Riverine threat indices to assess watershed condition and identify primary management capacity of agriculture natural resource management agencies.

Managers can improve conservation of lotic systems over large geographies if they have tools to assess total watershed conditions for individual stream segments and can identify segments where conservation practices are most likely to be successful (i.e., primary management capacity). The goal of this research was to develop a suite of threat indices to help agriculture resource management agencies select and prioritize watersheds across Missouri River basin in which to implement agriculture conservation practices. We quantified watershed percentages or densities of 17 threat metrics that represent major sources of ecological stress to stream communities into five threat indices: agriculture, urban, point-source pollution, infrastructure, and all non-agriculture threats. We identified stream segments where agriculture management agencies had primary management capacity. Agriculture watershed condition differed by ecoregion and considerable local variation was observed among stream segments in ecoregions of high agriculture threats. Stream segments with high non-agriculture threats were most concentrated near urban areas, but showed high local variability. 60 % of stream segments in the basin were classified as under U.S. Department of Agriculture's Natural Resources Conservation Service (NRCS) primary management capacity and most segments were in regions of high agricultural threats. NRCS primary management capacity was locally variable which highlights the importance of assessing total watershed condition for multiple threats. Our threat indices can be used by agriculture resource management agencies to prioritize conservation actions and investments based on: (a) relative severity of all threats, (b) relative severity of agricultural threats, and (c) and degree of primary management capacity.

Influence of targets and assessment region size on perceived conservation priorities.

We used an existing conservation opportunity area (OA) data layer for four contiguous ecological subsections within the Ozark Highlands to quantitatively evaluate the influence of conservation targets and assessment region size on conservation priorities. OAs are natural and seminatural land-cover patches that are away from roads and away from patch edges. To evaluate the influence of targets, we assigned a priority score to each OA polygon for each of five different conservation targets, including land-cover patch size, landform representation, target vertebrate richness, target breeding bird richness, and target land cover. The top-scoring OAs for each target were added to an OA selection set for that target until 50% of the study area was chosen. These five OA selection sets were overlain to quantify overlap in priorities. Only 1.6% of the study area, or 2.1% of all OA polygons, was selected by all five targets. To evaluate the influence of assessment region size, we compared results of priority ranking of OAs relative to the entire study area against a merged set of priority rankings established separately relative to each of the four subsections within the study area. When high-priority OAs were added until 25% of the region was within the selection set for each of the five targets, the sets based on the whole study area versus each subsection evaluated separately overlapped from 45.4% to 81.9%. Thus, perceived priorities of conservation assessments are strongly influenced both by the targets that are evaluated and by the size of the assessment region.