Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes. (15th December 2022)

• Record Type: Journal Article
• Authors: Roberts, Caleb P.; Naugle, David E.; Allred, Brady W.; Donovan, Victoria M.; Fogarty, Dillon T.; Jones, Matthew O.; Maestas, Jeremy D.; Olsen, Andrew C.; Twidwell, Dirac
• Is Part Of: Journal of environmental management. Volume 324(2022)
• Publication Date: 2022-12-15
• Subjects: Adaptive management -- Monitoring -- Private lands conservation -- Remote sensing -- restoration -- Scale; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2022.116359
• Languages: English
• ISSNs: 0301-4797

Abstract

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. Highlights: New plant productivity datasets empower monitoring at scales from pixels to biomes. New productivity datasets captured heterogeneity in management outcomes. We can consistently quantify fire, grazing, and tree removal management outcomes. New remote sensing datasets can rapidly inform adaptive management.