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Societal Impact Statement Botanic gardens play a crucial role in addressing global environmental challenges by providing a unique setting for long‐term plant studies and engaging the public in climate change awareness. Our review highlights the underuse of these gardens' living collections for monitoring climate impacts, revealing significant gaps in data and phylogenetic diversity. The Witness Tree Project at Trinity College Botanic Garden will enhance long‐term research and public engagement through open‐access data and protocols. This initiative not only advances scientific understanding but also fosters community involvement and education, promoting a collective effort towards mitigating climate change impacts. Summary Botanic gardens are ideal settings for long‐term studies on plant responses to climate change, providing extensive outreach and visitor engagement opportunities. However, the use of living collections for multi‐year studies has not been thoroughly assessed. This paper first reviews environmental monitoring projects conducted in these institutions over three continuous years, revealing that fewer than 1% of botanic gardens and arboreta globally engage in long‐term research. There is also a notable lack of phylogenetic diversity, with only 3% of angiosperm and 35% of gymnosperm families represented. Monitoring efforts mainly focus on phenology and plant pathology, with limited attention to other subjects like plant traits. Moreover, no studies have linked climate change impacts on plants with urban green space research, despite the urban locations of many botanic gardens, and no structured guidelines exist for establishing long‐term monitoring programmes. In the second part of this paper, we introduce The Witness Tree Project (WTP) at Trinity College Botanic Garden (TCBG), a newly established long‐term (>30 years) annual monitoring programme. The WTP tracks the physiological performance of selected woody plants under climate change and the deposition of particulate pollution (PM 2.5 and PM10) on their leaves. The project leverages the potential of a university botanic garden to integrate multidisciplinary research, teaching and outreach activities, using open‐access protocols and data‐sharing practices. Finally, we outline a framework for designing long‐term monitoring programmes in botanic gardens and arboreta. This framework, informed by the establishment and pilot year of the WTP, encourages the use of living collections in advancing global change research. Botanic gardens play a crucial role in addressing global environmental challenges by providing a unique setting for long‐term plant studies and engaging the public in climate change awareness. Our review highlights the underuse of these gardens' living collections for monitoring climate impacts, revealing significant gaps in data and phylogenetic diversity. The Witness Tree Project at Trinity College Botanic Garden will enhance long‐term research and public engagement through open‐access data and protocols. This initiative not only advances scientific understanding but also fosters community involvement and education, promoting a collective effort towards mitigating climate change impacts. Image courtesy of Peter Lang.

Desertification is a critical environmental problem in China’s northwestern region. In this context, since the early 2000s, projects targeting ecological restoration have been implemented in the lower reaches of the Heihe River basin. Using multi-scale remote sensing data and field observations, this paper examines the outcomes of the ecological restoration projects. Specifically, this paper examines the vegetation change through remote sensing and local perceptions of the projects through semi-structured questionnaires. The results from remote sensing reveal that during the restoration projects, vegetation coverage in riparian areas of the lower reaches of the Heihe River basin increased. However, this increase cannot be simply equated with ecological recovery. Expansion of farmland and afforested areas have also contributed to the increase in vegetation coverage. Questionnaire results reveal that although locals perceived improvements in the ecological conditions of the lower reaches, most of them were more about future environmental changes. Additionally, results indicate that ecological restoration projects redistributed water resources in the local river reaches and, as a result, local residents living in riparian areas perceive greater benefit. Therefore, the implementation of the project may have actually negatively impacted the water accessibility of those living in the drier Gobi Desert areas.

Verlorenvlei is a globally important RAMSAR wetland on the arid west coast of South Africa. A prolonged drought between 2016 and 2021 and increasing competition for water from the agricultural sector resulted in extremely low water levels. We used historical aerial and satellite imagery from 1942 and rainfall and water level data for the past 50 years, to assess habitat changes within the estuarine functional zone of the Verlorenvlei Estuarine Lake. Prior to the drought, lake water levels and water surface area remained stable (1113 ± 27 ha (SE)). Since then, there has been a 64% decrease in open water area, exposing 193 ha of sandbanks, of which 190.9 ha were hyper-sulfidic pyrite-rich. The water in the lower lake was hypersaline (>100), and in the middle, it was acidic (pH<3). The low water level plus sediment and nutrient input from surrounding agriculture resulted in a localised increase in reeds. Additional pressures, such as fires, have reduced the above-ground biomass of reeds and sedges, potentially altering surface morphology and reducing stored carbon. Despite flooding and filling up in June 2023, the lake remained in an acidic state (3.9-4.3). Similar low-lake level, hypersaline and acidic conditions are predicted to become more common under future climate change scenarios where aridity and extreme weather events are anticipated. Inflow of fresh water into the estuary and control of farming practices are required to keep the Verlorenvlei in a functional state, with long-term monitoring necessary to assess the ecological condition in response to restoration actions.Significance: We assessed the habitat changes in Verlorenvlei, an estuarine lake on the arid west coast of South Africa. Estuarine lakes are scarce, and an extended drought greatly reduced the water surface area, exposing hypersulfidic pyrite-rich soils from agribusiness and the burning of reeds are added pressures. Subsequent heavy rains have been slow to buffer lake acidity, and the impacts thereof serve as a warning for the management of similar ecosystems and their ecological water requirements, especially under climate change where extreme weather conditions, increased aridity and competition for water are realities.

Climate‐vegetation interaction assessments often focus on vegetation response to concurrent climatic perturbations, seldom on the time‐lag effect of climate. Here we employ global satellite observations, climate data records and CO2 flux measurements to calculate the time‐lag of vegetation response to climate. We analyze the time‐lags of various climate variables under distinct environmental conditions to gain insight into how the long‐term climatic regimes and tree cover influence the time‐lag effects. Our findings reveal that terrestrial ecosystems characterized by arid and cold climates show more concurrent climate‐vegetation interactions than other ecosystems. Whereas areas with higher tree cover and humid ecosystems with both high mean annual temperature and precipitation show substantial time‐lag response of vegetation to climate by up to 6 months. Since the global climate‐vegetation interaction is dominated by time‐lag effects, incorporating these effects is paramount to improve our understanding of vegetation dynamics under a changing climate. Plain Language Summary When studying how climate affects vegetation, many studies usually focus on immediate plant responses, without considering the long‐term effects of climate. In our study, we used satellite data to look at how plant photosynthesis and growth changed over time in response to concurrent and past climates. We found that in dry and cold areas, plants respond quickly to changes in climate. But in regions with high tree cover and humid climate, plant responses to climate can take up to 6 months. Understanding these delays is crucial for predicting how vegetation will respond as the climate changes around the world. Key Points Terrestrial ecosystems with higher tree cover respond to climate perturbation more slowly than grasslands and croplands Temperature consistently has more significant impacts on vegetation in the longer term than VPD and soil moisture Arid and cold ecosystems show shorter time‐lag responses of vegetation to climate

A flash drought typically exhibits rapid development and high intensity, with significant impacts on societies and ecosystems. Central Asia (CA), a typical arid region, little attention has been paid to the characteristics of flash droughts and their impact on ecosystems. Therefore, a novel composite decomposition flash drought identification (CDFDI) framework was adopted to integrate data on soil moisture, normalized difference vegetation index (NDVI), and gross primary productivity to identify flash drought as a subphase of regular drought in CA. This study aims to explore flash drought characteristics and vegetation response in CA, comparing them with existing identification methods to assess the effectiveness of the flash drought identification framework. The main findings are: (1) introducing inter-event time and volume criterion and Madsen methods in the CDFDI framework yielded promising results, verified through correlation between flash drought characteristics and NDVI deficits (e.g., the average percentage of correlations between flash drought features and NDVI in the − 1 to -0.5 and 0.5 to 1 intervals was 15%); (2) the northern, central, eastern, and southeastern CA were frequently affected by flash droughts, while the western region experienced prolonged regular droughts with an insignificant weakening trend between 1948 and 2022; and (3) Average gross primary productivity response time was 30 days, and its spatial distribution indicated that the impacts of flash drought on vegetation were more immediate in the comparatively arid western CA. This study provides new insights into identifying and characterizing flash drought in changing environments, contributing to a better understanding of its impacts on ecosystems.

Grassland ecosystems are affected by the increasing frequency and intensity of extreme climate events (e.g., droughts). Understanding how grassland ecosystems maintain their functioning, resistance, and resilience under climatic perturbations is a topic of current concern. Resistance is the capacity of an ecosystem to withstand change against extreme climate, while resilience is the ability of an ecosystem to return to its original state after a perturbation. Using the growing season Normalized Difference Vegetation Index (NDVI gs , an index of vegetation growth) and the Standardized Precipitation Evapotranspiration Index (a drought index), we evaluated the response, resistance, and resilience of vegetation to climatic conditions for alpine grassland, grass-dominated steppe, hay meadow, arid steppe, and semi-arid steppe in northern China for the period 1982–2012. The results show that NDVI gs varied significantly across these grasslands, with the highest (lowest) NDVI gs values in alpine grassland (semi-arid steppe). We found increasing trends of greenness in alpine grassland, grass-dominated steppe, and hay meadow, while there were no detectable changes of NDVI gs in arid and semi-arid steppes. NDVI gs decreased with increasing dryness from extreme wet to extreme dry. Alpine and steppe grasslands exhibited higher resistance to and lower resilience after extreme wet, while lower resistance to and higher resilience after extreme dry conditions. No significant differences in resistance and resilience of hay meadow under climatic conditions suggest the stability of this grassland under climatic perturbations. This study concludes that highly resistant grasslands under conditions of water surplus are low resilient, but low resistant ecosystems under conditions of water shortage are highly resilient.

Drought has devastating impacts on agriculture and other ecosystems, and its occurrence is expected to increase in the future. However, its spatiotemporal impacts on net primary productivity (NPP) in Mongolia have remained uncertain. Hence, this paper focuses on the impact of drought on NPP in Mongolia. The drought events in Mongolia during 2003–2018 were identified using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The Boreal Ecosystem Productivity Simulator (BEPS)-derived NPP was computed to assess changes in NPP during the 16 years, and the impacts of drought on the NPP of Mongolian terrestrial ecosystems was quantitatively analyzed. The results showed a slightly increasing trend of the growing season NPP during 2003–2018. However, a decreasing trend of NPP was observed during the six major drought events. A total of 60.55–87.75% of land in the entire country experienced drought, leading to a 75% drop in NPP. More specifically, NPP decline was prominent in severe drought areas than in mild and moderate drought areas. Moreover, this study revealed that drought had mostly affected the sparse vegetation NPP. In contrast, forest and shrubland were the least affected vegetation types.

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems.

Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60%–4.68% when the temperature increased by 1.5 °C, while it only changed by 0.06%–0.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau.

This paper systematically reviews the potential of the Sentinel-2 (A and B) in assessing drought. Research findings, including the IPCC reports, highlighted the increasing trend in drought over the decades and the need for a better understanding and assessment of this phenomenon. Continuous monitoring of the Earth’s surface is an efficient method for predicting and identifying the early warnings of drought, which enables us to prepare and plan the mitigation procedures. Considering the spatial, temporal, and spectral characteristics, the freely available Sentinel-2 data products are a promising option in this area of research, compared to Landsat and MODIS. This paper evaluates the recent developments in this field induced by the launch of Sentinel-2, as well as the comparison with other existing data products. The objective of this paper is to evaluate the potential of Sentinel-2 in assessing drought through vegetation characteristics, soil moisture, evapotranspiration, surface water including wetland, and land use and land cover analysis. Furthermore, this review also addresses and compares various data fusion methods and downscaling methods applied to Sentinel-2 for retrieving the major bio-geophysical variables used in the analysis of drought. Additionally, the limitations of Sentinel-2 in its direct applicability to drought studies are also evaluated.