New research highlights how remote sensing tools accurately and efficiently detail conservation outcomes on rangelands.
Resilient grass and shrub lands support rural economies, store carbon, and provide habitat for a diverse set of wildlife. Tracking and measuring conservation-derived improvements to these ecosystem services is a critical component of restoring and perpetuating healthy rangelands, which encompass more than a third of the U.S.
For decades, accurately and efficiently measuring conservation outcomes across millions of acres of rangelands has been costly, time consuming, and difficult. This is especially true when measuring the response of vegetation to on-the-ground conservation actions. Additionally, traditional plot-level sampling often failed to capture fine-scale variations in vegetation change in response to management practices that are common across pasture, ranch, and watershed scales.
Spatial technologies, like the Rangelands Analysis Platform provide “wall-to-wall” measurements of vegetation biomass across all U.S. rangelands. These remotely sensed datasets are updated regularly and put decades of historic data at researchers’ fingertips. These tools have the potential to provide accurate, efficient, and meaningful evaluations of conservation outcomes, but until recently, this capacity had not been scientifically quantified and evaluated.
New research from Caleb Roberts, a Working Lands for Wildlife-affiliated researcher with the United States Geological Survey, tested whether modern remote sensing tools and datasets can accurately and efficiently quantify vegetation responses and fine-scale variations at different spatial scales following three commonly used rangeland conservation treatments – prescribed fire, tree removal, and prescribed grazing.
Roberts and his team found that next-generation technologies can measure nuanced conservation outcomes accurately and at multiple spatial scales. This capacity unlocks analyses and rapid-response adaptive management opportunities that were impossible with historic field-based monitoring. Additionally, using remote sensing technology to assess conservation outcomes can improve communication of the importance, and effectiveness, of rangeland conservation to diverse stakeholders. This research empowers scientists to employ remote sensing by providing multiple examples of new and exciting ways to quantify outcomes of conservation actions that are so desperately needed for rangelands today.
Spatial technologies are at the core of WLFW’s approach to rangeland conservation in sagebrush country and the Great Plains. Remotely sensed, spatially specific datasets, maps, and planning tools detail core areas where proactive, preventative conservation can prevent grassland losses, while also enabling the type of monitoring and outcome reporting featured in this paper. Learn more about how spatial technologies are foundational to our work.
Abstract: Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing. In Oregon’s sagebrush steppe, for example, juniper tree removal resulted in a 21% increase in one pasture’s productivity and an 18% decline in another. In Nebraska’s Loess Canyons, perennial grass productivity initially declined 80% at sites invaded by trees that were prescriptively burned, but then fully recovered post-fire, representing a 492% increase from nadir. In Kansas’ Shortgrass Prairie, plant biomass increased 4-fold (966,809 kg/ha) in pastures that were prescriptively grazed, with gains highly dependent upon precipitation as evidenced by sensitivity of remotely sensed estimates (SD ± 951,308 kg/ha). Our results emphasize that next-generation remote sensing datasets empower land managers to move beyond simplistic control versus treatment study designs to explore nuances in plant biomass in unprecedented ways. The products of new remote sensing technologies also accelerate adaptive management and help communicate wildlife and livestock forage benefits from management to diverse stakeholders.
Citation: Roberts, C.P. Roberts, D.E. Naugle, B.W. Allred, V.M. Donovan, D.T. Fogarty, M.O. Jones, J.D. Maestas, A.C. Olsen, and D. Twidwell. 2022. Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes. Journal of Environmental Management 2022, 324:116359.
Acknowledgements: Funding was provided by the National Science Foundation (OIA-1920938), United States Department of Agriculture – Natural Resources Conservation Service and Pheasants Forever (PG18-62799-01 and Sage Grouse Initiative 2.0-19-06), Nebraska Game & Parks Commission (W-125-R-1), US Department of Agriculture NIFA AFRI (M1903198), the University of Nebraska Agricultural Research Division, and the Department of Biological Sciences at the University of Arkansas. This work was made possible by the NRCS Working Lands for Wildlife in support of sage-grouse and prairie-chicken conservation and the USDA Conservation Effects Assessment Project-Wildlife Component and Arkansas Game and Fish Commission through cooperative agreement 1434-04HQRU1567.