DOI: 10.5061/dryad.51c59zwnb
title: Data from: Biological processes underpin the persistence of dryland productivity following extreme wet years

description: Global warming has induced more years of above-average rainfall,
 significantly affecting the interannual variability of the terrestrial
 global carbon cycle. An extreme wet year can cause changes to vegetation
 structure and function that persist beyond itself, referred to as “legacy
 effects”. The physical and biological mechanisms underlying these effects
 are poorly understood, introducing uncertainty into climate–carbon models
 to accurately represent post–wet year vegetation dynamics. Here we used
 multi-source satellite-derived vegetation productivity metrics, as well as
 eddy covariance (EC) measurements, to investigate the legacy effects of
 extreme wet years on the productivity of Australia’s drylands. We found
 that the impact of the 2010–2011 extreme wet year extended beyond
 generating a record-breaking carbon uptake, which exceeded the 40-year
 mean by more than 1.5 standard deviations. It also resulted in a
 widespread positive legacy effect in the following year. Specifically, up
 to 56% of the vegetated areas that experienced anomalous wetness showed
 significant legacy effect after one year, with impact size contributing up
 to 40 percent of total productivity in those regions. Biological memory in
 wet years, representing a potential process for carbon storage and
 subsequent remobilization, was shown to dominate the legacy effect. Random
 forest analysis identified key ecogeographic controls on biological
 memory, such as resource-conservative strategies associated with drier
 climates and relatively fertile soils. Comparisons with Dynamic Global
 Vegetation Models (DGVMs) further revealed that current models may
 underestimate this biological memory by up to 70%, in part due to limited
 representation of carbon storage dynamics. Our results contribute to more
 accurate modelling of dryland carbon cycle and provide a framework to
 better account for post-wet-year legacy effects by incorporating the
 influence of wet-year productivity.
description: # Data from: Biological processes underpin the persistence of dryland
 productivity following extreme wet years Dataset DOI:
 [10.5061/dryad.51c59zwnb](https://doi.org/10.5061/dryad.51c59zwnb) ##
 Description of the data and file structure This repository provides the
 codes used in the analysis for the manuscript: ***Biological Processes
 Underpin the Persistence of Dryland Productivity Following Extreme Wet
 Years***. * **Figure 1 and Figure 2** were produced using **MATLAB**
 scripts. * **Figure 3** was produced using **R** scripts. All codes are
 provided for reproducibility and transparency of the analysis. * The
 MATLAB scripts include procedures for detrending, normalization,
 regression, and legacy effect quantification. * The R scripts include
 procedures for recursive feature elimination (RFE), random forest
 modeling, and SHAP value analysis. The codes are generalized: * Input data
 are expected in raster format for gridded spatial data, including
 vegetation indices and meteorological variables. Detailed specifications
 are provided in the code annotations and in the associated manuscript: *
 **For Figures 1 and 2** * **Vegetation index**: The PKU GIMMS NDVI
 product \ Available at:
 [https://doi.org/10.5281/zenodo.8253971](https://doi.org/10.5281/zenodo.8253971) * **Meteorological data**: SPEI dataset.\ Available at: [https://digital.csic.es/handle/10261/332007](https://digital.csic.es/handle/10261/332007) - **For Figure 3** * **Soil and landscape data**: Soil and Landscape Grid of Australia.\ Available at: [https://www.csiro.au/en/research/natural-environment/land/soil-and-landscape-grid-of-australia](https://www.csiro.au/en/research/natural-environment/land/soil-and-landscape-grid-of-australia) - Spatial and temporal dimensions are determined by the input data. - Output files (tables, models, figures) are saved in the user-defined **target folder**. ## Access information Other publicly accessible locations of the data: * n/a Data was derived from the following sources: * n/a