Abstract
An explicit link between the abiotic environment, the biotic components of ecosystems, and resilience to disturbance across multiple scales is needed to operationalize the concept of ecological resilience. To accomplish this, managers must be able to measure the ecological resilience of current conditions and project resilience under future scenarios of landscape change. The goal of this paper is to present metrics and describe a process for using geospatial data, landscape pattern analysis and landscape dynamic simulation modeling to evaluate ecosystem resilience at management scales. The dynamic equilibria of species abundances, community structure, and landscape patterns that are produced under a given combination of abiotic conditions, such as topography, soils, and climate, can form a foundation to define desired conditions and measure resistance and resilience. The degree of forcing required to push the system from this dynamic range is a measure of resistance, and the rate of return to the dynamic range after the perturbation is a measure of the resilience and recovery of the system. Several tools from the field of landscape ecology are useful in defining the dynamic range of an ecosystem under natural regulation and to measure the forcing required to drive departure and the rate of recovery. Simulation models provide means to quantify the expected range of species abundance, community structure, and landscape patterns under a variety of scenarios, including the natural disturbance regime, current disturbance regime, and possible future regimes under alternative management and climate scenarios. Landscape pattern analysis and multivariate trajectory analysis provide a means to quantify conditions and change vectors relative to this desired range. Together this combination of tools provides a means to define the conditions of a desired state for an ecosystem, to quantify the degree of resistance and resilience of the system to perturbation, and to measure and monitor the departure from the range of natural variability in the system dynamics.
Highlights
Ecological resilience is a measure of the amount of perturbation required to change an ecosystem from one set of processes and structures to a different set of processes and structures, or the amount of disturbance that a system can withstand before it shifts into a new regime or alternative stable state (Holling, 1973; Curtin and Parker, 2014)
Landscape dynamic simulation modeling provides means to quantify the expected range of species abundance, community structure and landscape patterns under natural regulation (e.g., Costanza and Voinov, 2004; Littell et al, 2011). Tools such as landscape pattern analysis (McGarigal et al, 2012), direct and indirect community ordination (TerBraak and Prentice, 1988; Cushman and McGarigal, 2002; Ohmann and Gregory, 2002), and multivariate trajectory analysis (Cushman and McGarigal, 2007) provide a means to quantify conditions and change vectors relative to resilient desired conditions. Together this combination of tools provides a means to define the conditions of a desired state for a healthy ecosystem and to quantify the degree of resistance and resilience of the system to perturbation, and to measure and monitor the departure from these conditions relative to the range of natural variability in the system dynamics
We focus on three questions: (1) What is the historic range of variation in landscape structure in the sample landscape? (2) What is current degree of departure of the current landscape condition from that historic range of variability, and how do these things change with the spatial scale of the landscape under consideration? (3) How readily does the landscape pattern recover to within the HRV after the reimposition of the historic disturbance regime
Summary
Ecological resilience is a measure of the amount of perturbation required to change an ecosystem from one set of processes and structures to a different set of processes and structures, or the amount of disturbance that a system can withstand before it shifts into a new regime or alternative stable state (Holling, 1973; Curtin and Parker, 2014). More recently research has focused on the ability of systems to maintain fundamental structures, processes, and functioning following disturbances (Folke et al, 2010) This so-called general resistance concept is widely applied to evaluate responses ecosystems and landscapes, and to predict which systems are most vulnerable to transitions to alternative states (e.g., Hirota et al, 2011; Brooks et al, 2016; Levine et al, 2016), based on the relationships among an ecosystem’s attributes and its responses to stressors and disturbances (Chambers et al, 2014a,b, 2017a,b)
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