM) that entirely overlap. Using 2015-18 data and 13 land-health indicators, we obtained and compared survey and composite indicator estimates of percent area meeting land-health standards for sagebrush communities in Wyoming's Greater Sage-Grouse (Centrocercus urophasianus) Core and NonCore conservation areas on BLM-managed lands. We statistically assessed differences in indicator estimates between the conservation areas using composite estimates and estimates of the two surveys individually. We found composite variance to be about six to 24 units lower than 37% of the survey variances and composite estimates to differ by about six to 10 percentage points from six survey estimates. The composite improvements resulted in finding 11 indicators to statistically differ (p <0.05) between the conservation areas compared to only six and seven indicators for the individual surveys. Overall, we found composite estimation to be an efficient and useful option for improving environmental monitoring information where two surveys entirely overlap and suggest how this estimation method could be beneficial where environmental surveys partially overlap and in small area applications.

Identifying Policy-relevant Indicators for Assessing Landscape Vegetation Patterns to Inform Planning and Management on Multiple-use Public Lands.

Understanding the structure and composition of landscapes can empower agencies to effectively manage public lands for multiple uses while sustaining land health. Many landscape metrics exist, but they are not often used in public land decision-making. Our objectives were to (1) develop and (2) apply a process for identifying a core set of indicators that public land managers can use to understand landscape-level resource patterns on and around public lands. We first developed a process for identifying indicators that are grounded in policy, feasible to quantify using existing data and resources, and useful for managers. We surveyed landscape monitoring efforts by other agencies, gathered science and agency input on monitoring goals, and quantified the prevalence of potential indicators in agency land health standards to identify five landscape indicators: amount, distribution, patch size, structural connectivity, and diversity of vegetation types. We then conducted pilot applications in four bureau of land management (BLM) field offices in Arizona, California, and Colorado to refine procedures for quantifying the indicators and assess the utility of the indicators for managers. Results highlighted the dominance of upland and the limited extent of riparian/wetland vegetation communities, moderate connectivity of priority vegetation patches, and lower diversity of native vegetation types on BLM compared to non-BLM lands. Agency staff can use the indicators to inform the development of quantitative resource management objectives in land use plans, evaluate progress in meeting those objectives, quantify potential impacts of proposed actions, and as a foundation for an all-lands approach to landscape-level management across public lands.

Influences of potential oil and gas development and future climate on Sage-grouse declines and redistribution.

Multiple environmental stressors impact wildlife populations, but we often know little about their cumulative and combined influences on population outcomes. We generally know more about past effects than potential future impacts, and direct influences such as changes of habitat footprints than indirect, long-term responses in behavior, distribution, or abundance. Yet, an understanding of all these components is needed to plan for future landscapes that include human activities and wildlife. We developed a case study to assess how spatially explicit individual-based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater Sage-grouse in southwest Wyoming, USA, we projected oil and gas development footprints and climate-induced vegetation changes 50 years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we recalculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term Sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered a useful means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. The inclusion of movement and demographic responses to oil and gas infrastructure resulted in substantive changes in distribution and abundance when cumulated over several decades and throughout the regional population. When combined, additive development and climate-induced vegetation changes reduced abundance by up to half of the original size. In our example, the consideration of only a single population stressor the final possible population size by as much as 50%. Multiple stressors and their cumulative impacts need to be broadly considered through space and time to avoid underestimating the impacts of multiple gradual changes and overestimating the ability of populations to withstand change.

Gene flow and simulation of transgene dispersal from hybrid poplar plantations.

Gene flow is a primary determinant of potential ecological impacts of transgenic trees. However, gene flow is a complex process that must be assessed in the context of realistic genetic, management, and environmental conditions. We measured gene flow from hybrid poplar plantations using morphological and genetic markers, and developed a spatially explicit landscape model to simulate pollination, dispersal, establishment, and mortality in the context of historical and projected disturbance and land-use regimes. Most pollination and seed establishment occurred within 450 m of the source, with a very long tail. Modeled transgene flow was highly context-dependent, strongly influenced by the competitive effects of transgenes, transgenic fertility, plantation rotation length, disturbance regime, and spatial and temporal variation in selection. The use of linked infertility genes even if imperfect, substantially reduced transgene flow in a wide range of modeled scenarios. The significance of seed and vegetative dispersal was highly dependent on plantation size. Our empirical and modeling studies suggest that transgene spread can be spatially extensive. However, the amount of spread is highly dependent on ecological and management context, and can be greatly limited or prevented by management or mitigation genes such as those that cause sexual infertility.

An Approach for Managing Vertebrate Diversity Across Multiple-Use Landscapes.

Land managers face the difficult challenge of maintaining biodiversity on lands also used for commodity production. We present an approach for managing the habitats of terrestrial vertebrates at the landscape scale on multiple-use lands. The approach is based on the hypothesis that animal community response to landscape change is a function of species life histories and local patterns of landscape change. Key steps are: (1) set clear objectives; (2) associate target species with specific habitat configurations; (3) assess the potential sensitivity of species by mapping habitat suitability and examining species life histories; (4) evaluate alternative management prescriptions using simulation models; and (5) implement preferred or experimental strategies and monitor the responses of habitats and species. The approach was demonstrated for a watershed in western Oregon. Management objectives were to maximize habitat diversity for early- and late-successional bird species and to produce saw timber at levels compatible with the habitat goals. Habitat associations of 51 bird species were described by four variables that encompass three spatial scales. An analysis of species sensitivity to landscape change revealed several species that may merit special attention. The landscape model LSPA and the gap model ZELIG.PNW were used to simulate four disturbance/management scenarios over a 140-yr period: natural fire, wood production, multiple use, and no action. The results indicated that 65% more saw timber would be produced under the wood production run than the multiple-use run, but the former would maintain habitats for many fewer bird species than the latter. The multiple-use scenario was selected as the preferred alternative. We suggest carrying out management experiments and rigorous monitoring during the implementation phase. While this approach has various limitations, it is an incremental step towards the effective management of species diversity on multiple-use lands.