Quantification of the Ecological Resilience of Drylands Using Digital Remote Sensing

Abstract

ABSTRACT. Drylands cover 41% of the terrestrial surface and support > 36% of the world's population. However, the magnitude of dryland degradation is unknown at regional and global spatial scales and at 15-30-yr temporal scales. Historical archives of > 30 yr of Landsat satellite imagery exist and allow local to global monitoring and assessment of a landscape's natural resources in response to climatic events and human activities. Vegetation indices (VIs), i.e., proxies of vegetation characteristics such as phytomass, can be derived from the spectral properties of Landsat imagery. A dynamical systems analysis method called mean-variance analysis can be used to describe and quantify dynamic regimes of VI response to disturbance using characteristics of ecological resilience, particularly amplitude and malleability, from a change detection perspective. Amplitude is the magnitude of response of a VI to a disturbance; malleability is the degree of recovery of a resource after a disturbance. Spatially aggregate and spatially explicit (image) differencing are methods whereby a VI image or statistic from one time period is subtracted from a VI image or statistic from another time period. To illustrate this method, we used a time series of Landsat imagery from 1972 to 1987 to measure the response of vegetation communities that are managed by subsistence agropastoral communities to the severe 1982-1984 El Niño-induced drought on the Bolivian Altiplano. We found that the entire landscape had decreased vegetation cover, increased variance (diagnostic of a regime shift), and thus, increased susceptibility to soil erosion during the drought. The wet meadow vegetation cover class had the lowest amplitude and thus the most resilience relative to other vegetation cover classes. This response identified the wet meadow as a key resource, as well as a harbinger of climate change for agropastoral communities in areas where drought is an endemic stressor.

Macroecological Patterns of Resilience Inferred from a Multinational, Synchronized Experiment

“…There is concern that eutrophication and water level changes will influence patterns of structure and processes in shallow lakes [3][4][5]. However, our results, together with findings from previous research [34,77], suggest that unless persistent dry spells caused by a state shift in meteorological and climatological settings on a regional scale, resilience attributes of shallow lakes may be otherwise little affected by changing water levels or trophic state conditions at least within our studied range. In practice, this means that drought mitigation and natural resource management might be especially challenging in arid and semi-arid countries in the future, because as our study suggests, these effects can be spatially contingent and difficult to predict [70,71,87].…”

“…This is at odds with the expectation that communities operate in a single broad basin of attraction and also with the finding that the Turkish zooplankton did not undergo such a shift, despite having suffered drawdown. However, Angeler et al [34] and Washington-Allen et al [77] found that severe drought events over prolonged periods of time (i.e., supra-seasonal droughts), a consequence of climate change [78,79] especially in arid countries [80], trigger nonlinear state shifts in hydrological functioning and biological communities. Such changes have also been documented in other studies [81][82][83][84].…”

Changes in carbon storage with land management promoted by payment for ecosystem services

“…Bofedales provide vital dry season grazing, and increased bofedal vegetation due to check dams can contribute to grazing stability (Preston et al 2002;Washington-Allen et al 2008). The increased standing water associated with check dams also has implications for water security in arid and semiarid lands (Scott et al 2013), contributing to groundwater recharge and stabilization of downstream water flows (Bouwer 2002).…”

“…Bofedales are particularly sensitive to changes in hydrology induced by gully erosion or prolonged drought (Earle et al 2003;Moreau & Toan 2003;Squeo et al 2006;Washington-Allen et al 2008). Bofedal degradation impacts local livelihoods, as they are a vital source of dry season grazing for llamas and sheep.…”

Spatio-Temporal Analysis of Vegetation Dynamics in Relation to Shifting Inundation and Fire Regimes: Disentangling Environmental Variability from Land Management Decisions in a Southern African Transboundary Watershed

“…Informed by work by Pickup and Foran [34] and more recent work [35][36][37][38], we used mean-variance analysis, a form of graphical dynamical systems analysis previously used successfully in dry land ecosystems with remotely-sensed data. Mean-variance analyses are based on established empirical relationships that show that the location of statistical vegetation parameters such as mean and variance in a Cartesian space can be correlated to field measurements of vegetation heterogeneity, homogeneity and overall vegetation productivity.…”