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Quantifying the mitigation of temperature extremes by forests and wetlands in a temperate landscape
(2021)
As a result of ongoing climate change and more frequent heat events, the regulating services of land cover in terms of moderating and mitigating local temperatures are increasingly important. While the reduced temperatures found in forests and wetlands are recognized, their wider contribution to regional landscape cooling remains largely uncharacterized and unquantified. Herein, we propose and test a new method that estimates the temperature response and inertia of landscapes in high temperatures, based on land cover share. In order to achieve this goal, we combined the MODIS daytime land surface temperature (henceforth LST) time series and CORINE land cover data. We classified the time series in two ways, i.e. by stepwise temperature range (−10/−5 °C to +35/+40 °C) and by the occurrence of hot days (days with a mean LST ≥ 30 °C). As an explanatory variable, we developed and used a greenest pixel composite of the MODIS normalized difference vegetation index (NDVI) time series. In our study area, covering parts of northeastern Germany and western Poland, the fragmented landscape has heterogeneous temperature patterns, including urban heat islands, warm agricultural areas, cool forests and cold wetlands. We found that at high temperature ranges only forests and wetlands remained comparably cool, with LSTs up to 20.8 °C lower than the maximum LST in the study area. The analysis of land cover shares and LSTs revealed the substantial cooling effect of forests and wetlands in line with increasing land cover share in higher temperature ranges, as well as on hot days. The relation between LST and the NDVI indicated vegetation cover as the cause. We propose the corresponding metrics to quantify landscape-level temperature regulation. Equally, we advocate for management to identify these ecosystem services and their current and potential contributions, along with implications for sustaining and increasing, both tree cover and wetlands and thereby adapting landscapes to climate change.
The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.