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Institute
The authors demonstrate that a vegetation system's ability to recover from disturbances-its resilience-can be estimated from its natural variability. Global patterns of resilience loss and gains since the early 1990s reveal shifts towards widespread resilience loss since the early 2000s.
The character and health of ecosystems worldwide is tightly coupled to changes in Earth's climate. Theory suggests that ecosystem resilience-the ability of ecosystems to resist and recover from external shocks such as droughts and fires-can be inferred from their natural variability. Here, we quantify vegetation resilience globally with complementary metrics based on two independent long-term satellite records. We first empirically confirm that the recovery rates from large perturbations can be closely approximated from internal vegetation variability across vegetation types and climate zones. On the basis of this empirical relationship, we quantify vegetation resilience continuously and globally from 1992 to 2017. Long-term vegetation resilience trends are spatially heterogeneous, with overall increasing resilience in the tropics and decreasing resilience at higher latitudes. Shorter-term trends, however, reveal a marked shift towards a global decline in vegetation resilience since the early 2000s, particularly in the equatorial rainforest belt.
In semi-arid environments characterized by erratic rainfall and scattered primary production, migratory movements are a key survival strategy of large herbivores to track resources over vast areas. Veterinary Cordon Fences (VCFs), intended to reduce wildlife-livestock disease transmission, fragment large parts of southern Africa and have limited the movements of large wild mammals for over 60 years. Consequently, wildlife-fence interactions are frequent and often result in perforations of the fence, mainly caused by elephants. Yet, we lack knowledge about at which times fences act as barriers, how fences directly alter the energy expenditure of native herbivores, and what the consequences of impermeability are. We studied 2-year ungulate movements in three common antelopes (springbok, kudu, eland) across a perforated part of Namibia's VCF separating a wildlife reserve and Etosha National Park using GPS telemetry, accelerometer measurements, and satellite imagery. We identified 2905 fence interaction events which we used to evaluate critical times of encounters and direct fence effects on energy expenditure. Using vegetation type-specific greenness dynamics, we quantified what animals gained in terms of high quality food resources from crossing the VCF. Our results show that the perforation of the VCF sustains herbivore-vegetation interactions in the savanna with its scattered resources. Fence permeability led to peaks in crossing numbers during the first flush of woody plants before the rain started. Kudu and eland often showed increased energy expenditure when crossing the fence. Energy expenditure was lowered during the frequent interactions of ungulates standing at the fence. We found no alteration of energy expenditure when springbok immediately found and crossed fence breaches. Our results indicate that constantly open gaps did not affect energy expenditure, while gaps with obstacles increased motion. Closing gaps may have confused ungulates and modified their intended movements. While browsing, sedentary kudu's use of space was less affected by the VCF; migratory, mixed-feeding springbok, and eland benefited from gaps by gaining forage quality and quantity after crossing. This highlights the importance of access to vast areas to allow ungulates to track vital vegetation patches.
In semi-arid environments characterized by erratic rainfall and scattered primary production, migratory movements are a key survival strategy of large herbivores to track resources over vast areas. Veterinary Cordon Fences (VCFs), intended to reduce wildlife-livestock disease transmission, fragment large parts of southern Africa and have limited the movements of large wild mammals for over 60 years. Consequently, wildlife-fence interactions are frequent and often result in perforations of the fence, mainly caused by elephants. Yet, we lack knowledge about at which times fences act as barriers, how fences directly alter the energy expenditure of native herbivores, and what the consequences of impermeability are. We studied 2-year ungulate movements in three common antelopes (springbok, kudu, eland) across a perforated part of Namibia's VCF separating a wildlife reserve and Etosha National Park using GPS telemetry, accelerometer measurements, and satellite imagery. We identified 2905 fence interaction events which we used to evaluate critical times of encounters and direct fence effects on energy expenditure. Using vegetation type-specific greenness dynamics, we quantified what animals gained in terms of high quality food resources from crossing the VCF. Our results show that the perforation of the VCF sustains herbivore-vegetation interactions in the savanna with its scattered resources. Fence permeability led to peaks in crossing numbers during the first flush of woody plants before the rain started. Kudu and eland often showed increased energy expenditure when crossing the fence. Energy expenditure was lowered during the frequent interactions of ungulates standing at the fence. We found no alteration of energy expenditure when springbok immediately found and crossed fence breaches. Our results indicate that constantly open gaps did not affect energy expenditure, while gaps with obstacles increased motion. Closing gaps may have confused ungulates and modified their intended movements. While browsing, sedentary kudu's use of space was less affected by the VCF; migratory, mixed-feeding springbok, and eland benefited from gaps by gaining forage quality and quantity after crossing. This highlights the importance of access to vast areas to allow ungulates to track vital vegetation patches.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.