Drought is one of the abiotic stresses controlling plant function and ecological stability. In the context of climate change, drought is predicted to occur more frequently in the future. Despite numerous attempts to clarify the overall effects of drought stress on the growth and physiological processes of plants, a comprehensive evaluation on the impacts of drought stress on biomass allocation, especially on reproductive tissues, remains elusive. We conducted a meta‐analysis by synthesizing 164 published studies to elucidate patterns of plant biomass allocation in relation to drought stress. Results showed that drought significantly increased the fraction of root mass but decreased that of stem, leaf, and reproductive mass. Roots of herbaceous plants were more sensitive to drought than woody plants that reduced reproductive allocation more sharply than the former. Relative to herbaceous plants, drought had a more negative impact on leaf mass fraction of woody plants. Among the herbaceous plants, roots of annuals responded to drought stress more strongly than perennial herbs, but their reproductive allocation was less sensitive to drought than the perennial herbs. In addition, cultivated and wild plants seemed to respond to drought stress in a similar way. Drought stress did not change the scaling exponents of the allometric relationship between different plant tissues. These findings suggest that the allometric partitioning theory, rather than the optimal partitioning theory, better explains the drought‐induced changes in biomass allocation strategies.

Accurate mapping of vegetation is a premise for conserving, managing, and sustainably using vegetation resources, especially in conditions of intensive human activities and accelerating global changes. However, it is still challenging to produce high-resolution multiclass vegetation map in high accuracy, due to the incapacity of traditional mapping techniques in distinguishing mosaic vegetation classes with subtle differences and the paucity of fieldwork data. This study created a workflow by adopting a promising classifier, extreme gradient boosting (XGBoost), to produce accurate vegetation maps of two strikingly different cases (the Dzungarian Basin in China and New Zealand) based on extensive features and abundant vegetation data. For the Dzungarian Basin, a vegetation map with seven vegetation types, 17 subtypes, and 43 associations was produced with an overall accuracy of 0.907, 0.801, and 0.748, respectively. For New Zealand, a map of 10 habitats and a map of 41 vegetation classes were produced with 0.946, and 0.703 overall accuracy, respectively. The workflow incorporating simplified field survey procedures outperformed conventional field survey and remote sensing based methods in terms of accuracy and efficiency. In addition, it opens a possibility of building large-scale, high-resolution, and timely vegetation monitoring platforms for most terrestrial ecosystems worldwide with the aid of Google Earth Engine and citizen science programs.

Aim: Dryland ecosystems are exceedingly sensitive to climate change. Desertification induced by both climate changes and human activities seriously threatens dryland vegetation. However, the impact of climate change on distribution of dryland plant species has not been well documented. Here, we studied the potential distribution of four representative dryland plant species (Haloxylon ammodendron, Anabasis aphylla, Calligonum mongolicum, and Populus euphratica) under current and future climate scenarios in a temperate desert region, aiming to improve our understanding of the responses of dryland plant species to climate change and provide guidance for dryland conservation and afforestation.Location: Junggar Basin, a large desert region in northwestern China.Methods: Occurrence data of the studied species were collected from an extensive field investigation of 2,516 sampling sites in the Junggar Basin. Ensemble species distribution models using 10 algorithms were developed and used to predict the potential distribution of each studied species under current and future climate scenarios.Result: Haloxylon ammodendron and A. aphylla were likely to lose most of their current suitable habitats under future climate scenarios, while C. mongolicum and P. euphratica were likely to expand their ranges or remain relatively stationary. Variable importance evaluation showed that the most important climate variables influencing species distribution differed across the studied species. These results may be explained by the different ecophysiological characteristics and adaptation strategies to the environment of the four studied species.Main conclusions: We explored the responses of the representative dryland plant species to climate change in the Junggar Basin in northwestern China. The different changes in suitability of different species imply that policymakers may need to reconsider the selection and combination of the afforestation species used in this area. This study can provide valuable reference for the management and conservation of dryland ecosystems under future climate change scenarios.

We aim to investigate variations in the resorption efficiencies of 10 mineral nutrients [i.e. nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), manganese (Mn), zinc (Zn), aluminum (Al), iron (Fe) and copper (Cu)] in leaves of desert shrubs and to explore effects of aridity on resorption efficiency of these nutrients. Plant samples were collected from 10 sites in northern Xinjiang Uygur Autonomous Region of China. Samples of green and senesced leaves were analysed to determine concentrations of N, P, K, Mg, Ca, Mn, Zn, Al, Fe and Cu and thus the nutrient resorption efficiency. The mean nutrient concentrations in the desert shrubs varied, with the stoichiometric ratio Ca:N (19.3 mg g⁻¹):K (10.5 mg g⁻¹):Mg:P (1.01 mg g⁻¹):Al:Fe:Mn:Zn:Cu (4.78 mg kg⁻¹) = 4038:2950:2199:1816:211:37:32:11:2:1 in green leaves; and Ca:N (12.6 mg g⁻¹):Mg:K (7.6 mg g⁻¹):P (0.56 mg g⁻¹):Fe:Al:Mn:Zn:Cu (2.85 mg kg⁻¹) = 5583:3710:2943:2523:178:133:119:19:3.7:1 in senesced leaves. Resorption generally occurred for six elements (N, P, K, Cu, Mg and Mn, with average resorption efficiency 47.8%, 52.0%, 38.6%, 41.0%, 12.7% and 7.89%, respectively) during leaf senescence, while the other four nutrients tended to accumulate in senesced leaves, showing averagely negative resorption efficiencies [Ca (–3.87%), Al (−57.1%), Zn (−62.6%), Fe (−89.6%)]. Aridity showed strikingly different effects on the resorption process of the 10 nutrients. Of the four elements with totally (N/P/K) or mostly (Cu) positive observations of resorption efficiency, their resorption generally decreased with aridity, suggesting that drought stress had negative effects on the resorption efficiencies of these elements. In contrast, with at least one-third observations of resorption efficiency being negative, the other elements (Mg/Mn/Ca/Zn/Al/Fe) showed generally increasing resorptive tendency with aridity, except for Zn. This research provided a systematic analysis on the large variation and contrasting responses of the resorption of multi-elements to aridity in typical desert shrubs. Our findings foster the understanding of nutrient resorption patterns of desert plants and enable us to better predict the contrastive effects of drought stress on the cycling of diverse nutrients and the consequent stoichiometric decoupling in plants of desert ecosystems.

Forest aboveground biomass (AGB) is not simply affected by a single factor or a few factors, but also by the interaction between them in complex ways across multiple spatial scales. Understanding the joint effect of stand structural characteristics and climate factors on AGB on large scales is critical for accurate forest carbon storage prediction and sustainable management. Despite numerous attempts to clarify the relationships between stand structural characteristics (tree density/TD, diameter at breast height/DBH, basal area/BA), climate factors (mean annual temperature/MAT, mean annual precipitation/MAP), and AGB, they remain contentious on a large scale. Therefore, we explored the relationships between stand structural characteristics, climate factors, and AGB at a biome level by meta-analyzing datasets contained in 40 articles from 25 countries, and then answered the questions of how stand structural characteristics influence AGB at the biome level and whether the relationships are regulated by climate on a large scale. Through using regression analysis and the establishment of a structural equation model, the results showed that the influence of basal area on AGB at the biome level was more substantial than that of tree density and DBH, and the significant relationship between basal area and AGB was relatively stable regardless of biome variation, but the effects of tree density and DBH was non-negligible within the biome. Climatic factors (e.g., temperature and precipitation), should be considered. Our meta-analysis illustrated the complicated interactions between climate factors, stand structural characteristics, and the AGB of forests, highlighting the importance of climate effects on regulating stand structural characteristics and AGB relationships. We suggest that basal area be preferred and considered in forest sustainable management practice to optimize stand structure for increasing carbon storage potential, with close attention to local climate conditions. Overall, our meta-analysis will crucially aid forest management and conservation in the context of global environmental changes, and provide novel insights and a scientific reference to lead to future carbon storage research on large scales.

In recent years, Rwanda, especially its Eastern Province, has been contending with water shortages, primarily due to prolonged dry spells and restricted water sources. This situation poses a substantial threat to the country’s agriculture-based economy and food security. The impact may escalate with climate change, exacerbating the frequency and severity of droughts. However, there is a lack of comprehensive spatiotemporal analysis of meteorological and agricultural droughts, which is an urgent need for a nationwide assessment of the drought’s impact on vegetation and agriculture. Therefore, the study aimed to identify meteorological and agricultural droughts by employing the Standardized Precipitation Evapotranspiration Index (SPEI) and the Vegetation Health Index (VHI). VHI comprises the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), both derived from the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). This study analyzed data from 31 meteorological stations spanning from 1983 to 2020, as well as remote sensing indices from 2001 to 2020, to assess the spatiotemporal patterns, characteristics, and adverse impact of droughts on vegetation and agriculture. The results showed that the years 2003, 2004, 2005, 2006, 2013, 2014, 2015, 2016, and 2017 were the most prolonged and severe for both meteorological and agricultural droughts, especially in the Southern Province and Eastern Province. These extremely dry conditions led to a decline in both vegetation and crop production in the country. It is recommended that policymakers engage in proactive drought mitigation activities, address climate change, and enforce water resource management policies in Rwanda. These actions are crucial to decreasing the risk of drought and its negative impact on both vegetation and crop production in Rwanda.