Data and code for "Soil as a Reservoir of Multi Annual Rainfall Determining Semiarid Vegetation Productivity"

<p><strong>Soil as a Reservoir of Multi Annual Rainfall Determining Semiarid Vegetation Productivity (Fux, Svoray &amp; Bell, 2024)</strong></p> <p><strong>Abstract</strong><br>Climate change and natural variability alter rainfall characteristics. In dry environments, these changes&nbsp;<br>affect vegetation productivity, however, studies of remotely sensed data in high resolution temporal are scarce.&nbsp;<br>We quantified daily scale rainfall-productivity relationships by analyzing daily time series of rainfall and NDVI&nbsp;<br>from Landsat and Sentinel imagery from Israel, New Mexico, and SW Australia. Methodologically wise, we found that&nbsp;<br>the representative area size varied from 0.02--0.14 \(Km^2\), depending on the uniformity of vegetation formations.&nbsp;<br>More substantive, herbaceous vegetation showed maximal response to 3--4 months cumulative rainfall, while woody&nbsp;<br>vegetation response is dominated by rainfall accumulated over a year and even longer periods. These results emphasize&nbsp;<br>the water reservoirs' significance upon intermittent rainfall events and may have implications for ecohydrological&nbsp;<br>modeling, conservation biology, and ecosystem management.</p> <p><strong>Plain Language Summary</strong><br>Dry environments are characterized by high rainfall variability and water scarcity sets it as a limiting factor for&nbsp;<br>vegetation growth. Yet, vegetation response to rainstorms in semiarid regions is not fully understood. Specifically,&nbsp;<br>it is unclear what dominant statistical characteristic of rainstorms dictates vegetation growth. It has been long&nbsp;<br>debated whether daily, seasonal or annual rainfall characteristics are crucial for triggering vegetation&rsquo;s response.&nbsp;<br>Here, we used high-resolution satellite images and daily rainfall records, from three locations worldwide, to&nbsp;<br>investigate the rainfall-productivity relationship. We found that for most vegetation formations, maximal correlation&nbsp;<br>is obtained for no lag and seasonal, or longer, rainfall accumulation periods. These results suggest that vegetation&nbsp;<br>does not show a significant response to rainfall pulses but rather to accumulated rainfall over longer periods (even&nbsp;<br>years). Thus, accumulated rainfall is likely stored in soil water reservoirs and remains accessible to ecosystems.&nbsp;<br>These results are more pronounced in woody vegetation and should be considered for environmental management policies.</p> <p><strong>Description</strong><br>The compressed file contains two folders, one for the characteristic unit size test and one for the rainfall-NDVI&nbsp;<br>cross correlations.<br>The unit size folder contains NDVI images for the dates used to calculate the characteristic unit size, the shape&nbsp;<br>files of the polygons used to delineate the different vegetation types areas and the R code.<br>The rainfall-NDVI cross correlations folder contain the NDVI images for each vegetation type in each region,&nbsp;<br>processed from the original data, and the code for creating the detrended and summed rainfall time series, the&nbsp;<br>detrended NDVI time series and the cross-correlation analyses.<br>The rainfall and the original satellite data are available from the resources listed in the article.</p>