Above‐ground biomass retrieval with multi‐source data: Prediction and applicability analysis in Eastern Mongolia

Grassland aboveground biomass (AGB) is a key variable to measure grassland productivity, and accurate assessment of AGB is important for optimizing grassland resource management and understanding carbon, water, and energy fluxes. Current approaches on large scales such as the Mongolian Steppe Ecosystem often combine field measurements with optical and/or synthetic aperture radar (SAR) data. Meanwhile, especially the representativeness of the field measurements for large-scale analysis have seldom been accounted for. Therefore, we provide the first remotely sensed AGB product for central and Eastern Mongolia which (1) uses random forest (RF), (2) is fully validated against over 600 field samples, and (3) applies a novel method, dissimilarity index (DI), to derive the area of applicability of the model with respect to the training data. Therefore, different remote sensing data sources such as multi-scale and multi-temporal optical images—Worldview 2 (WV2), Sentinel 2 (S2), and Landsat 8 (L8) in combination with SAR data are tested for their suitability to provide an area-wide estimation on large scale. The results showed that the AGB prediction by combining Sentinel 1 (S1) and S2 using RF had the highest accuracy. Furthermore, the model was applicable to at least 72.61% of the steppe area. Areas where the model was not applicable are mostly distributed along the edges of grassland. This study demonstrates the potential of combining Sentinel-derived indices and machine learning to provide a reliable AGB prediction for grassland for extremely large ecosystems with strong climatic gradients

data_SPAGeDi_format

The microsatellite data is presented in a format that is accepted by the software SPAGeDi. You may use SPAGeDi to re-run the analyses and/or to convert the data into other formats

Data from: Climate outweighs native vs. non-native range-effects for genetics and common garden performance of a cosmopolitan weed

Comparing genetic diversity, genetic differentiation and performance between native and non-native populations has advanced our knowledge of contemporary evolution and its ecological consequences. However, such between-range comparisons can be complicated by high among-population variation within native and non-native ranges. For example, native vs. non-native comparisons between small and non-representative subsets of populations for species with very large distributions have the potential to mislead because they may not sufficiently account for within-range adaptation to climatic conditions, and demographic history that may lead to non-adaptive evolution. We used the cosmopolitan weed Conyza canadensis to study the interplay of adaptive and demographic processes across, to our knowledge, the broadest climatic gradient yet investigated in this context. To examine the distribution of genetic diversity, we genotyped 26 native and 26 non-native populations at 12 microsatellite loci. Furthermore, we recorded performance traits for 12 native and 13 non-native populations in the field and in the common garden. To analyze how performance was related to range and/or climate, we fit pedigree mixed-effects models. These models weighed the population random effect for co-ancestry to account for the influence of demographic history on phenotypic among-population differentiation. Genetic diversity was very low, selfing rates were very high, and both were comparable between native and non-native ranges. Non-native populations out-performed native populations in the field. However, our most salient result was that both neutral genetic differentiation and common garden performance were far more correlated with the climatic conditions from which populations originated than native vs. non-native range-affiliation. Including co-ancestry of our populations in our models greatly increased explained variance and our ability to detect significant main effects for among-population variation in performance. High propagule pressure and high selfing rates, in concert with the ability to adapt rapidly to climatic gradients, may have facilitated the global success of this weed. Neither native nor non-native populations were homogeneous groups but responded comparably to similar environments in each range. We suggest that studies of contemporary evolution should consider widely distributed and genotyped populations to disentangle native vs. non-native range-effects from varying adaptive processes within ranges and from potentially confounding effects of demographic history