title: Scaling up the diversity-resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire.
abstract: Understanding the mechanisms underlying ecosystem resilience - why some systems have an irreversible response to disturbances while others recover - is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large-scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small-scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four-corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local-scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues.
authors.affiliation: Department of Biology and Tyson Research Center, Washington University in St. Louis, St. Louis, MO, 63130, USA.
authors.forename: Marko J
authors.initials: MJ
authors.lastname: Spasojevic
authors.affiliation: Department of Entomology and Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, 48915, USA.
authors.forename: Christie A
authors.initials: CA
authors.lastname: Bahlai
authors.affiliation: Department of Environmental Conservation, University of Massachusetts, Amherst, MA, 01003, USA.
authors.forename: Bethany A
authors.initials: BA
authors.lastname: Bradley
authors.affiliation: Department of Biological Sciences and Merriam-Powell Center for Environmental Research, Northern Arizona University, Flagstaff, AZ, 86011-5640, USA.
authors.forename: Bradley J
authors.initials: BJ
authors.lastname: Butterfield
authors.affiliation: Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA.
authors.forename: Mao-Ning
authors.initials: MN
authors.lastname: Tuanmu
authors.affiliation: Department of Ecology & Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA.
authors.forename: Seeta
authors.initials: S
authors.lastname: Sistla
authors.affiliation: School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA.
authors.forename: Ruscena
authors.initials: R
authors.lastname: Wiederholt
authors.affiliation: Department of Environmental Science, Policy & Management, University of California Berkeley, Berkeley, CA, USA.
authors.forename: Katharine N
authors.initials: KN
authors.lastname: Suding
mesh_terms: D044822:Biodiversity; D016208:Databases, Factual; D005390:Fires; D065928:Forests; D008962:Models, Theoretical; D058998:Remote Sensing Technology; D014481:United States
keywords: Landfire; MODIS; NatureServe; fire resistance; fire tolerance; functional diversity; path analysis; resprout ability; seed mass; southwest United States