Identifying management‐driven dynamics in vegetation cover: Applying the Compere framework to Cooper Creek, Australia

Abstract

The observed spatial and temporal dynamics in landscape and ecosystem resources are the net effects of natural processes and management activities. Monitoring the impact that humans have on these resources requires that these two sources of variability be partitioned, removing the natural variability to reveal variability due to management activities. Here, we present Compere, a relative benchmarking framework for monitoring the management‐driven impacts on ecosystem resources. The framework identifies locations in a region that share similar biophysical properties to a target location. Taking an attribute of interest, it then compares the value of the target location with those of all its biophysically equivalent locations, with any differences being attributed to variations in management. We provide an example application of Compere, using satellite‐derived vegetation cover data to examine the impact of hydrocarbon extraction activities on land condition (as described by vegetation cover) across the 490,000‐km2 Cooper Creek region in arid central Australia. Validation was performed by comparing land condition estimates to known disturbance patterns across the region. We found that the establishment of well sites was associated with between 12% and 41% decreases in land condition but that condition recovered to original levels by 6 years after establishment. We also found that fires had much larger and longer lasting effects on land condition across these landscapes, indicating that mining‐related activities that change fire patterns are likely to affect land condition most. Compere is a generic, flexible framework, providing a new capability for monitoring management impacts on multiple types of ecosystem resources.

Monitoring of sustainable land management using remotely sensed vegetation cover and variable tolerable soil erosion targets across New South Wales, Australia

“…We believe our scheme has advantages over methods that solely use changes in remotely sensed vegetation cover as a surrogate for land management, even the more recent innovative schemes that apply relative benchmarking as a means to distinguish land management components from natural climatic and land condition causes of changes in vegetation cover (Bastin et al, 2012(Bastin et al, , 2014Donohue et al, 2022;Hobbs et al, 2018;Nauman et al, 2017). These schemes would seem to be hindered by difficulties in identifying sufficient reference areas with equivalent climatic, topographic and soil conditions to allow meaningful interpretation of changes in vegetation changes in the target areas of interest.…”

“…An ongoing issue with such vegetation cover monitoring schemes has been how to effectively distinguish between changes arising from (i) natural influences such as climatic (weather), topographic and soil factors and (ii) land management influences such as stocking rates. To identify the land management influences, recent innovative schemes have applied a 'relative benchmarking' approach, where the vegetation cover over target pixels is compared in an automated process to the vegetation cover over nearby reference sites that represent minimally disturbed and preferably physically equivalent locations (Bastin et al, 2012(Bastin et al, , 2014Donohue et al, 2022;Hobbs et al, 2018;Nauman et al, 2017). Whilst providing valuable data and insights into land management over their subject areas, these approaches have difficulties and limitations in effectively identifying equivalent reference sites to meaningfully compare with the target sites.…”

Do regenerative grazing management practices improve vegetation and soil health in grazed rangelands? Preliminary insights from a space-for-time study in the Great Barrier Reef catchments, Australia

“…Then, more innovative methods for benchmarking changes owing to management can be applied at property and regional scale (e.g. Donohue et al 2022). It is noted that commercial methods to estimate pasture biomass have recently become available (e.g.…”

Applying Remote Sensing Methods to Estimate Alterations in Land Cover Change and Degradation in the Desert Regions of the Southeast Iberian Peninsula

“…Since the radial pattern around watering points is clearly visible from satellite imagery, recent studies have been conducted by interpreting and modeling the remote sensing data [13,14], which can be processed in a semi-automated and repeatable manner over large and distant regions. For this reason, different remote-sensing models that utilize geographic information systems techniques have been created to calculate the spatial spread of various elements in the vicinity of watering points [5,[13][14][15].…”