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Anticipating future impacts of climate warming and aridification on drylands requires understanding how coexisting woody plant species respond to climate variability. However, we lack knowledge of the growth resilience capacity of Mediterranean shrubs. Do coexisting trees and shrubs differ in their response to climate? Do coexisting shrub species have comparable post‐drought growth resilience? This study was conducted in two Mediterranean shrublands with sparse trees in semi‐arid north‐eastern Spain. We selected sites situated in formerly agricultural or grassland areas in two regions subjected to semi‐arid Mediterranean climate conditions. We sampled six shrubs' species (Juniperus phoenicea, Juniperus oxycedrus, Pistacia lentiscus, Pistacia terebinthus, Rhamnus lycioides and Rhamnus alaternus) and one tree species (Pinus halepensis) to measure their radial growth and to reconstruct their past growth patterns using dendrochronology. We quantified climate–growth relationships of trees and shrubs, as well as the growth resilience capacity after drought events of the six shrubs. Growth patterns differed between species but a prevalent trade‐off between growth and longevity was found. Growth responses to climate were comparable between species but differed between sites. Most species responded positively to precipitation and negatively to temperature. The most negative correlations of growth with drought severity were found at the driest Valcuerna site. Shrubs differed in their resilience capacity. Across sites, species were more resistant and resilient in Alcubierre, the wettest site. The shrubs P. terebinthus and R. lycioides were more resistant and resilient than the rest of species, which required longer growth recovery times and accumulated stronger growth reductions, particularly J. phoenicea. Synthesis. These results highlight the importance of drought as a driver of growth in Mediterranean scrublands. Growth resilience strategies differed between species with junipers being less resilient to drought than other coexisting shrubs. Further research should investigate how this difference in post‐drought resilience is related to functional traits, particularly those related with plant water‐use strategies. [ABSTRACT FROM AUTHOR]

Context: Vegetation mapping is subject to a diversity of approaches and lack of coordination, leading to low repeatability and predictive power in the species-rich flora of the Southwest Australian Floristic Region. Yet it has potential as a tool of use in fire management. Aims: This project, extending over five decades, aimed to develop an authoritative vegetation classification and map plant fire responses at Two Peoples Bay Nature Reserve. Methods: Using Muir's classification approach, field surveys were conducted with aerial photography in hand. Thirty-three vegetation units were identified, described, mapped, and photographed. Defining attributes and taxa were identified for each unit. Key results: Map, descriptions, and photographs detail forest, woodlands, mallee, scrub thickets, heath, wetlands, and granite communities on the Reserve. The forest, woodland, and shrublands were adequately classified and mapped. However, granite complex and mallee were least satisfactory, oversimplifying a rich diversity of vegetation types and habitats. Conclusions: The Reserve may be divided for management into the central third of heath, shrublands, and low woodlands largely across the isthmus, the dunes and wetlands of the west with a greater diversity of vegetation types, and the eastern granite inselberg attaining 408 m with the most diverse vegetation types. The latter inselberg needs continued protection from fire and other disturbances. Greatest change in vegetation is seen in lowland landscapes where fire activity has also been pronounced. Implications: Vegetation mapping has been a valuable aid for managers and fire planning, and for active comanagement with appropriate Aboriginal families. This project, extending over five decades, developed an authoritative vegetation classification and mapped plant fire responses at Two Peoples Bay Nature Reserve. Using Muir's classification approach, field surveys were conducted with aerial photography in hand. Thirty-three vegetation units were identified, described, mapped, and photographed. Defining attributes and taxa were identified for each unit. Vegetation mapping has been a valuable aid for phytogeographical placement of the Reserve, for managers and for fire planning. This article belongs to the Collection The Natural History of Two Peoples Bay Nature Reserve, Western Australia. [ABSTRACT FROM AUTHOR]

Laetoli, Tanzania is one of the most important palaeontological and palaeoanthropological localities in Africa. We report on a survey of the extant terrestrial gastropod faunas of the Laetoli-Endulen area, examine their ecological associations and re-examine the utility of Pliocene fossil molluscs in palaeoenvironmental reconstruction. Standardised collecting at 15 sites yielded 7302 individuals representing 58 mollusc species. Significant dissimilarities were found among the faunas of three broad habitat types: forest, woodland/bushland and open (grassland and scattered, xeric shrubland). Overall, more species were recorded in the woodland/bushland sites than in the forest sites. Open sites were less diverse. Environmental factors contributing most strongly to the separation of habitat types were aridity index and elevation. The results are supplemented with new mollusc data from the Mbulu Plateau south of Lake Eyasi, and compared to the list of species cumulatively recorded from the Ngorongoro area. Some regional variation is apparent and historical factors may explain the absence of some fossil taxa from Laetoli today. Differences in seasonality separated upland forest sites on the Mbulu plateau from those at Lemagurut at Laetoli. Indicator species were identified for each habitat. These included several large-bodied species analogous to the Laetoli Pliocene fossil species that were then used for palaeoenvironmental reconstruction. Based on the estimated aridity index, and adopting the widely used United Nations Environment Programme (UNEP) global climate classification, the four stratigraphic subunits of the Upper Laetolil Beds (3.6–3.85 Ma) would be placed in either the UNEP's Dry Sub-humid or Semi-arid climate classes, whereas the Upper Ndolanya Beds (2.66 Ma) and Lower Laetolil Beds (3.85-<4.36 Ma) would be assigned to the Humid and Semi-arid climate classes respectively. Pliocene precipitation at Laetoli is estimated as 847–965 mm per year, refining previous estimates. This is close or slightly higher than the present mean annual precipitation, and is likely to have corresponded to a mosaic of forest, woodland and bushland within a grassland matrix consistent with other reconstructions. [ABSTRACT FROM AUTHOR]

Accurate estimation for vegetation net primary production (NPP) at high resolution is essential for ecosystem management and at local to global scales. However, no reliable methods are available to achieve fine-resolution estimation. In this study, a new NPP estimation system was developed by integrating high spatial resolution remote sensing images, tree ring measurements, and process-based model CASA. The system was illustrated by estimating the historical NPP of caragana shrublands from 2011 to 2021 in Dingbian County, China. The results showed that: (1) by employing the biomass model and tree ring measurements, an NPP-crown width model was established to enable a large number of samples for calibrating the CASA model on high spatial resolution images without continuous field measurements. The calibrated parameters, including maximum NDVI, minimum NDVI, and maximum light use efficiency, were determined to be 0.415, 0.022 and 0.025, respectively; (2) according to the estimation by the calibrated CASA model, the NPP in Dingbian County revealed an increasing trend from 2011 to 2021, and the NPP in southern hilly and gully regions was significantly higher than the other regions; (3) among the different indices, max temperature of warmest month had a significant negative effect on the NPP of cagarana shrublands, whereas annual precipitation had a positive effect. In the northern and central regions, air temperature predominantly influenced NPP, while in the southern regions, both temperature and precipitation played a joint role. The implementation in this study illustrated that the NPP estimation system could provide reliable NPP with high resolution and efficient to monitor and detect dominant factors affecting NPP for ecosystem management. [ABSTRACT FROM AUTHOR]

Climate change is significantly affecting mountain plant communities, causing dynamic alterations in species composition as well as spatial distribution. This raises the need for constant monitoring. The Tatra Mountains are the highest range of the Carpathians which are considered biodiversity hotspots in Central Europe. For this purpose, microwave Sentinel-1 and optical multi-temporal Sentinel-2 data, topographic derivatives, and iterative machine learning methods incorporating classifiers random forest (RF), support vector machines (SVMs), and XGBoost (XGB) were used for the identification of thirteen non-forest plant communities (various types of alpine grasslands, shrublands, herbaceous heaths, mountain hay meadows, rocks, and scree communities). Different scenarios were tested to identify the most important variables, retrieval periods, and spectral bands. The overall accuracy results for the individual algorithms reached RF (0.83–0.96), SVM (0.87–0.93), and lower results for XGBoost (0.69–0.82). The best combination, which included a fusion of Sentinel-1, Sentinel-2, and topographic data, achieved F1-scores for classes in the range of 0.73–0.97 (RF) and 0.66–0.95 (SVM). The inclusion of topographic variables resulted in an improvement in F1-scores for Sentinel-2 data by one–four percent points and Sentinel-1 data by 1%–9%. For spectral bands, the Sentinel-2 10 m resolution bands B4, B3, and B2 showed the highest mean decrease accuracy. The final result is the first comprehensive map of non-forest vegetation for the Tatra Mountains area. [ABSTRACT FROM AUTHOR]

Coastal mallee shrubland wildfires present challenges for accurately predicting fire spread sustainability and rate of spread. In this study, we assess the fuel drivers contributing to coastal mallee shrubland fires. A review of shrubland fire behaviour models and fuel metrics was conducted to determine the current practice of assessing shrubland fuels. This was followed by workshops designed to elicit which fuel structural metrics are key drivers of fire behaviour in coastal mallee shrublands. We found that height is the most commonly used fuel metric in shrubland fire models due to the ease of collection in situ or as a surrogate for more complex fuel structures. Expert workshop results suggest that cover and connectivity metrics are key to modelling fire behaviour in coastal mallee shrublands. While height and cover are frequently used in fire models, we conclude that connectivity metrics would offer additional insights into fuel drivers in mallee shrublands. Future research into coastal mallee fire behaviour should include the measurements of fuel height, cover, and horizontal and vertical connectivity. [ABSTRACT FROM AUTHOR]

Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences. We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example, Austrocedrus chilensis and Nothofagus dombeyi forests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland of Nothofagus antarctica representing a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems. The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences. [ABSTRACT FROM AUTHOR]

In recent years, Geoscience Australia has undertaken a successful continental-scale validation program, targeting Landsat and Sentinel analysis-ready data surface reflectance products. The field validation model used for this program was successfully built upon earlier studies, and the measurement uncertainties associated with these protocols have been quantified and published. As a consequence, the Australian earth observation community was well-prepared to respond to the United States Geological Survey (USGS) call for collaborators with the 2021 Landsat 8 (L8) and Landsat 9 (L9) underfly. Despite a number of challenges, seven validation datasets were captured across five sites. As there was only a single 100% overlap transit across Australia, and the country was amidst a strong La Niña climate cycle, it was decided to deploy teams to the two available overpasses with only 15% side lap. The validation sites encompassed rangelands, chenopod shrublands, and a large inland lake. Apart from instrument problems at one site, good weather enabled the capture of high-quality field data allowing for meaningful comparisons between the radiometric performance of L8 and L9, as well as the USGS and Australian Landsat analysis-ready data processing models. Duplicate (cross-calibration) spectral sampling at different sites provides evidence of the field protocol reliability, while the off-nadir view of L9 over the water site has been used to better compare the performance of different water and atmospheric correction processing models. [ABSTRACT FROM AUTHOR]

Environmental niche modeling (ENM) has emerged as a promising tool for identifying grass species with potential for rangeland restoration. This approach can detect suitable areas and environments where these species can be planted. In this study, we employed ENM to estimate the potential distribution range of 50 grass species of the grasslands and shrublands of northern Mexico. The outcome of the ENM served to identify grass species with potential for restoration in Mexico, especially those not commonly used for that purpose in the past. Results suggested the possibility of selecting seven grass species with the potential for revegetating degraded grasslands, nine for shrublands, and six for alkaline soils. This research provides insights into the environmental adaptations of different grass species distributed in the rangelands of northern Mexico. Ecologists, conservation planners, researchers, and range managers could use these outcomes and the maps of the potential distribution ranges as supportive information to conduct effective restoration efforts. In turn, this can assist in increasing the probability of success of future rangelands restoration programs, which are often costly in terms of financial investments and labor. [ABSTRACT FROM AUTHOR]

Background: In Italy, malaria was endemic until the 1970s, when it was declared eradicated by WHO. Nowadays, with the persistence of competent mosquito populations, the effect of climate change, and increased possibility of importing malaria parasites from endemic counties due to growing migration, a malaria resurgence in Italy has become more likely. Hence, enhancing the understanding of the current distribution of the Anopheles maculipennis complex and the factors that influence the presence of this malaria vector is crucial, especially in Northern Italy, characterised by a high density of both human population and livestock. Methods: To assess the presence and abundance of malaria vectors, a 4-year field survey in the plain areas of Lombardy and Emilia-Romagna region in Italy was conducted. Every sampling point was characterised in space by the land use in a 500-m radius and in time considering meteorological data collected in the short and long time periods before sampling. We combined the results of a linear regression model with a random forest analysis to understand the relative importance of the investigated niche dimensions in determining Anopheles mosquito presence and abundance. Results: The estimated normalised variable importance indicates that rice fields were the most important land use class explaining the presence of Anopheles, followed by transitional woodlands and shrubland. Farm buildings were the third variable in terms of importance, likely because of the presence of animal shelters, followed by urbanised land. The two most important meteorological variables influencing the abundance of Anopheles in our study area were mean temperature in the 24 h before the sampling date and the sum of degree-days with temperature between 18 °C and 30 °C in the 14 days before the sampling date. Conclusions: The results obtained in this study could be helpful in predicting the risk of autochthonous malaria transmission, based on local information on land cover classes that might facilitate the presence of malaria vectors and presence of short- and medium-term meteorological conditions favourable to mosquito development and activity. The results can support the design of vector control measures through environmental management. [ABSTRACT FROM AUTHOR]

Previous studies have shown that climate change has significant cumulative effects on vegetation growth. However, there remains a gap in understanding the characteristics of cumulative climatic effects on different vegetation types and the underlying driving mechanisms. In this study, using the normalized difference vegetation index data from 1982 to 2015, along with accumulated temperature, precipitation, and solar radiation data, we quantitatively investigated the intra-annual cumulative effects of climatic factors on global vegetation biomes across climatic zones. We also explored the underlying driving mechanisms. The results indicate that precipitation has a longer intra-annual cumulative effect on vegetation, with effects lasting up to 12 months for large percentages of most vegetation biomes. The cumulative effect of solar radiation is mostly concentrated within 0–6 months. Temperature has a shorter cumulative effect, with no significant cumulative effect of temperature on large percentages of tree-type vegetation. Compared to other vegetation types, evergreen broadleaf forests, close shrublands, open shrublands, savannas, and woody savannas exhibit more complex cumulative climatic effects. Each vegetation type shows a weak-to-moderate correlation with accumulated precipitation while exhibiting strong-to-extremely-strong positive correlations with accumulated temperature and accumulated solar radiation. The climate-induced regulations of water, heat, and nutrient, as well as the intrinsic mechanisms of vegetation's tolerance, resistance, and adaptation to climate change, account for the significant heterogeneity of cumulative climatic effects across vegetation biomes in different climatic zones. This study contributes to enriching the theoretical understanding of the relationship between vegetation growth and climate change. It also offers crucial theoretical support for developing climate change adaptation strategies and improving future "vegetation-climate" models. [ABSTRACT FROM AUTHOR]

Phenotypic plasticity can increase the extent of the environmental gradient occupied by a species (niche breadth) and modify the portion of niche space shared among co‐occurring species (niche overlap). Thus, phenotypic plasticity may play a role in community assembly processes. Given that plants deal with a multivariate environment, and that functional traits are often correlated, plastic responses to different environmental factors are likely correlated. However, the implications of correlations of plasticities for niche overlap remain unexplored. Here, we present and evaluate a conceptual framework that links correlations of plasticities and niche overlap patterns among co‐occurring plant species. We specifically tested in an arid shrubland whether positive, negative, or null correlations between plasticity to light and water availability would be associated with patterns of high, low, or random niche overlap, respectively. Field data identified light and water availability as key factors shaping herbaceous plant community structure. We estimated species' niche breadth and niche overlap using two‐dimensional kernel–density estimations (NOK) and standardised effect sizes of Pianka's niche overlap index (OSES). We measured phenotypic plasticity to light and water availability in the six most abundant species in a greenhouse experiment. We used the plasticity index (PI) to test 1) the relationship between plasticity to light and water availability, and 2) the association between overall plasticity (average PI across traits) and niche breadth. We found a positive relationship between plasticity to light and water availability. Increased overall plasticity was associated with a broader niche breadth. Both NOK and OSES estimations indicated a significant niche overlap pattern. Results supported one of the predictions of our conceptual framework: that a positive correlation of plasticities would lead to increased niche overlap. The verified conceptual framework broadens our understanding of the role of phenotypic plasticity in plant community coexistence. [ABSTRACT FROM AUTHOR]

As a predominant ecosystem-providing area and distinctive landscape in arid regions, an oasis plays an important role in maintaining land stability, human production, and daily activities. Studying the dynamics of oasis and its driving factors is vital to supporting arid regions' sustainable development. As a typical mountain–desert–oasis landscape, the Turpan–Hami (Tuha) Basin, located in Xinjiang, China, includes complex interactions among different land types. For this study, we revealed the spatio-temporal patterns and transition processes of the oasis using a complex network method between 1990 and 2020 in the Tuha Basin. In the oasis transition network, the degree value, betweenness centrality, and average path length were calculated to express the transition relationship, key oasis type, and oasis structural stability, respectively. Six factors related to climate change and human actives were selected to investigate the driving forces behind oasis transitions, including the average temperature and precipitation in the growing season, the total power of agricultural machinery (TAMP), the production of raw coal (PRC), the total output value of the plantation industry (TPI), and the population (Pop). Our results show that the oasis area of the Tuha Basin, including the natural oasis and artificial oasis, all grew from 1990 to 2020, with the natural oasis expanding more than the artificial oasis. The transitions between oasis types became more frequent as the area of oasis land types increased throughout the study period. Grassland acted as the most important oasis type in the network, with the highest betweenness centrality, but its importance declined due to the increasing complexity of the oasis transition network from 1990 to 2020. The transitions between oasis types became simpler, and the oasis structural stability decreased. Through driving force analysis, the oasis changes showed a positive correlation with the temperature (p-value < 0.05, r = 0.88), and urbanization and industrialization factors prompted transitions to built-up areas and cropland from grassland and shrubland. In summary, our results suggest that to create a harmonious symbiotic relationship between the natural environment in dryland and human activities, preventing grassland degradation and excessive reclamation of land cover is an available way. Meanwhile, the protection of shrubland and water resources is also important. This study provided reference and theory support for promoting the sustainable development of oases. [ABSTRACT FROM AUTHOR]

Climate change induces changes in plant communities according to species' climatic requirements. These changes can be assessed by community climatic disequilibrium (CD), which corresponds to the difference between the climate inferred from the climatic requirements of the species in a community (community‐inferred climate, CIC) and the local observed climate.We assessed changes in CIC and CD during a long‐term climatic manipulation (warming and drought treatments), embedded within the ongoing trends of climate change, in a Mediterranean shrubland (NE Iberian Peninsula) during 1999–2014. We used plant censuses, species distribution and climate layers since 1979 to create a multivariate environmental space where CIC and CD trends were estimated for 1999–2014.CD consistently decreased, concomitant with an overall climate change‐derived increase in aridity (higher temperature and lower precipitation). CIC significantly changed during 1999–2014, reflecting the reshuffling of the community composition due to an increase in the abundance of species distributed in warmer, drier and more seasonal localities. Overall, treatments simulating greater climate change did not accelerate the decrease in CD. However, a trend of steeper diminution of CD was observed under warming treatment. In turn, under drought treatment the species less adapted to seasonality and aridity became less abundant. This community tracking of climate did not follow yearly climatic variability; instead, it was detected by the CD trend at the decadal scale.Synthesis. The procedure developed to measure CD reflects demographic behaviours, thus providing a reliable method to assess the impact of climate change on species and communities. The study demonstrates the current, rapid tracking of Mediterranean woody plant communities to climate change. This tracking results from changes in the abundance of species according to their climatic requirements, inferred from their distribution. However, inertia in demographic processes implies that plant communities do not immediately fit current climate change at local level, as supported by the minor effect of experimentally accentuated climate change. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems affect climate by reflecting solar irradiation, evaporative cooling, and carbon sequestration. Yet very little is known about how plant traits affect climate regulation processes (CRPs) in different habitat types. Here, we used linear and random forest models to relate the community‐weighted mean and variance values of 19 plant traits (summarized into eight trait axes) to the climate‐adjusted proportion of reflected solar irradiation, evapotranspiration, and net primary productivity across 36,630 grid cells at the European extent, classified into 10 types of forest, shrubland, and grassland habitats. We found that these trait axes were more tightly linked to log evapotranspiration (with an average of 6.2% explained variation) and the proportion of reflected solar irradiation (6.1%) than to net primary productivity (4.9%). The highest variation in CRPs was explained in forest and temperate shrubland habitats. Yet, the strength and direction of these relationships were strongly habitat‐dependent. We conclude that any spatial upscaling of the effects of plant communities on CRPs must consider the relative contribution of different habitat types. [ABSTRACT FROM AUTHOR]

Climate change is increasing the frequency and severity of short-term (~1 y) drought events--the most common duration of drought--globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function--aboveground net primary production (ANPP)--was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought. [ABSTRACT FROM AUTHOR]

Shrubs are important ecological barriers in desert regions and an important component of global carbon estimation. However, the shrubland in deserts has been hardly presented, although many high-quality land cover datasets with a 10 m scale based on remote-sensing data have been publicly released products. Therefore, the underestimation of carbon storage is inevitable with the absence of desert shrublands. The existing land-cover datasets have been analyzed and compared, and it has been found that the reason for missing the shrubland in deserts is mainly indued by the absence of shrubland samples, which are easy to neglect and difficult to retrieve. In this study, we developed a semi-automatic method to extract shrubland samples in deserts as the updated input for the machine-learning method. Firstly, the initial samples of desert shrublands were identified from the very high spatial-resolution (0.3~0.5 m) imagery on GEE, and the maximum NDVI from Sentinel-2 was used for double-checking. Secondly, a feature-based method was used to learn the feature from the initial samples and a similarity-based searching method was employed to automatically expand the samples. Finally, the expanded samples and their corresponding time-series satellite images were inputted into different machine-learning methods at a large region (1.63 × 106 km2) for extracting the shrubland in the desert. It was found that different combinations of feature variables and time-series combinations have different impacts on the overall accuracy (OA) of the classification results, as well as the performance of identifying and classifying the different land-cover types. Compared to the existing global-scale land-cover products, the proposed method can better identify the shrubland in deserts and show better overall accuracy. [ABSTRACT FROM AUTHOR]

The knowledge of the effects of fuel dryness on fire occurrence is critical for sound forest fire management planning, particularly in a changing climate. This study aimed to analyze the monthly distributions of MODIS active fire (AF) detections and their relationships with a fuel dryness index (FDI) based on satellite-derived weather and vegetation greenness. Monthly AF distributions showed unimodal distributions against FDI, which were described using generalized Weibull equations, fitting a total of 19 vegetation types and ecoregions analyzed in Mexico. Monthly peaks of fire activity occurred at lower FDI values (wetter fuels) in more hygrophytic ecosystems and ecoregions, such as wet tropical forests, compared to higher fire activity in higher FDI values (drier fuels) for the more arid ecosystems, such as desert shrublands. In addition, the range of fuel dryness at which most monthly fire activity occurred was wider for wetter vegetation types and regions compared to a narrower range of fuel dryness for higher monthly fire occurrence in the more arid vegetation types and ecoregions. The results from the current study contribute towards improving our understanding of the relationships between fuel dryness and fire occurrence in a variety of vegetation types and regions in Mexico. [ABSTRACT FROM AUTHOR]

Elephants have been structuring woodlands along the Chobe Riverfront, changing them to shrublands. Along with the loss of woodland cover, impala populations seem to be increasing along the Chobe Riverfront. We tested the prediction that elephant-induced loss in woodland cover has increased preferred habitats for impalas along the Chobe Riverfront. We found that home range sizes of impala breeding herds did not differ among seasons at all spatial scales. Impala breeding herds were more selective at broader spatial scales than finer spatial scales in all seasons. Impala breeding herds selected shrublands more than the other habitats throughout the year. The Baikiaea woodland and the riparian woodland were the most avoided habitats, with mixed combretum shrublands and relationships between habitat selectivity and group size, inter-herd encounter and habitat fidelity. The results of our study suggest that impala breeding herds used elephant-transformed habitats throughout the year. Season did not influence habitat selectivity, suggesting that the preferred habitat had higher required resources relative to the other habitats throughout the year. [ABSTRACT FROM AUTHOR]

Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic "live fast, die young" life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a very important variable in the global water cycle, carbon cycle, and energy cycle. However, there are still some uncertainties in existing ET products. Therefore, this paper evaluates the uncertainty of three widely used global ET products (ERA5-Land, GLDAS-Noah, and MERRA-2) based on the three-cornered hat (TCH) method, and generates a new ET product based on this. The new product is a long-series global monthly ET dataset with a spatial resolution of 0.25° × 0.25° and a time span of 21 years. The results show that ERA5-Land (8.46 mm/month) has the lowest uncertainty among the three ET products, followed by GLDAS-Noah (8.81 mm/month) and MERRA-2 (11.78 mm/month). The new product (TCH) captures ET trends in different regions as well as validating against in situ flux observations, and it exhibits better performance than the re-analysis dataset (ERA5-Land) in vegetation classifications such as evergreen needle-leaf forest, grassland, open shrubland, savanna, and woody savanna. The linear trend analysis of the new product shows a significant decreasing trend in south-eastern South America and southwestern parts of Africa, and an increasing trend in almost all other regions, including eastern North America, north-eastern South America, western Europe, north-central Africa, southern Asia, and south-eastern Oceania. [ABSTRACT FROM AUTHOR]

Vegetation of the Northern Hemisphere plays a vital role in global ecosystems and the carbon cycle. Variations in precipitation profoundly affect vegetation productivity, plant growth, and species communities. Precipitation frequency directly controls soil moisture availability, which has an impact on the vegetation carbon sink. However, it is unclear how precipitation frequency affects the vegetation productivity of different land cover types in different seasons. In this study, the sensitivities of the gross primary production (GPP) of six vegetation types (forest, cropland, grassland, shrubland, tundra and barren land) in response to the frequency of five categories of precipitation (trace: 0.1–5 mm/day, small: 5–10 mm/day, moderate: 10–15 mm/day, heavy: 15–20 mm/day, and very heavy: >20 mm/day) were analyzed based on the XGBoost model. The results showed that, between 1982 and 2015, precipitation frequency declined in most land cover types but increased significantly in the pan-Arctic. Differences in the sensitivity to precipitation frequency were observed between seasons and precipitation categories in northern latitudes. The GPP values of forest and barren land vegetation were less sensitive to precipitation frequency than grassland, shrubland and tundra. This may be related to different vegetation community structures and underlying surfaces and gradually increasing drought resistance capability. The sensitivity to precipitation frequency declined for moderate and heavy precipitation in cropland, but it increased in winter. As the frequency of trace precipitation diminishes in winter, the sensitivity of each vegetation type reduces by an average of 0.03%/decade. Conversely, the sensitivities to small and moderate rain increase by 0.01%/decade and 0.02%/decade, respectively, for ecosystems such as cultivated land, forests, and shrubs. However, shrubs and tundra exhibit distinct behaviors, where shifts in precipitation frequency align directly with trends in sensitivity. These results show that the frequency of precipitation significantly affects vegetation productivity and has different sensitivities, and vegetation shows different feedback mechanisms in the face of environmental changes. [ABSTRACT FROM AUTHOR]

Nest predation is the most important factor responsible for nest failure in birds. Nest height may be a factor that affects the rate of nest depredation in different species. In this comparative study, we tested a relationship between nest height and nest depredation in open nesting songbirds. We analyzed data from 357 populations of 252 species and found that nests built high in trees were safer than those closer to the ground. Nest depredation rates strongly decreased with increasing nest height above 5 m. This could be because there are fewer nest predator species foraging in the canopy or because there is a lower density of nesting birds making it less profitable for predators to search for nests there. We also found that ground nests in open habitats were more likely to be depredated than those in shrublands and forests. This may be because open habitats are less complex and thus more easily searched by nest predators, or because most nests in open habitats are ground nests and predators can focus on them without having to search other vegetation layers. [ABSTRACT FROM AUTHOR]

Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA‐GPP) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA‐GPP relationship (RWA‐GPP) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near‐infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance–light‐use efficiency GPP. We found that the 3‐ and 7‐year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17‐ and 40‐year time scales (7.28% and 8.23%). The long‐term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA‐GPP and RWA‐GPP with different source products: In high‐latitude regions, RWA‐GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid‐low latitudes. Forests had weak RWA‐GPP at all time scales, shrublands showed negative RWA‐GPP at long time scales, and grassland (GL) showed a positive RWA‐GPP at short time scales. Globally, the EWA‐GPP, whether positive or negative, enhanced significantly at 3‐, 7‐, and 17‐year time scales. For arid and humid zones, the semi‐arid and sub‐humid zones experienced a faster increase in the positive EWA‐GPP, whereas the humid zones experienced a faster increase in the negative EWA‐GPP. At the ecosystem types, the positive EWA‐GPP at a 3‐year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA‐GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA‐GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change. [ABSTRACT FROM AUTHOR]

Aim: Earth observation‐based estimates of land–atmosphere exchange of carbon are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. Temperature, soil water content and gross primary production are the main drivers of ecosystem respiration (Reco), and the main aims of this study are to develop an Reco model driven by long‐term global‐scale Earth observations and to study Reco spatiotemporal dynamics 1982–2015. Location: Global scale. Time Period: 1982–2015. Major Taxa Studied: Terrestrial ecosystems. Methods: We parameterized and applied a global Reco model for 1982–2015 using novel Earth observation‐based data. We studied the relationships between Reco measured at field sites globally and land surface temperature, gross primary production and soil water content. Trends 1982–2015 were quantified, and the contributions from terrestrial regions to the spatiotemporal variability were evaluated. Results: The Reco model (LGS‐Reco) captured the between‐site and intra‐ and interannual variability in field‐observed Reco and soil respiration well in comparison with other Earth observation‐based products. The global annual Reco was on average 105.6 ± 2.3 Pg C for 1982–2015, which is close to 105 Pg C according to residuals of the carbon exchange processes within the global carbon budgets. The trend in global terrestrial Reco 1982–2015 was 0.19 ± 0.02 Pg C y−1, with the strongest positive trends found in cropland areas, whereas negative trends were primarily observed for savannah/shrublands of Southern Africa and South America. Trends were especially strong during the eighties and nineties, but substantially smaller 1998–2015. Main Conclusions: The LGS‐Reco model revealed a substantial increase in global Reco during recent decades. However, the growth rates of global Reco were slower during 1998–2015, partially explaining the reduced growth rates of atmospheric CO2 during this period. The LGR‐Reco product may be an essential source for studying carbon sources and sinks and functioning of the Earth system. [ABSTRACT FROM AUTHOR]

Divergence in the acoustic structure of mate-attraction signals between closely related taxa can contribute to reproductive isolation and speciation, and acoustic differences are often useful for identifying otherwise similar taxa from recordings. The Brewer’s Sparrow (Spizella breweri) is a migratory oscine songbird with 2 recently diverged subspecies. The nominate subspecies (S. b. breweri) primarily breeds in sagebrush (Artemisia spp.) shrublands in the western United States and southwestern Canada, whereas the Timberline Sparrow (S. b. taverneri) breeds in alpine shrubs and conifer krummholz near treeline in mountain ranges from east-central Alaska to northwestern Montana. Quantitative comparison of the acoustic structure of Brewer’s Sparrow mate-attraction songs is needed to help resolve the outstanding debate regarding the taxonomic status of S. b. taverneri and improve subspecific identification from song recordings. I compared the acoustic structure of 181 short song types from 180 male S. b. breweri and 22 short song types from 20 male S. b. taverneri recorded from across each subspecies’ breeding range. Despite extreme variation in acoustic structure of short songs among individuals, 19 acoustic variables differed between subspecies. Short song types of S. b. taverneri averaged 19.3%–22.1% lower maximum frequency, 4.9%–15.9% higher minimum frequency, 36.7%–42.6% narrower frequency bandwidth, and 12.9%–26.0% lower aggregate entropy (a measure of sound complexity) than those of S. b. breweri across acoustic elements (song, section, syllable, and note). Random forest classification analysis identified 10 acoustic variables important for distinguishing between short songs of the 2 subspecies and correctly classified 89.2% (95% CI 84.1% to 93.1%) of songs overall. Principal component scores representing overall acoustic structure showed an abrupt change near the breeding boundary between S. b. breweri and S. b. taverneri but overlapped sufficiently that they did not meet an established “75%–99% rule” for reciprocal diagnosability of subspecies. An easy-to-measure logistic regression threshold based on song bandwidth and mean note bandwidth accurately classified >90% of short songs to subspecies. Additional recordings of S. b. taverneri are needed to improve our understanding of geographic variation in the song of that subspecies. Data on responses of males and females to songs of the other subspecies would inform whether acoustic differences are sufficient to impede mate recognition and attraction in areas of potential breeding overlap. [ABSTRACT FROM AUTHOR]

This study endeavors to produce a comprehensive land cover map for Morocco, addressing the absence of such a detailed map in the country. Our research encompasses ecological and climatic aspects specific to Morocco, while the methods used can be adapted to various regions and countries, considering their unique climatic conditions and land cover types. A combination of MODIS and Landsat datasets was employed to create a 5 km resolution Land Use and Land Cover (LULC) map for the entire nation. The process involved the aggregation and advanced processing of these datasets using surface processes algorithms. The resulting LULC map is the first of its kind for Morocco, shedding light on land cover distribution nationwide. It shows that approximately 13.5% of the country is covered by forests, predominantly in the Atlas and Rif mountains, Rabat–Sale, and the southern regions. Grasslands occupy over 16% of the study area, mainly in the north-east and west. Urban areas, including major cities like Casablanca, Rabat, and Marrakech, span nearly 3400 km². Moreover, large areas of shrublands and bare lands are evident across the country, while agricultural lands account for almost 20% of the national territory, mainly in the interior plains and north-western Atlantic coast. This study forms a crucial basis for ecological and climatic research in Morocco and serves as a valuable reference for various disciplines such as agriculture, natural resource management, and climate modeling. The mapping of biophysical parameters for each land cover class is a key feature of our research, and these parameters will be instrumental in a subsequent study examining the impact of urban development on surface climate in Morocco. Overall, our study underscores the importance of understanding biophysical parameters in addressing environmental and societal challenges. [ABSTRACT FROM AUTHOR]

Vegetation net primary productivity (NPP) serves as a crucial and intuitive indicator for assessing ecosystem health. However, the nonlinear dynamics and influencing factors operating at various time scales are not yet fully understood. Here, the ensemble empirical mode decomposition (EEMD) method was used to analyze the spatiotemporal patterns of NPP and its association with hydrothermal factors and anthropogenic activities across different temporal scales for the Yellow River Basin (YRB) from 2000 to 2020. The results indicate that: (1) the annual average NPP was 236.37 g C/m2 in the YRB and increased at rates of 4.64 g C/m2/a1 (R2 = 0.86, p < 0.01) during 2000 to 2020. Spatially, nonlinear analysis indicates that 72.77% of the study area exhibits a predominantly increasing trend in NPP, while 25.17% exhibits a reversing trend. (2) On a 3-year time scale, warming has resulted in an increase in NPP in the majority of areas of the study area (69.49%). As the time scale widens, the response of vegetation to climate change becomes more prominent; especially under the long-term trend, the percentage areas of the correlation between vegetation and precipitation and temperature increased with significance, reaching 48.21% and 11.57%, respectively. (3) Through comprehensive time analysis and multivariate regression analysis, it was confirmed that both human activities and climate factors had comparable impacts on vegetation growth. Among different vegetation types, climate was still the main factor affecting grassland NPP, and only 15.74% of grassland was affected by human activities. For shrubland, forest, and farmland, human activity was a dominating factor for vegetation NPP change. There are still few studies on vegetation change using nonlinear methods in the Yellow River Basin, and most studies have not considered the effect of time scale on vegetation evolution. The findings highlight the significance of multi-time scale analysis in understanding the vegetation dynamics and providing scientific guidance for future vegetation restoration and conservation efforts. [ABSTRACT FROM AUTHOR]

Two new species and two new subspecies of the satyrine butterfly genus Punargentus Heimlich, P. atusparia sp. n., P. heimlichi sp. n., P. blanchardi libertas ssp. n. and P. atusparia yupania ssp. n., are described from north-central Peru (Ancash, Huánuco and La Libertad). The affinities of the new taxa are evaluated based on molecular data obtained using target enrichment and COI barcoding. Punargentus is fully supported and consists of two branches, the P. lamna clade with four species and P. blanchardi clade with three species, two of which are described here. Species in the P. blanchardi clade occur in Andean shrubland, at altitudes between 2800-3600 m, whereas those in the P. lamna clade occur in puna grassland at 3600-4600 m, with occasional overlaps. Based on their habitat preferences, none of the newly described species are in need of immediate conservation measures. The genus Etcheverrius Herrera is reinstated, with E. chiliensis (Guérin-Méneville) and E. tandilensis (Köhler), comb. n. [ABSTRACT FROM AUTHOR]

Simple Summary: Rockrose (Cistus laurifolius L.) is a pyrophyte species with allelopathic effects that colonizes acid forest soils in the Mediterranean basin. Its continuous spread contributes to increasing wildfire risk, even more so in the current context of forecasts of increasingly intense and prolonged heat waves and droughts. Its mechanized collection and transformation into biofuels contributes to climate change mitigation, the economic development of rural areas and wildfire risk reduction. Biomass storage is an essential requirement in the supply chain of bio-refineries and biomass plants. This research aims to evaluate the influence of long-term outdoor storage (1 year) of baled rockrose shrub biomass on the quality of biofuels (30 mm milled material and pellets), on pre-treatment processes and on combustion emissions in an industrial boiler. After storage, no significant differences were observed in the biomass pre-treatment processes or in the emissions in an industrial combustion boiler. Biomass weight loss was 12% after storage. Some quality biofuels parameters improved, with the reduction in ash content being the most prominent aspect, which allowed 30 mm of milled material to be classified as I1, according to ISO 17225-9:2022, and rockrose pellets as class I3 for industrial use, according to the ISO 17225-2-2021 standard. Biomass storage is an essential requirement in the supply chain of bio-refineries and power plants. This research aims to evaluate the influence of long-term outdoor storage (1 year) of baled rockrose (Cistus laurifolius L.) shrub biomass on biofuel's quality, pre-treatment processes and on combustion emissions in an industrial boiler. The raw material was obtained from different rockrose shrublands in north central Spain. A total of 233 tWM (tones of wet matter) of biomass were used to produce biofuels (30 mm of milled biomass and Ø 8 mm pellets) in the pre-treatment pilot plants at CEDER-CIEMAT. The combustion tests were conducted in an industrial moving grate boiler with a thermal power of 50 MWth, in a 17 MWe power plant. Outdoor storage improved some biofuel quality parameters, mainly the reduction in ash content, which allowed 30 mm of milled material to be classified as class I1 (ISO 17225-9:2022) and pellets as class I3 (ISO 17225-2-2021). No significant differences were observed in the total specific mass flow and energy consumption in the pre-treatment processes. The combustion tests had similar results, with the emissions being below the limits established in the directive (EU) 2015/2193. The results obtained indicated that the 1-year outdoor storage of rockrose-baled biomass, under Mediterranean conditions, was feasible for its subsequent use as biofuel. [ABSTRACT FROM AUTHOR]

Multiyear periods (≥4 years) of extreme rainfall are increasing in frequency as climate continues to change, yet there is little understanding of how rainfall amount and heterogeneity in biophysical properties affect state changes in a sequence of wet and dry periods. Our objective was to examine the importance of rainfall periods, their legacies, and vegetation and soil properties to either the persistence of woody plants or a shift toward perennial grass dominance and a state reversal. We examined a 28‐year record of rainfall consisting of a sequence of multiyear periods (average, dry, wet, dry, average) for four ecosystem types in the Jornada Basin. We analyzed relationships between above ground net primary production (ANPP) and rainfall for three plant functional groups that characterize alternative states (perennial grasses, other herbaceous plants, dominant shrubs). A multimodel comparison was used to determine the relative importance of rainfall, soil, and vegetation properties. For perennial grasses, the greatest mean ANPP in mesquite‐ and tarbush‐dominated shrublands occurred in the wet period and in the dry period following the wet period in grasslands. Legacy effects in grasslands were asymmetric, where the lowest production was found in a dry period following an average period, and the greatest production occurred in a dry period following a wet period. For other herbaceous plants, in contrast, the greatest ANPP occurred in the wet period. Mesquite was the only dominant shrub species with a significant positive response in the wet period. Rainfall amount was a poor predictor of ANPP for each functional group when data from all periods were combined. Initial herbaceous biomass at the plant scale, patch‐scale biomass, and soil texture at the landscape scale improved the predictive relationships of ANPP compared with rainfall alone. Under future climate, perennial grass production is expected to benefit the most from wet periods compared with other functional groups with continued high grass production in subsequent dry periods that can shift (desertified) shrublands toward grasslands. The continued dominance by shrubs will depend on the effects that rainfall has on perennial grasses and the sequence of high‐ and low‐rainfall periods rather than the direct effects of rainfall on shrub production. [ABSTRACT FROM AUTHOR]

Questions: What are the main vegetation types of forest and shrubland vegetation in central and eastern Euxine Turkey and SW Georgia? What are the main environmental factors affecting their diversity? What is their syntaxonomic position? Can we integrate them into the European vegetation classification system? Location: Central and eastern Euxine Turkey and SW Georgia. Methods: We collected 3104 vegetation plots of forest and shrubland vegetation in the study region and performed Two‐Way Indicator Species Analysis (TWINSPAN) classification. We described vegetation types based on the classification results, expert knowledge and information from literature sources. We defined diagnostic species and prepared distribution maps for each vegetation type. To determine the most significant environmental variables on floristic differentiation, we used canonical correspondence analysis. Detrended correspondence analysis with passive projection of most significant environmental variables was run to interpret the environmental variation of vegetation types. Results: The studied vegetation was divided into 29 vegetation types related to seven main vegetation groups: relict Mediterranean forests and shrubland (mainly along the coastline, beside some inland localities), lowland to submontane forests, central Euxine mountain forests, eastern Euxine (Colchic) mountain forests, subeuxine forests, azonal riparian forests and subalpine and alpine shrubland. Elevation is the most important factor causing the differentiation in vegetation. It is followed by longitude and latitude. Among climatic variables, temperature seasonality, annual precipitation and precipitation of the wettest quarter are the most significant factors for vegetation differentiation. These factors correlate with the reduction of maritime climate and geomorphological features. Conclusions: Vegetation types mostly correspond to the syntaxa accepted in the EuroVegChecklist. However, some of them do not appear in the EuroVegChecklist since they appear only beyond Europe. We described three syntaxa as new: Abietion equi‐trojani, Querco cerridis‐Carpinion orientalis and Piceo orientalis‐Fagenion orientalis. The study revealed high vegetation diversity of the region that should be taken into consideration in ecosystem management and used as a reference in restoration and mitigation of the effects of global changes. [ABSTRACT FROM AUTHOR]

The mountain ranges that cross the highlands of San Luis Potosí (Chihuahuan Desert, Mexico) constitute an important refuge for different types of flora and vegetation whose distribution limits occur within these orographic and climatic 'islands'. Shrub communities are generally included within the concepts of microphyllous, rosetophyllous and submontane scrub types. In addition, small woods of pine, oak and juniper occur towards higher zones. According to the biogeographic typology, the study area is in the Mexican Xerophytic region (Chihuahuan Province) and dominated by a Tropical Xeric bioclimate, although Tropical Desert and Tropical Pluviseasonal bioclimates also occasionally appear. The shrubs under study are included in Mesotropical and Thermotropical thermotypes. Eighty phytosociological relevés were carried out at elevations of between 1300 and 2200 m a.s.l., including a total of 208 species. Multivariate analysis enabled identification of four groups corresponding to other associations: Echinocacto platyacanthi-Agavetum lechuguillae, Ferocacto pilosi-Gochnatietum hypoleucae, Dasylirio longissimae-Heliettetum parvifoliae and Berberido trifoliolatae-Juniperetum coahuilensis. Aspects related to the structure, composition, bioclimatic affinity, dynamic-catenal position and syntaxonomic arrangement are discussed. Finally, the importance of these plant communities as refuge habitats for the flora included in some conservation categories and the threats that affect them are addressed. [ABSTRACT FROM AUTHOR]

In this study, we conducted a global assessment of the sensitivity of vegetation greenness (VGS) to precipitation and to the estimated Lagrangian precipitation time series of oceanic (PLO) and terrestrial (PLT) origin. The study was carried out for terrestrial ecosystems consisting of 9 biomes and 139 ecoregions during the period of 2001–2018. This analysis aimed to diagnose the vegetative response of vegetation to the dominant component of precipitation, which is of particular interest considering the hydroclimatic characteristics of each ecoregion, climate variability, and changes in the origin of precipitation that may occur in the context of climate change. The enhanced vegetation index (EVI) was used as an indicator of vegetation greenness. Without consideration of semi-arid and arid regions and removing the role of temperature and radiation, the results show the maximum VGS to precipitation in boreal high-latitude ecoregions that belong to boreal forest/taiga: temperate grasslands, savannas, and shrublands. Few ecoregions, mainly in the Amazon basin, show a negative sensitivity. We also found that vegetation greenness is generally more sensitive to the component that contributes the least to precipitation and is less stable throughout the year. Therefore, most vegetation greenness in Europe is sensitive to changes in PLT and less to PLO. In contrast, the boreal forest/taiga in northeast Asia and North America is more sensitive to changes in PLO. Finally, in most South American and African ecoregions, where PLT is crucial, the vegetation is more sensitive to PLO, whereas the contrast occurs in the northern and eastern ecoregions of Australia. [ABSTRACT FROM AUTHOR]

The accurate estimation of gross primary productivity (GPP) plays an important role in accurately projecting the terrestrial carbon cycle and climate change. Satellite-driven near-infrared reflectance (NIRv) can be used to estimate GPP based on their nearly linear relationship. Notably, previous studies have reported that the relationship between NIRv and GPP seems to be biome-specific (or land cover) at the ecosystem scale due to both biotic and abiotic effects. Hence, the NIRv-based estimation of GPP may be influenced by land cover changes (LCC) and the discrepancies in multisource products (DMP). However, these issues have not been well understood until now. Therefore, this study took the Yellow River basin (YRB) as the study area. This area has experienced remarkable land cover changes in recent decades. We used Moderate-Resolution Imaging Spectroradiometer (MODIS) and European Space Agency (ESA) Climate Change Initiative (CCI) land cover products (termed MCD12C1 and ESACCI, respectively) during 2001–2018 to explore the impact of land cover on NIRv-estimated GPP. Paired comparisons between the static and dynamic schemes of land cover using the two products were carried out to investigate the influences of LCC and DMP on GPP estimation by NIRv. Our results showed that the dominant land cover types in the YRB were grassland, followed by cropland and forest. Meanwhile, the main transfer was characterized by the conversion from other land cover types (e.g., barren) to grassland in the northwest of the YRB and from grassland and shrubland to cropland in the southeast of the YRB during the study period. Moreover, the temporal and spatial pattern of GPP was highly consistent with that of NIRv, and the average increase in GPP was 2.14 gCm−2yr−1 across the YRB. Nevertheless, it is shown that both LCC and DMP had significant influences on the estimation of GPP by NIRv. That is, the areas with obvious differences in NIRv-based GPP closely correspond to the areas where land cover types dramatically changed. The achievements of this study indicate that considering the land cover change and discrepancies in multisource products would help to improve the accuracy of NIRv-based estimated GPP. [ABSTRACT FROM AUTHOR]

Quantifying how climate factors affect vegetation phenology is crucial for understanding climate-vegetation interactions and carbon and water cycles under a changing climate. However, the effects of different intensities of extreme climatic events on vegetation phenology remain poorly understood. Using a long-term solar-induced chlorophyll fluorescence dataset, we investigated the response of vegetation phenology to extreme temperatures and precipitation events of different intensities across the Tibetan Plateau (TP) from 2000 to 2018. We found that the effect of maximum temperature exposure days (TxED) and minimum temperature exposure days (TnED) on the start of the growing season (SOS) was initially delayed and shifted to advance along the increasing temperature gradients. However, the response of the end of the growing season (EOS) to TxED and TnED shifted from an advance to a delay with increasing temperature gradients until the temperature thresholds were reached, above which thresholds produced an unfavorable response to vegetation growth and brought the EOS to an early end. The corresponding maximum and minimum temperature thresholds were 10.12 and 2.54°C, respectively. In contrast, cumulative precipitation (CP) was more likely to advance SOS and delay EOS as the precipitation gradient increased, but the advance of SOS is gradually weakening. Four vegetation types (i.e., forest, shrubland, meadow, and steppe) showed similar trends in response to different climates, but the optimal climatic conditions varied between the vegetation types. Generally, meadow and steppe had lower optimal temperatures and precipitation than forest and shrubland. These findings revealed the divergent responses of vegetation phenology to extreme climate events of different intensities, implying that the SOS will continue to advance with warming, whereas the EOS may undergo a partial transformation from delayed areas to advanced areas with continued warming. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) hosts a variety of vegetation types ranging from broadleaved and needle-leaved forests at the lower altitudes and mesic areas to alpine grassland at the higher altitudes and xeric areas. Accurate and detailed mapping of the vegetation distribution on TP is essential for an improved understanding of climate change effects on terrestrial ecosystems. Yet, existing land cover datasets of TP are either provided at a low spatial resolution or have insufficient vegetation types to characterize certain unique TP ecosystems, such as the alpine scree. Here, we produced a 10 m resolution TP land cover map with 12 vegetation classes and 3 non-vegetation classes for the year 2022 (referred as TP_LC10-2022) by leveraging state-of-the-art remote sensing approaches including the Sentinel-1 and Sentinel-2 imagery, environmental and topographic datasets, and 4 machine learning models using Google Earth Engine platform. Our dataset TP_LC10-2022 achieved an overall classification accuracy of 86.5% with a Kappa coefficient of 0.854. By comparing with 4 existing global land cover products, TP_LC10-2022 showed significant improvements in terms of reflecting local-scale vertical variations in the southeast TP region. Moreover, we found that alpine scree occupied 13.99% of the TP region which was ignored in existing land cover datasets, and that shrublands occupied 4.63% of the TP region characterized by distinct forms of deciduous shrublands and evergreen shrublands largely determined by topography and missed in existing land cover datasets. Our dataset provides a solid foundation for further analyses which need accurate delineation of these unique vegetation types in TP. The TP_LC10-2022 and the sample dataset are freely available at https://doi.org/10.5281/zenodo.8228112 (Huang et al., 2023b) and https://doi.org/10.5281/zenodo.8227942 (Huang et al., 2023a) respectively. Additionally, the classification map can be viewed through https://cold-classifier.users.earthengine.app/view/tplc10-2022. [ABSTRACT FROM AUTHOR]

Aims: Prolonged fire suppression in conifer forests of the Sierra Nevada Mountain range, California, USA, has led to ingrowth of conifer seedlings, converting the open heterogeneous structure into uniformly dense and layered forest. The threat of a stand‐replacing fire has increased because of fuel buildup in combination with rising drought and extreme heat frequency caused by climate change. With such high severity fire, there is also rising concern regarding conifer forest converting to shrublands as severe fire favors the establishment of large shrub patches altering landscape vegetation pattern and heterogeneity. However, a clear understanding of the effects of increased fire severity, size, and frequency on landscape‐scale heterogeneity and postfire patch dynamics is lacking, which is critical in implementing restoration and forest management activities. Our aim was to understand multiscale dynamics and spatial heterogeneity patterns of conifer forests and chaparral shrublands due to repeated mixed‐severity fire. Location: A mosaic of burned and unburned patches spanning the boundary of Lassen and Plumas National Forests, CA, USA. Methods: We used secondary geospatial landcover data classified by cover type before modern fires (1999) and after eight modern fires (2014). We calculated various landscape diversity and fragmentation metrics at patch and landscape scales using FRAGSTATS for comparison before and after fires. Results: At the fire severity patch scale, high‐severity fire reduced vegetation cover type heterogeneity by half, but reburning at low to moderate severity nearly doubled cover type heterogeneity. At the full landscape scale mixed‐severity fire, including all burn severities, increased vegetation cover type heterogeneity. Fragmentation indexes confirmed that fire created larger patches of shrub and fragmented patches of conifer forest. Conclusions: The effects of frequent large fire events on vegetation pattern and heterogeneity vary with the scale of analysis. Hence, heterogeneity and vegetation pattern change need to be evaluated at more than one scale to understand past and future ecological processes before prioritizing management actions for the conifer forests of the Sierra Nevada Mountain range. [ABSTRACT FROM AUTHOR]

Aim: Studies investigating the determinants of plant invasions rarely examine multiple factors and often only focus on the role played by native plant species richness. By contrast, we explored how vegetation structure, landscape features and climate shape non‐native plant invasions across New Zealand in mānuka and kānuka shrublands. Location: New Zealand. Method: We based our analysis on 247 permanent 20 × 20‐m plots distributed across New Zealand surveyed between 2009 and 2014. We calculated native plant species richness and cumulative cover at ground, understorey and canopy tiers. We examined non‐native species richness and mean species ground cover in relation to vegetation structure (native richness and cumulative cover), landscape features (proportion of adjacent anthropogenic land cover, distance to nearest road or river) and climate. We used generalized additive models (GAM) to assess which variables had greatest importance in determining non‐native richness and mean ground cover and whether these variables had a similar effect on native species in the ground tier. Results: A positive relationship between native and non‐native plant species richness was not due to their similar responses to the variables examined in this study. Higher native canopy richness resulted in lower non‐native richness and mean ground cover, whereas higher native ground richness was associated with higher native canopy richness. Non‐native richness and mean ground cover increased with the proportion of adjacent anthropogenic land cover, whereas for native richness and mean ground cover, this relationship was negative. Non‐native richness increased in drier areas, while native richness was more influenced by temperature. Main Conclusions: Adjacent anthropogenic land cover seems to not only facilitate non‐native species arrival by being a source of propagules but also aids their establishment as a result of fragmentation. Our results highlight the importance of examining both cover and richness in different vegetation tiers to better understand non‐native plant invasions. [ABSTRACT FROM AUTHOR]

The present study focuses on the microvertebrate fossil material retrieved from the three fossiliferous units of Kalamakia cave dating from ca. 90–25 kya BP, to identify the accumulation agents of the assemblage and the processes that affected it post-depositionally. This was done through the quantification of specific indices described in the literature concerning breakage, digestion and other types of modifications observed upon the surface of the specimens. Furthermore, the Taxonomic Habitat Index was calculated to reconstruct the possible habitat types in the surrounding area. Regarding the results on taphonomy, significant amounts of post-depositional breakage were observed, possibly resulting from trampling and, secondarily, modifications from the occasionally naturally occurring high humidity within a cave. The main accumulators of the microvertebrate assemblage seem to have been barn owls either independently or jointly with long-eared owls and/or owlets. Concerning the habitats possibly present in the area, the existence of mixed habitats varying between relative expansions of shrublands, grasslands, rocky areas and (limited) deciduous forests was identified, while the occasional presence of water bodies was also revealed. Shifts between the percentages of different habitats were not great but could be correlated with climatic events within a geochronological context. [ABSTRACT FROM AUTHOR]

We estimated the amount of carbon (C) stored in terrestrial ecosystems of the Chilean Patagonia and the proportion within protected areas. We used existing public databases that provide information on C stocks in biomass and soils. Data were analysed by ecosystem and forest type in the case of native forests. Our results show that some ecosystems have been more extensively studied both for their stocks in biomass and soils (e.g. forests) compared with others (e.g. shrublands). Forests and peatlands store the largest amount of C because of their large stocks per hectare and the large area they cover. The total amount of C stored per unit area varies from 261.7 to 432.8 Mg C ha−1, depending on the published value used for soil organic C stocks in peatlands, highlighting the need to have more precise estimates of the C stored in this and other ecosystems. The mean stock in national parks (508 Mg C ha−1) is almost twice the amount stored in undisturbed forests in the Amazon. State and private protected areas contain 58.9% and 2.1% of the C stock, respectively, playing a key role in protecting ecosystems in this once pristine area. [ABSTRACT FROM AUTHOR]

Protected Areas (PAs) play a crucial role in the conservation and appreciation of the biological, ecological and socio-cultural elements of the landscape. These areas, in line with their creation objectives, provide various environmental services such as watershed protection, landscape and biodiversity preservation, and regulation of ecosystem processes. Additionally, they offer opportunities for research, education, and environmental training. Researchers from the Facultad de Agronomía, UNLPam are currently conducting two projects related to the theme of fire in Parque Nacional Lihué Calel, focusing on the impact of recurrent wildfires and the assessment of prescribed burns. Undertaking such investigations within a national park creates an interdisciplinary and interinstitutional working space, addressing various topics with the aim of transforming gathered information into practical management tools. Collaboration with PA technicians is essential to achieve the proposed objectives and serves as the link between information generation and effective implementation. [ABSTRACT FROM AUTHOR]

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad‐scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long‐term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland–shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one‐time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long‐term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change. [ABSTRACT FROM AUTHOR]

Land cover change is one of the major problems facing the world, and as human needs increase, so the inappropriate use of land, climate change, precipitation variability, temperature rise, and the frequency of extreme natural disasters are the primary factors influencing land cover change. We investigate how the land cover in Khar Yamaat Nature Reserve and its buffer zone changed between 2014 and 2019. Using Landsat satellite images between September 2014 and September 2019, the land cover change was classified into three ways using the pixel based supervised classification method: Maximum likelihood classification, K-Nearest neighbor, and Minimum distance classifier. Based on common plant species and environmental factors, land cover categories were divided into nine categories: mountain steppe, dry steppe, shrubland, degraded area, agriculture land, sand, lake, river, and meadow. To detect land cover changes, the "Maximum likelihood classification" that accurately depicts the spatial distribution of each land cover class and has a high statistical significance was chosen. During the six-year period from 2014 to 2019, the area of dry steppes decreased by 42.232 hectares (42.8%), mountain steppes 3.797 hectares (3.84%), rivers 1.000 hectares (1.1%), meadows 1.581 hectares (1.6%), and agriculture 723 hectares (0.7%), while degraded area increased by 39.480 hectares. For 2014 and 2019, the overall accuracy was 95.96 (k=0.94) and 93.39 (k=0.93). [ABSTRACT FROM AUTHOR]

The lack of information regarding biodiversity status hampers designing and implementing conservation strategies and achieving future targets. Northern Pakistan consists of a unique ecoregion mosaic which supports a myriad of environmental niches for anuran diversity in comparison to the deserts and xeric shrublands throughout the rest of the country. In order to study the niche suitability, species overlap and distribution patterns in Pakistan, we collected observational data for nine anuran species across several distinct ecoregions by surveying 87 randomly selected locations from 2016 to 2018 in Rawalpindi District and Islamabad Capital Territory. Our model showed that the precipitation of the warmest and coldest quarter, distance to rivers and vegetation were the greatest drivers of anuran distribution, expectedly indicating that the presence of humid forests and proximity to waterways greatly influences the habitable range of anurans in Pakistan. Sympatric overlap between species occurred at significantly higher density in tropical and subtropical coniferous forests than in other ecoregion types. We found species such as Minervarya spp., Hoplobatrachus tigerinus and Euphlyctis spp. preferred the lowlands in proximal, central and southern parts of the study area proximal to urban settlements, with little vegetation and higher average temperatures. Duttaphrynus bengalensis and D. stomaticus had scattered distributions throughout the study area with no clear preference for elevation. Sphaerotheca pashchima was patchily distributed in the midwestern extent of the study area as well as the foothills to the north. Microhyla nilphamariensis was widely distributed throughout the study area with a preference for both lowlands and montane terrain. Endemic frogs (Nanorana vicina and Allopaa hazarensis) were observed only in locations with higher elevations, higher density of streams and lower average temperatures as compared to the other seven species sampled. It is recommended to provide legal protection to amphibians of Pakistan, especially endemic species, through revision in the existing wildlife laws. We suggest studying the effectiveness of existing amphibian tunnels and corridors or designing new ones tailored to the needs of our species to prevent their local extinction due to ongoing or proposed urban development which might affect their dispersal and colonization. [ABSTRACT FROM AUTHOR]

Climate change forecasts indicate that the frequency and intensity of extreme climate events will increase in the future; these changes will have important effects on ecosystem stability and function. An important arid region of the world, Central Asia has ecosystems that are extremely vulnerable to extreme weather events. However, few studies have investigated the resistance and resilience of this region's ecosystems to extreme weather events. In this study, first, the extreme drought/wet threshold was calculated based on the 113-year (1901–2013) standardized precipitation–evapotranspiration index (SPEI); second, moderate resolution imaging spectroradiometer (MODIS) remote sensing data were applied to calculate ecosystem water use efficiency (WUE) and quantify ecosystem resistance and resilience after different extreme climate events; and finally, differences in the changes of various ecosystem types before and after climate events were assessed. The results showed the following: (1) The average SPEI was 0.073, and the thresholds of extreme wetness and drought were 0.91 and −0.67, respectively. Central Asia experienced extreme wet periods in 2002 and 2003 and a drought period in 2008. (2) Suitable wetness levels can increase the resistance of an ecosystem; however, continuous wetness reduces ecosystem resistance, as does drought. Wet areas had strong resilience after wet events, and arid areas had strong resilience after drought events. (3) During both wet and drought years, the transition between shrubland and grassland caused changes in ecosystem resistance and resilience. These findings are important for understanding the impact of future climate change on ecosystem stability. [ABSTRACT FROM AUTHOR]

Monitoring and estimating drought impact on plant physiological processes over large regions remains a major challenge for remote sensing and land surface modeling, with important implications for understanding plant mortality mechanisms and predicting the climate change impact on terrestrial carbon and water cycles. The Orbiting Carbon Observatory 3 (OCO‐3), with its unique diurnal observing capability, offers a new opportunity to track drought stress on plant physiology. Using radiative transfer and machine learning modeling, we derive a metric of afternoon photosynthetic depression from OCO‐3 solar‐induced chlorophyll fluorescence (SIF) as an indicator of plant physiological drought stress. This unique diurnal signal enables a spatially explicit mapping of plants' physiological response to drought. Using OCO‐3 observations, we detect a widespread increasing drought stress during the 2020 southwest US drought. Although the physiological drought stress is largely related to the vapor pressure deficit (VPD), our results suggest that plants' sensitivity to VPD increases as the drought intensifies and VPD sensitivity develops differently for shrublands and grasslands. Our findings highlight the potential of using diurnal satellite SIF observations to advance the mechanistic understanding of drought impact on terrestrial ecosystems and to improve land surface modeling. [ABSTRACT FROM AUTHOR]

During the cold arctic winter, small mammals like lemmings seek refuge inside the snowpack to keep warm and they dig tunnels in the basal snow layer, usually formed of a soft depth hoar, to find vegetation on which they feed. The snowpack, however, is a heterogenous medium and lemmings should use habitats where snow properties favor their survival and winter reproduction. We determined the impact of snow physical properties on lemming habitat use and reproduction in winter by sampling their winter nests for 13 years and snow properties for 6 years across 4 different habitats (mesic, riparian, shrubland, and wetland) on Bylot Island in the Canadian High Arctic. We found that lemmings use riparian habitat most intensively because snow accumulates more rapidly, the snowpack is the deepest and temperature of the basal snow layer is the highest in this habitat. However, in the deepest snowpacks, the basal depth hoar layer was denser and less developed than in habitats with shallower snowpacks, and those conditions were negatively related to lemming reproduction in winter. Shrubland appeared a habitat of moderate quality for lemmings as it favored a soft basal snow layer and a deep snowpack compared with mesic and wetland, but snow conditions in this habitat critically depend on weather conditions at the beginning of the winter. With climate change, a hardening of the basal layer of the snowpack and a delay in snow accumulation are expected, which could negatively affect the winter habitat of lemmings and be detrimental to their populations. [ABSTRACT FROM AUTHOR]

Aims: Changes in global precipitation regimes are caused by an increase in the frequency of extremely wet and dry years inter-annually and extreme rainfall intensity intra-annually. However, the interactive effects of these precipitation variabilities remain relatively unclear. Methods: To better understand the responses of semi-arid ecosystems to precipitation changes, a manipulative field experiment was conducted with multilevel annual precipitation amounts and precipitation allocation, at a temporal scale, within desert shrubland in the Mu Us Desert in northern China. Results: With fewer, yet larger, precipitation events, the annual net primary production (ANPP) was found to increase in dry years. The annual precipitation amount and precipitation intervals affected the community ANPP. However, precipitation intervals only affected the ANPP in the context of low precipitation amounts. Extending the intervals between precipitation events significantly increased the ANPP of shrubs and weeds however decreased that of grasses. The nursery effect of shrubs on the herbs and competition between the grass and weeds can interfere with the response of the community ANPP to precipitation. Conclusions: With a global shift toward precipitation regimes dominated by lower frequency and higher intensity, an increase in productivity in this desert shrubland ecosystem is expected, with shrubs largely dominating the community composition. This study advances the current understanding of how community productivity is shaped by the interaction between inter-annual precipitation amount and intra-annual precipitation distribution. Meanwhile, plant–plant interactions between different functional species also have essential roles in community productivity stabilization within the context of precipitation change. [ABSTRACT FROM AUTHOR]

Time-lag effect of vegetation refers to the growth and distribution patterns out of sync with the varying climate. Vegetation cannot adapt immediately the climate change, leading to adjustment time. Previous research has focused mainly on the overall growth of vegetation under climate monitor or changes in a single type of vegetation. It is still lacking in the timelag effect of vegetation types and their response to the climate. Therefore, this study aims to determine the vegetation activity and its response to climate change. The lag time of different vegetation types was also clarified in response to the hydrothermal changes. The Normalized Difference Vegetation Index (NDVI) and meteorological grid data were monthly collected from 1982 to 2015. The GIMMS NDVI dataset was also selected, together with the CRU precipitation and air temperature dataset. Sen + Mann-Kendall trend analysis was then conducted to obtain the interannual change rate of vegetation NDVI in over the past 34 years. At the same time, a significance test was carried out on the NDVI change trend, in order to distinguish the significant improvement and degradation areas. The growth and degradation of different vegetation types were statistically determined after the test. The lagged partial correlation analysis was used to calculate the partial correlation coefficients between vegetation NDVI and precipitation and air temperature in the current month, the previous month, the first previous two months, and the first previous three months. Then, the partial correlation coefficients were also synthesized to obtain the maximum partial correlation coefficient. The lag time was set as the maximum partial correlation coefficient. The dynamic characteristics of the vegetation pattern change over the past 34 years were presented to determine the relationship between vegetation NDVI and climate response. The lag effect was obtained in the different vegetation types on climate response. The results showed that: 1) A spatial distribution pattern of vegetation was achieved in the higher vegetation in northern Xinjiang than that in the southern, and higher in the west than that in the east. There was an overall "greening" trend in the study area. Specifically, the significantly improved and stable unchanged areas accounted for 20.6%, and 65.7%, respectively. The areas insignificant improvement and degradation accounted for 3.3%, and 10.4%, respectively. There was no area with significant degradation. In the spatial distribution, a significant NDVI increase was found in the oasis around the Tarim Basin and the northern section of the Tianshan Mountains, whereas, the Ili region showed a trend of degradation. In vegetation types, the cultivated vegetation shared the largest improvement area, accounting for 75.3%, while, the degraded area of coniferous forest was the largest, accounting for 24.2%; 2) There was a lag response of 72% of vegetation areas to the precipitation at the monthly time scale, with an average lag time of 1.1 months, while the lag response of 70% of vegetation areas to air temperature, with an average lag time of 1.4 months. The higher the lagged correlation coefficient between vegetation and climate elements was, the higher the response speed was. Overall, the vegetation was much more sensitive to the precipitation. 3) Different types of vegetation varied greatly in response to the precipitation and air temperature. Precipitation was the main promoting factor for the grassland, shrubland, and coniferous forest, while air temperature shared the strongest impact on the broad-leaved forest. The lagged partial correlation coefficients between different vegetation types and precipitation were higher than those of air temperature. The response time of different vegetation types to air temperature was longer than that of precipitation. There were lagged effects in the response of different vegetation to both precipitation and air temperature. The correlation between vegetation and precipitation was higher in Xinjiang, indicating a more rapid response of vegetation to precipitation than that to air temperature. [ABSTRACT FROM AUTHOR]