We found widespread increases in cover and production of annual grasses and forbs, declines in herbaceous perennial cover, and expansion of trees. Cover and production of annual plants now exceed that of perennials on > 21 million ha of BLM rangeland, marking a fundamental shift in the ecology of these lands. This trend was most dramatic in the Western Cold Desert of Nevada and parts of surrounding states where aboveground production of annuals has more than tripled. Trends in annuals were negatively correlated with trends in bare ground but not with trends in perennials, suggesting that annuals are filling in bare ground rather than displacing perennials. Tree cover increased in half of ecoregions affecting some 44 million ha and underscoring the threat of woodland expansion for western rangelands. A multiscale variance partitioning analysis found that trends often varied the most at the finest spatial scale. This result reinforces the need to combine plot-level field data with moderate-resolution remote sensing to accurately quantify vegetation changes in heterogeneous rangelands. The long-term changes in vegetation on public rangelands argue for a more hands-on approach to management, emphasizing preventative treatment and restoration to preserve rangeland habitat and functioning. Our work shows the power of new remote-sensing tools for monitoring public rangelands and developing effective strategies for adaptive management and conservation.
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This tool is called the Climate and Economic Justice Screening Tool. The tool has an interactive map and uses datasets that are indicators of burdens in eight categories: climate change, energy, health, housing, legacy pollution, transportation, water and wastewater, and workforce development. The tool uses this information to identify communities that are experiencing these burdens. These are the communities that are disadvantaged because they are overburdened and underserved.
We sought to forecast future shifts in rangeland growing season timing due to climate change, and interpret their importance for land management and ecosystem function. We trained a model on remotely sensed land surface phenology and climate data collected from 2001 to 2014 in temperate United States rangelands. We used this model to forecast annual growing season start dates, end dates, and season length through 2099 among six general circulation models and under RCP 4.5 and 8.5 scenarios. Growing season start was projected to shift earlier throughout our study area. In 2090-2099, start of season advanced by an average of 10 (RCP 4.5) to 17 (RCP 8.5) days. End of season also advanced by 12 (RCP 4.5) to 24 (RCP 8.5) days, but with greater heterogeneity. Start and end of season change mainly offset one another, so growing season length changes were lesser (2 days in RCP 4.5, and 7 in RCP 8.5). Some mountainous areas experienced both earlier start of season and later end of season, lengthening their growing season. Earlier phenology in rangelands would force adaptation in grazing and impact ecosystem function. Mountainous areas with earlier start and later end of season may become more viable for grazing, but most areas may experience slightly shortened growing seasons. Autumn phenology warrants greater research, and our finding of earlier autumn senescence contradicts some prior research.
The magnitude of impact of tree encroachment on rangeland loss is similar to conversion to cropland, another well-known and primary mechanism of rangeland loss in the US Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion.
We organize our exploration of new horizons around three key areas, suggesting that PODs can enable climate-smart forest and fire management and planning, inform more agile and adaptive allocation of suppression resources, and enable risk-informed performance measurement. These efforts can be synergistic and self-reinforcing, and we argue that expanded application of PODs at local levels could enhance the performance of the broader wildland fire system. We provide rationales for each problem area and offer growth opportunities with attendant explanations and illustrations.
We created a novel, multiple-region, N-mixture community model (MNCM) to examine the relations of riparian area and fragmentation with species richness of breeding birds in mountain ranges within the Great Basin, Nevada, USA. Projections of future riparian contraction suggested that decreases in species richness are likely to be greatest in canyons that currently have moderate (~10–25 ha) amounts of riparian vegetation. Our results suggest that if a goal of management is to maximize the species richness of breeding birds in montane riparian areas in the Great Basin, it may be more effective to focus on total habitat area than on fragmentation of patches within canyons, and that canyons with at least moderate amounts of riparian vegetation should be prioritized.
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Wildfire risk, species conservation, and ecosystem management all depend on seamless spatial data. LANDFIRE may already be supporting your mission if you have ever asked questions like these:
- What is the wildfire risk within a particular landscape?
- Where can I get data to evaluate fauna habitats?
- If ignited, how might a wildfire move through a particular landscape?
- How does the vegetation cover in one area compare with the vegetation in another area?
- How have disturbances in the past affected current forest conditions?
- What is the spatial distribution of a certain vegetation type?
- Where can I find spatial vegetation and structure data for all lands, regardless of ownership?
National LANDFIRE datasets can help answer all these questions for areas of interest within the United States and insular areas at the 30-meter pixel level. LANDFIRE is a Federal program that provides a suite of spatial datasets indicating areas of disturbance, vegetation and fuels distributions and structure, and historical conditions. Although LANDFIRE is the definitive dataset used by the interagency fire community for surface and canopy fuels, the program also maps more than 30 spatial datasets that can be used for a variety of purposes.