Tree cover change data

% woody cover as measured from aerial photographs using Definiens ECognition between 1940 - 2010. Each data point represents cover measured across 4 common land uses (conservation areas without elephants, conservation areas with elephants, communal rangelands, and cattle ranches) in untransformed savannas sites across north-eastern South Africa

Retrieval of savanna vegetation canopy height from ICESat-GLAS spaceborne LiDAR with terrain correction

Light detection and ranging (LiDAR) remote sensing enables accurate estimation and monitoring of vegetation structural properties. Airborne and spaceborne LiDAR is known to provide reliable information on terrain elevation and forest canopy height over closed forests. However, it has rarely been used to characterize savannas, which have a complex structure of trees coexisting with grasses. This letter presents the first validation of spaceborne Ice Cloud and land Elevation Satellite Geoscience Laser Altimeter System (GLAS) full-waveform data to retrieve savanna vegetation canopy height that uses field data specifically collected within the GLAS footprints. Two methods were explored in the Kruger National Park, South Africa: one based on the Level 2 Global Land Surface Altimetry Data product and the other using Level 1A Global Altimetry Data (GLA01) with terrain correction. Both methods use Gaussian decomposition of the full waveform. Airborne LiDAR (AL) was also used to quantify terrain variability (slope) and canopy height within the GLAS footprints. The canopy height retrievals were validated with field observations in 23 GLAS footprints and show that the direct method works well over flat areas (Pearson correlation coefficient r = 0.70, p<0.01, and n = 8 for GLA01) and moderate slopes (r = 0.68, p<0.05, and n = 9 for GLA01). Over steep slopes in the footprint, however, the retrievals showed no significant correlation and required a statistical correction method to remove the effect of terrain variability on the waveform extent. This method improved the estimation accuracy of maximum vegetation height with correlations (R[superscript 2] = 0.93, p<0.05, and n = 6 using the terrain index (g) generated from AL data and R[superscript 2] = 0.91, p<0.05, and n = 6 using the GLAS returned waveform width parameter). The results suggest that GLAS can provide savanna canopy height estimations in complex tree/grass plant communities

Data for "Pyrodiversity interacts with rainfall to increase bird and mammal richness in African savannas" DOI 10.1111/ele.12921

These files contain the data analysed in the paper Pyrodiversity interacts with rainfall to increase bird and mammal richness in African savannas" DOI 10.1111/ele.12921 by the same authors, published in Ecology Letters in 2018. The files detail the richness of savanna dwelling bird and mammal species in 1/2 degree grid cells across Africa. Fire data (including the pyrodiversity scores used) are available from <a href="http://dx.doi.org/10.5061/dryad.26sb5" target="_blank">http://dx.doi.org/10.5061/dryad.26sb5</a> . A full list of the bird and mammal species included and the sources of the raw distribution data is provided in supplementary material for the paper.<div><br></div><div>All files are geotiffs. savBirds.tif contains the bird richness pattern, BirdsTop25.tif the richness of the commonest 25% of species, BirdsBot25.tif the richness of the rarest 25% of species, richness patterns for mammals are in files mamm.richness.tif (all species), rich.sav.mammlight.tif (small mammals), rich.sav.mammheavy.tif (large mammals), rich.bats.tif (bats), 02.mamm.top25.new.tif (common mammals), 03.mamm.bot25.new.tif (rare mammals).</div

Natural Hazards in a Changing World: A Case for Ecosystem-Based Management

<div><p>Communities worldwide are increasingly affected by natural hazards such as floods, droughts, wildfires and storm-waves. However, the causes of these increases remain underexplored, often attributed to climate changes or changes in the patterns of human exposure. This paper aims to quantify the effect of climate change, as well as land cover change, on a suite of natural hazards. Changes to four natural hazards (floods, droughts, wildfires and storm-waves) were investigated through scenario-based models using land cover and climate change drivers as inputs. Findings showed that human-induced land cover changes are likely to increase natural hazards, in some cases quite substantially. Of the drivers explored, the uncontrolled spread of invasive alien trees was estimated to halve the monthly flows experienced during extremely dry periods, and also to double fire intensities. Changes to plantation forestry management shifted the 1∶100 year flood event to a 1∶80 year return period in the most extreme scenario. Severe 1∶100 year storm-waves were estimated to occur on an annual basis with only modest human-induced coastal hardening, predominantly from removal of coastal foredunes and infrastructure development. This study suggests that through appropriate land use management (e.g. clearing invasive alien trees, re-vegetating clear-felled forests, and restoring coastal foredunes), it would be possible to reduce the impacts of natural hazards to a large degree. It also highlights the value of intact and well-managed landscapes and their role in reducing the probabilities and impacts of extreme climate events.</p></div

Wave run-up elevations for various storm-wave return intervals for different scenarios of beach slope and climate change.

<p>Simulations used here are for a typical sandy beach location in Eden (Tergniet, near Mossel Bay), which is prone to storm-wave damage. Return periods were based on the simulated wave run-up elevations for a south-south westerly swell, and spring high tide levels. The numbers prefixing the annotated description of each scenario provides a reference to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095942#pone-0095942-t001" target="_blank">Table 1</a>, which describes each scenario in more detail.</p

Flood return intervals for different scenarios of land cover and climate change.

<p>The numbers prefixing the annotated description of each scenario provides a reference to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095942#pone-0095942-t001" target="_blank">Table 1</a>, which describes each scenario in more detail. The changes in the values for each return interval illustrate the potential changes in the likelihood of extreme flow events under the different scenarios. For example, the return period of a flood with a daily flow of 150 mm (similar to the May 1981 flood in this area) would decrease from a baseline of more than 100 years to 70 years under future climate (scenario 5).</p

Flow duration curve for different scenarios of land cover and climate change.

<p>This shows the cumulative proportion of the months where a flow exceeded a given discharge for the different scenarios. The numbers prefixing the annotated description of each scenario provides a reference to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095942#pone-0095942-t001" target="_blank">Table 1</a>, which describes each scenario in more detail. Extreme low flows were defined as those with >90% exceedance, which were used in this study to represent severe drought conditions. A log-normal probability curve was used to allow the low and high flow ends of the plot to be more clearly displayed.</p

The location of the hazard model study areas within Eden.

<p>The inset showing the location of Eden in South Africa.</p

The African Regional Greenhouse Gases Budget (2010–2019)

As part of the REgional Carbon Cycle Assessment and Processes Phase 2 (RECCAP2) project, we developed a comprehensive African Greenhouse gases (GHG) budget covering 2000 to 2019 (RECCAP1 and RECCAP2 time periods), and assessed uncertainties and trends over time. We compared bottom‐up process‐based models, data‐driven remotely sensed products, and national GHG inventories with top‐down atmospheric inversions, accounting also for lateral fluxes. We incorporated emission estimates derived from novel methodologies for termites, herbivores, and fire, which are particularly important in Africa. We further constrained global woody biomass change products with high‐quality regional observations. During the RECCAP2 period, Africa's carbon sink capacity is decreasing, with net ecosystem exchange switching from a small sink of −0.61 ± 0.58 PgC yr−1 in RECCAP1 to a small source in RECCAP2 at 0.16 (−0.52/1.36) PgC yr−1. Net CO2 emissions estimated from bottom‐up approaches were 1.6 (−0.9/5.8) PgCO2 yr−1, net CH4 were 77 (56.4/93.9) TgCH4 yr−1 and net N2O were 2.9 (1.4/4.9) TgN2O yr−1. Top‐down atmospheric inversions showed similar trends. Land Use Change emissions increased, representing one of the largest contributions at 1.7 (0.8/2.7) PgCO2eq yr−1 to the African GHG budget and almost similar to emissions from fossil fuels at 1.74 (1.53/1.96) PgCO2eq yr−1, which also increased from RECCAP1. Additionally, wildfire emissions decreased, while fuelwood burning increased. For most component fluxes, uncertainty is large, highlighting the need for increased efforts to address Africa‐specific data gaps. However, for RECCAP2, we improved our overall understanding of many of the important components of the African GHG budget that will assist to inform climate policy and action.</p

The African Regional Greenhouse Gases Budget (2010–2019)

As part of the REgional Carbon Cycle Assessment and Processes Phase 2 (RECCAP2) project, we developed a comprehensive African Greenhouse gases (GHG) budget covering 2000 to 2019 (RECCAP1 and RECCAP2 time periods), and assessed uncertainties and trends over time. We compared bottom‐up process‐based models, data‐driven remotely sensed products, and national GHG inventories with top‐down atmospheric inversions, accounting also for lateral fluxes. We incorporated emission estimates derived from novel methodologies for termites, herbivores, and fire, which are particularly important in Africa. We further constrained global woody biomass change products with high‐quality regional observations. During the RECCAP2 period, Africa's carbon sink capacity is decreasing, with net ecosystem exchange switching from a small sink of −0.61 ± 0.58 PgC yr−1 in RECCAP1 to a small source in RECCAP2 at 0.16 (−0.52/1.36) PgC yr−1. Net CO2 emissions estimated from bottom‐up approaches were 1.6 (−0.9/5.8) PgCO2 yr−1, net CH4 were 77 (56.4/93.9) TgCH4 yr−1 and net N2O were 2.9 (1.4/4.9) TgN2O yr−1. Top‐down atmospheric inversions showed similar trends. Land Use Change emissions increased, representing one of the largest contributions at 1.7 (0.8/2.7) PgCO2eq yr−1 to the African GHG budget and almost similar to emissions from fossil fuels at 1.74 (1.53/1.96) PgCO2eq yr−1, which also increased from RECCAP1. Additionally, wildfire emissions decreased, while fuelwood burning increased. For most component fluxes, uncertainty is large, highlighting the need for increased efforts to address Africa‐specific data gaps. However, for RECCAP2, we improved our overall understanding of many of the important components of the African GHG budget that will assist to inform climate policy and action.</p