Quantifying ecological variation across jurisdictional boundaries in a management mosaic landscape

Abstract

Context Large landscapes exhibit natural heterogeneity. Land management can impose additional variation, altering ecosystem patterns. Habitat characteristics may reflect these management factors, potentially resulting in habitat differences that manifest along jurisdictional boundaries.

Objectives We characterized the patchwork of habitats across a case study landscape, the Grand Canyon Protected Area-Centered Ecosystem. We asked: how do ecological conditions vary across different types of jurisdictional boundaries on public lands? We hypothesized that differences in fire and grazing, because they respond to differences in management over time, contribute to ecological differences by jurisdiction.

Methods We collected plot-scale vegetation and soils data along boundaries between public lands units surrounding the Grand Canyon. We compared locations across boundaries of units managed differently, accounting for vegetation type and elevation differences that pre-date management unit designations. We used generalized mixed effects models to evaluate differences in disturbance and ecology across boundaries.

Results Jurisdictions varied in evidence of grazing and fire. After accounting for these differences, some measured vegetation and soil properties also differed among jurisdictions. The greatest differences were between US Forest Service wilderness and Bureau of Land Management units. For most measured variables, US Forest Service non-wilderness units and National Park Service units were intermediate.

Conclusions In this study, several ecological properties tracked jurisdictional boundaries, forming a predictable patchwork of habitats. These patterns likely reflect site differences that pre-date jurisdictions as well as those resulting from different management histories. Understanding how ecosystem differences manifest at jurisdictional boundaries can inform resource management, conservation, and cross-boundary collaborations.