Use of landscape simulation modeling to quantify resilience for ecological applications

Robert E Keane,Sharon M Hood,Paul F Hessburg,Donald A Falk,Philip Higuera,Rachel A Loehman,Lisa M Holsinger

doi:10.1002/ecs2.2414

Abstract

AbstractGoals of fostering ecological resilience are increasingly used to guide U.S. public land management in the context of anthropogenic climate change and increasing landscape disturbances. There are, however, few operational means of assessing the resilience of a landscape or ecosystem. We present a method to evaluate resilience using simulation modeling. In this method, we use historical conditions (e.g., in North America, prior to European settlement), quantified using simulation modeling, to provide a comparative reference for contemporary conditions, where substantial departures indicate loss of resilience. Contemporary ecological conditions are compared statistically to the historical time series to create a resilience index, which can be used to prioritize landscapes for treatment and inform possible treatments. However, managing for resilience based on historical conditions is tenuous in the Anthropocene, which is characterized by rapid climate change, extensive human land use, altered disturbance regimes, and exotic species introductions. To account for the future variability of ecosystems resulting from climate and disturbance regime shifts, we augment historical simulations with simulations of ecosystem dynamics under projected climate and land use changes to assess the degree of departure from benchmark historical conditions. We use a mechanistic landscape model (FireBGCv2) applied to a large landscape in western Montana, USA, to illustrate the methods presented in this paper. Spatially explicit ecosystem modeling provides the vehicle to generate the historical and future time series needed to quantify potential resilience conditions associated with past and potential future conditions. Our methods show that given selection of a useful set of metrics, managers could use simulations like ours to evaluate potential future management directions.

Highlights

Management for ecological resilience, mandated by some U.S public land policies, is intended to guide land stewardship in a context of profound environmental challenges caused by complex and potentially novel interactions of anthropogenic climate changes, shifting fire regimes, exotic plant, insect, and pathogen invasions, and industrial, agricultural, and urban development (Moritz and Agudo 2013, Joyce et al 2014, Bone et al 2016, Kolb et al 2016, Smith et al 2016, Stephens et al 2016, Schoennagel et al 2017)
The operative assumption of this historical range and variation (HRV)-resilience method is that ecosystems are resilient when they resemble conditions represented by the historical range of variability (HRV), because the HRV represents the recent conditions under which most of the biota have evolved, and under which contemporary ecological communities have formed (Bunnell 1995)
At the core of our method is the use of simulation modeling to quantify the HRV time series, which are compared statistically to current conditions to compute a resilience index

Summary

INTRODUCTION

Management for ecological resilience, mandated by some U.S public land policies, is intended to guide land stewardship in a context of profound environmental challenges caused by complex and potentially novel interactions of anthropogenic climate changes, shifting fire regimes, exotic plant, insect, and pathogen invasions, and industrial, agricultural, and urban development (Moritz and Agudo 2013, Joyce et al 2014, Bone et al 2016, Kolb et al 2016, Smith et al 2016, Stephens et al 2016, Schoennagel et al 2017). As in Seidl et al (2016), we propose to use historical reference conditions as a benchmark for characterizing and quantifying ecological resilience for land management. The concept behind historical range and variation (HRV) is that historical ecosystem characteristics, described by management-relevant variables such as burned area, species composition, or patch size distribution, represent the broad envelope of responses possible for a persistent (resilient) ecosystem under natural perturbations of climate, competitive stress, disturbances, and other stressors (Fig. 1). We describe the use of simulation modeling as a means for generating the reference time series for quantifying HRV that is used to calculate resilience metrics to inform land management. Our approach is intended for scientists and managers who are attempting to integrate measures of ecological resilience into research and land management planning

Background

Findings

SUMMARY