## 2 Data and Methods
### Data
#### 2.1.2 Remote Sensing Data  
Considering the availability of datasets, three categories of remote sensing metrics were collected: energy/productivity metrics, climate metrics, and ecosystem texture metrics. Because the species richness data was recorded and updated for decades, we selected the remote sensing data as long-term as possible. In addition, all remote sensing data had global coverage. For the energy/productivity category, we selected gross primary production (GPP), dynamic habitat index (DHI), and potential evapotranspiration (PET). The GPP product was obtained from the global monthly MOD17A2 GPP product [60]. The DHI, including Cumulative Annual Productivity (DHI-cum), Minimum Annual Apparent Cover (DHI-min), and Seasonal Variation of Greenness (DHI-sea), is a composite vector deduced from the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time-series, representing the vegetation dynamics. The monthly maximum FAPAR-value is the basic input dataset to compute the three relevant annual indices for the subsequent habitat analysis [51; 61]. DHI-cum provides an indication of overall site vegetation productivity. DHI-min represents the lowest (minimum value) level of vegetative productivity in a year. DHI-sea refers to the variation of the vegetative productivity. Further details of the DHI can be found in previous publications [51; 62; 63; 61]. In this study, DHI was calculated from the Global Inventory Modelling and \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Category** & **Metrics** & **Spatial Resolution** & **Temporal Resolution** & **Temporal Coverage** \\ \hline \multirow{5}{*}{Energy/productivity} & Dynamic habitat index (DHI)-cum & \(1/12^{\circ}\) & yearly & 2000–2011 \\  & Dynamic habitat index (DHI)-min & \(1/12^{\circ}\) & yearly & 2000–2011 \\  & Dynamic habitat index (DHI)-sea & \(1/12^{\circ}\) & yearly & 2000–2011 \\  & Gross primary production (GPP) & \(0.05^{\circ}\) & monthly & 2001–2015 \\  & Potential evapotranspiration (PET) & \(0.05^{\circ}\) & monthly & 2001–2014 \\  & Land surface temperature (LST) & \(0.05^{\circ}\) & monthly & 2000–2011 \\ Climate & Evaportranspiration (ET) & \(0.05^{\circ}\) & monthly & 2000–2014 \\  & Coefficient of variation (CV) & 1 km & 5-year & 2001–2005 \\  & Evenness & 1 km & 5-year & 2001–2005 \\  & Contrast (CON) & 1 km & 5-year & 2001–2005 \\  & Dissimilarity (DIS) & 1 km & 5-year & 2001–2005 \\ Texture & Entropy (ENT) & 1 km & 5-year & 2001–2005 \\  & Homogeneity (HOM) & 1 km & 5-year & 2001–2005 \\  & Range & 1 km & 5-year & 2001–2005 \\  & Shannon & 1 km & 5-year & 2001–2005 \\  & Simpson & 1 km & 5-year & 2001–2005 \\  & Standard deviation (SD) & 1 km & 5-year & 2001–2005 \\  & Correlation (COR) & 1 km & 5-year & 2001–2005 \\  & Maximum (MAX) & 1 km & 5-year & 2001–2005 \\  & Uniformity (UNI) & 1 km & 5-year & 2001–2005 \\  & Variance (VAR) & 1 km & 5-year & 2001–2005 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Remote sensing metrics. Mapping Studies (GIMMS) AVHRR-FAPAR 3g dataset. The PET product was obtained from the MOD16A2 product. In our study, PET was taken as an energy/productivity metric, because it characterizes the features of the surface temperature and radiance. For the climate category, we selected evapotranspiration (ET) and land surface temperature (LST). The ET product was obtained from the global monthly MOD16A2 ET product [64; 65; 66; 67; 68]. The LST product used in this study was obtained from the global monthly MOD11C3 LST product, which belonged to the temperature/surface emissivity global data sets (C5) [69]. For the texture category, we selected a suite of global terrestrial habitat heterogeneity data, which was developed by [PERSON] et al. and computed by [PERSON] using the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product [70; 25]. Heterogeneity is an important indicator of ecosystem texture, which has long been recognized as a key landscape characteristic with strong relevance for biodiversity [71; 72].