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[Display omitted] • Climate change triggers shrub encroachment into alpine grasslands and snowbeds. • Back from the future aims restore the encroached vegetation through shrub removal. • A multicriteria research protocol is proposed to assess the experiment feasibility. • The data obtained assessed the full comparability of control and manipulation zones. • The protocol allows assess the experiment feasibility and its long-term monitoring. Climate change triggers changes of vegetation floristic composition, physiognomy and even the onset of new successional pathways, requiring adequate, robust and replicable methodological approaches to properly track these changes. In tundra ecosystems woody plants are encroaching into grasslands and snowbeds, inducing their gradual regression. "Back from the Future" is a pilot project performing selective shrub removal from grasslands and snowbeds in the Italian Central Alps to contrast climate-driven shrub encroachment and promote the recovery and active conservation of vegetation communities. Here we propose a multi-criteria research protocol providing a quantitative tool for: a) the set-up of the manipulation experiment; b) the assessment of the full comparability of manipulation and control areas; c) the long-term monitoring of the efficiency of the manipulation experiment. The experiment was carried out in three study sites (Braulio, Cedec, Sforzellina) across an elevation gradient from the subalpine to the nival belts in the Italian Central Alps. At each study site we identified a control and a manipulation zone to assess the efficiency of the manipulation experiment compared to the natural ecosystem dynamics. The multi-criteria research protocol integrates different sampling approaches: mapping and morphological characterization of trees and shrubs; phytosociological survey of permanent plots; grid-point intercept survey of permanent plots; line-intercept survey along transects; allometric shrub measurements along transects. Our data show that this protocol is applicable to different vegetation types, across different elevation belts, and is suitable to match different targets and/or bioindicators of change. Indeed, the limitations of each selected method when individually applied can be overcome by their combination. Our data demonstrate the full comparability of the control and manipulation zone at each of the three study sites in terms of species richness, floristic composition, species coverage, shrub characteristics and volume. Our results supported the feasibility of this protocol as tool for the set-up of the experiment, to assess the full comparability of control and manipulation zones, and perform a detailed monitoring of the effects and the feasibility of the restoration action and the success and efficiency of this pilot project. The protocol elaborated in the frame of this pilot project could be exported beyond the local context and applied to similar mountain regions, especially in the European Alps, for the planning, set up and monitoring of good land management practices aiming to climate change mitigation. [ABSTRACT FROM AUTHOR]

• DayCent now includes microbial-explicit decomposition and soil carbon stabilization. • Refined perennial plant traits better represent litter chemistry. • Microbe model projects less soil carbon under future climate than first-order model. Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Climate zone shifts of northeastern US and maritime Canada delineated and characterized. • Based on differing spatial resolutions, optimal zones of 3, 9, 15, and 21 were determined. • Current high diversity of distinct climate zones in region is anticipated to decrease. • Projected shifts have important implications for regional forest structure and productivity. Climate zones play a significant role in shaping the forest ecosystems located within them by influencing multiple ecological processes, including growth, disturbances, and species interactions. Therefore, delineation of current and future climate zones is essential to establish a framework for understanding and predicting shifts in forest ecosystems. In this study, we developed and applied an efficient approach to delineate regional climate zones in the northeastern United States and maritime Canada, aiming to characterize potential shifts in climate zones and discuss associated changes in forest ecosystems. The approach comprised five steps: climate data dimensionality reduction, sampling scenario design, cluster generation, climate zone delineation, and zone shift prediction. The climate zones in the study area were delineated into four different orders, with increasing subzone resolutions of 3, 9, 15, and 21. Furthermore, projected climate normals under Shared Socioeconomic Pathways 4.5 and 8.5 scenarios were used to predict the shifts in climate zones until 2100. Our findings indicate that climate zones characterized by higher temperatures and lower precipitation are expected to become more prevalent, potentially becoming the dominant climate condition across the entire region. Thes changes are likely to alter regional forest composition, structure, and productivity. In short, such shifts in climate underscore the significant impact of environmental change on forest ecosystem dynamics and carbon sequestration potential. [ABSTRACT FROM AUTHOR]

• Combined application of CASA model and random forest regression models. • Precipitation was identified as a vital climatic factor. • The most important months for climatic factors were identified. • NPP exhibited nonlinear responses across the three analyzed temporal scales. Grassland, as highly vulnerable ecosystem, requires a comprehensive understanding of its dynamics and response patterns to climate factors in response to climate change challenges. While previous research has primarily centered on the influence of interannual climate variability on grassland Net Primary Productivity (NPP), knowledge of the impacts of seasonal or monthly climate variations on annual net primary productivity (ANPP) remains limited. This study investigated the climatic drivers of grassland NPP dynamics in Xinjiang's Altay region from 2000 to 2022 using the Carnegie-Ames-Stanford approach (CASA) model and the random forest regression model. The study examined the significance and patterns of precipitation, solar radiation, temperature, soil moisture, and snowmelt water on NPP at three temporal scales. The results revealed the following key findings: (1) Grassland NPP declined significantly from 2000 to 2009 but showed a gradual increase from 2009 to 2022. Spatially, higher values were observed in the northern region and lower values were observed in the southern region. (2) Precipitation was the primary influential climate factor affecting grassland NPP, followed by solar radiation, temperature, soil moisture, and snowmelt water. In determining the significance of climate factor timing on ANPP, June played a critical role particularly for precipitation, temperature, and soil moisture, while August was essential for solar radiation. Moreover, the importance of snowmelt water had a bimodal distribution, with peaks in April and October. (3) Grassland NPP exhibited diverse nonlinear response dynamics and spatial heterogeneity to various climate factors at different temporal scales. These findings highlight the importance of considering both the magnitude and the local conditions, as well as the timing of climate variations when studying grassland dynamic responses to climate change and predicting future impacts. These insights enhance the comprehension of the intricate dynamics of grassland ecosystems and enhance predictions of their responses to future climate change. [ABSTRACT FROM AUTHOR]

At higher concentrations, tropospheric ozone can cause respiratory difficulties, premature human mortality and can harm vegetation by reducing photosynthesis and its growth. It is an oxidant and also an important greenhouse gas with positive feedback to temperature. It is produced as a byproduct of chemical reactions involving nitrogen oxides (NO x) and volatile organic compounds (VOCs) in the presence of sunlight, rather than being emitted directly to the atmosphere. Here, we analyse the seasonal and inter-annual variability, long-term trends and radiative forcing of the tropospheric column ozone (TPO) in India for the period of 2005–2020 using satellite and ground-based data. The analysis shows very high annual averaged TPO in the Indo-Gangetic Plain (IGP) and North West India, about 45–50 DU. Our findings reveal a significant increase of TPO in India, with the highest trend in the peninsular region (0.295 ± 0.0617 DU/year) and the lowest in North West (0.179 ± 0.048 DU/year). The increase in tropospheric ozone reveals a warming of about 0.5 °C in the troposphere as there is an associated radiative forcing of about 0.2–0.5 W/m2 at the tropopause (125 hPa); indicating that the increasing tropospheric ozone is a great concern for regional warming, public health and ecosystem dynamics. [Display omitted] • High concentrations of tropospheric ozone are found in the Indo-Gangetic Plain. • All regions show increasing ozone with the highest trends in the Peninsular India. • Highest seasonal trends are found during monsoon in all regions (0.3–0.5 DU/year). • Tropospheric ozone alone contributes to a radiative forcing of 0.2–0.5 W/m2. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Rapid change in sunlight from a total solar eclipse offered a unique natural experiment. • Biotic and abiotic responses were investigated using a suite of passive monitoring tools. • Differential response of bird and insect calling activity was observed. • Altered soundscape was associated with changes in photic and thermal conditions. • Integrative technologies offer an assessment method to examine ecological disturbances. Abstract On 21 August 2017, a total solar eclipse crossed the continental United States, providing a unique natural experiment to observe how wildlife and plants respond to rapid and drastic changes in photic conditions using a multi-modal suite of tools. We installed passive time-lapse and infrared cameras, sound recorders, and data loggers in the Central Platte River Valley of Nebraska to study this phenomenon. The eclipse lasted about three hours, and complete obscuration of the sun (totality) lasted for about 2 min and 30 sec. Light values, measured with time-lapse camera systems, decreased 67% on average during totality relative to the daily mean light value. Ambient temperatures decreased by 6.7 °C on average (12% of the daily mean) approximately 11–16 min after totality; concurrently, humidity increased by an average of 12% of the daily mean. We found evidence for altered acoustic activity in response to the eclipse, including site and species-specific changes in the call activities of late season breeding birds and insects in the orders orthoptera and hemiptera. In addition, acoustic indices were differentially correlated with changes in photic and thermal conditions. However, we did not observe changes in flowering plants nor detect bat activity at known night roost and foraging areas. Historically, observations during rare occurrences, such as a total solar eclipse, were anecdotal or limited in scope, and thus, how they changed the light, sound, and meteorological conditions on the landscape were difficult to validate and measure. In comparison, anthropogenic disturbances, including impacts from light pollution and climate change, often take place slowly over long periods, and therefore, can be complex and challenging to assess. Documentation of this stochastic occurrence, with an immediate change in environmental conditions, highlights the utility of passive multimedia technologies to increase our capacity to monitor ecosystem dynamics and chronicle the variations of abiotic properties of a landscape and concomitant responses of organisms with varying sensory abilities. [ABSTRACT FROM AUTHOR]

This paper discusses the economic impacts of climate change, including those on ecosystems, and whether a new backstop technology should be used under conditions of strict temperature targets. Using the dynamic integrated climate-economy (DICE) model, we developed a new model to calculate the optimal path by considering new backstop technologies, such as CO 2 capture and storage (CCS). We identify the effects of parameter changes based on the resulting differences in CO 2 leakage and sites, and we analyse the feasibility of CCS. In addition, we focus on ocean acidification and consider the impact on economic activity. As a result, when CCS is assumed to carry a risk of CO 2 leakage and acidification is considered to result in a decrease in utility, we find that CCS can only delay the effects of climate change, but its use is necessary to achieve strict targets, such as a 1.5 °C limit. This observation suggests that if the target temperature is too tight, we might end up employing a technology that sacrifices the ecosystem too greatly. [ABSTRACT FROM AUTHOR]

[Display omitted] • Our algorithm improved LSP retrieval in ecosystems with low seasonal amplitude. • The detectability of LSP increases when the seasonal amplitude increases. • Evaluation results showed the reliability of the algorithm in various ecosystems. • These LSP retrievals could help to quantify ecological response to climate change. Land surface phenology (LSP), the study of the seasonal vegetation dynamics from remote sensing imagery, provides crucial information for plant monitoring and reflects the responses of ecosystems to climate change. The Moderate Resolution Imaging Spectroradiometer (MODIS) phenology product (MCD12Q2) provides global LSP information, but it has large spatial gaps in many regions, especially in ecosystems where rainfall influences phenology more than temperature. This study aimed to improve spatial coverage of LSP retrieval in these ecosystems. To do so, we used a regionally modified threshold algorithm for LSP retrievals, which were tested over continental Australia as it includes diverse landscapes of arid, mesic, and forest environments. We generated LSP metrics annually from 2003 to 2018 using satellite Enhanced Vegetation Index (EVI) time series at 500 m resolution, including the start, peak, end, and length of growing seasons, the minimum EVI value prior to and after the peak date, the seasonal maximum EVI value, the integral EVI value during the growing season (an approximation of productivity), and seasonal amplitude (maximum EVI value minus minimum EVI). Our regionally optimised algorithm improved the spatial coverage of LSP information in Australia from only 26 % of the continent to 70 % averaged across 16 years. Our results showed that the growing season amplitude was low (EVI < 0.1) over arid/semi-arid shrublands and savannas, tropical and subtropical savannas, and temperate evergreen forests, whose LSP metrics were captured by our regional algorithm and not by the global product. Some ecosystems, such as arid/semi-arid shrublands and savannas, showed more irregular phenology with low seasonal dynamics, and the growing seasons could skip a year or occur more than once in a year depending on climate conditions. Our algorithm was more sensitive to ecosystems with low seasonal amplitudes. We found that the detectability of LSP increases as the growing season amplitude increases, regardless of vegetation cover. Evaluation of the LSP metrics using eddy covariance flux tower measurements of gross primary productivity (GPP) demonstrated the reliability and accuracy of the algorithm. These improved LSP retrievals provide a greater understanding of the vegetation phenology across diverse ecosystems, especially savanna, shrubland, and evergreen forest ecosystems that cover more than 30 % of the land globally. The LSP provides essential information for ecological and agricultural studies such as quantifying bushfire fuel accumulation and forest carbon cycling, whilst enhancing our capacity for quantifying ecological responses to climate change. [ABSTRACT FROM AUTHOR]

Soil bacterial community structures and associated ecosystem functions are known to vary both in space and time but spatial and temporal patterns are rarely studied simultaneously. Dynamic floodplains offer an ideal setting to study these spatio-temporal patterns and to determine the relative importance of habitat diversity and seasons in shaping soil bacterial communities. We studied the differences between habitats and seasonal patterns of soil bacterial communities (T-RFLPs) and soil environmental conditions (temperature, moisture and time elapsed since last inundation) and ecosystem functioning proxies (basal respiration, enzymatic activity, microbial C and N) over one year in seven habitats of a restored floodplain. Soil bacterial community structures in the two habitats closest to the river were most divergent from the others. However, although bacterial community structures differed between habitats at all sampling times, their seasonal variability was substantially higher than the habitat differences. Most of the ecosystem functioning proxies were lowest in the most dynamic habitat (gravel bar). Furthermore, while both bacterial community structure and ecosystem functions varied in relation to environmental conditions, the two were not directly correlated, and the link between communities and functions was seasonally inconsistent. The ratio of seasonal vs. habitat variability of soil bacterial communities decreased from the most dynamic to the most stable (forest) habitat. Thus in dynamic ecosystems such as floodplains also external factors (flood disturbance, seasonally changing climatic conditions) might influence ecosystem functions and bacterial communities independently – possibly because of species functional redundancy – and are keys in maintaining floodplain taxonomical and functional diversity. [ABSTRACT FROM AUTHOR]

Lake Victoria has experienced human induced pressures such as overfishing, introduction of alien species, increased eutrophication and climate change impacts. However, there is limited understanding of the system dynamics, major processes, drivers and responses to the changes. To address this challenge, we developed the first end-to-end whole ecosystem model (Atlantis) for the lake. The model is spatially resolved into 12 unique dynamic areas based on depth, species composition, physical-chemical characteristics and fisheries management zones. A total of 38 functional groups constitute the biological model. Four fishing fleets with different targeting options are simulated. Reliability of the model is confirmed by the good fit of simulations output to observational data sets. Herein, we describe the evolution of the biophysical system, illustrating how it responded to the aforementioned induced perturbations since 1958. The constructed virtual Lake Victoria ecosystem model provides a platform for exploring the impact of management interventions before actual implementation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Water use efficiency (WUE) in China's drylands is on an upward trend for 2003–2018. • WUE increased rapidly in semiarid regions due to vegetation restoration projects. • WUE can decrease if vapour pressure deficit and plantation saturation increases. Dryland ecosystems are crucial components within the Earth and atmospheric systems, and a number of projects have been implemented to restore vegetation in drylands in the recent years. However, these regions are experiencing extreme climatic changes, and the impact of these projects are unclear. To gain a better understanding of the effectiveness of these projects, we employed water use efficiency (WUE), the ratio of gross primary production (GPP) to terrestrial evapotranspiration (ET), to predict future dryland ecosystem dynamics, and detected the underlying causes of WUE changes. We analysed the WUE trends and the decomposed components of WUE, namely the GPP to plant transportation ratio (GPP/T) and the plant transportation to terrestrial evapotranspiration (T/ET) ratio, between 2003 and 2018 in China's drylands. The results indicated that 70.3 % of the study area had an upward WUE trend, and T/ET was the dominant factor of the WUE trend in 74.9 % of the areas investigated. Furthermore, the increase in T/ET was associated with growth in leaf area index (LAI). The rising WUE rate in the vegetation restoration project areas was significantly higher than that in other areas along with the drought gradient (P < 0.05), which indicated WUE increasing was strongly influenced by the increase in LAI resulting from vegetation restoration. Thus, our research affirms that vegetation restoration greatly influences WUE increase. However, over time, WUE in these restored drylands is likely to decrease due to increased VPD and plantation saturation, so future strategies for vegetation restoration in drylands are therefore required. [ABSTRACT FROM AUTHOR]

• Establishes consistent, generalizable standards for calibrating and validating LANDIS-II. • Initialization methods based on publicly available, full coverage datasets. • LANDIS-II can be calibrated to reliably simulate wildfire and biomass dynamics. • This study lowers the barrier to adapting forest landscape models to new landscapes. • Aids independent assessment of the credibility of existing forest landscape models. Process-based Forest Landscape Models (FLMs) rely on first principles to simulate ecological patterns and processes, making them uniquely powerful for forecasting ecological dynamics under unprecedented climatic and disturbance regimes. Persistent challenges with any ecological forecasting model are calibration ("tuning" the model) and validation ("proofing" the model). As no actual future data exist from which to conduct a formal model validation, model credibility is established through numerous tests against empirical datasets and comparisons with other types of models. The purpose of this study was to establish more consistent and generalizable standards for calibrating and validating LANDIS-II, a widely used, open-source FLM. We reviewed methods gleaned from a wide variety of previous FLM studies and advance some new techniques for evaluating the credibility of the model outputs. We used publicly available data with full coverage for the United States (US) so that our methods will be generalizable to other landscapes in the US, and we developed an ecologically meaningful set of validation metrics for evaluating the credibility of new applications. We found that LANDIS-II could be calibrated to reliably simulate empirical vegetation-disturbance-climate dynamics in diverse, mountainous terrain and fire-prone landscapes of the eastern Cascade Mountains. We performed an inter-model validation between LANDIS-II and the Forest Vegetation Simulator (FVS), demonstrating consistent projections of biomass dynamics for all tree-dominated ecoregions in the study domain. Similarly, simulated fires reliably approximated the empirical fire event size and severity patch size distributions based on observed fire activity from 1984 to 2019. By establishing rigorous, transparent, and repeatable standards for calibrating and validating FLM dynamics, we sought to remove some of the barriers to adapting LANDIS-II to new landscapes and climates, facilitate further validation of existing models, and aid independent assessment of the credibility of forest landscape models. [ABSTRACT FROM AUTHOR]

• Using DNDC model to predict the carbon dynamics in temperate meadow steppe. • The model calibrated by precision multiple field data. • Model parameters has high accuracy on NEE. • Future prediction is conducted by DNDC under different climate scenarios. Temperate meadow steppe is a representative ecosystem in northeast China. A process-oriented biogeochemistry model, denitrification–decomposition (DNDC) biogeochemistry model was employed and adapted to interpret and integrate field observations to determine whether temperate meadow steppe ecosystem was a carbon dioxide (CO 2) sink during the growing seasons from 2010 to 2011. Then, we applied the model to predict the long-term impacts of climate change on the carbon dynamics in the ecosystem. Daily weather data for 2010–2011 in conjunction with the soil properties data and management practices data for this site were utilized as inputs to simulate the grass growth and soil carbon dynamics. The modeled carbon fluxes were compared with eddy tower data. The observed and modeled CO 2 fluxes data were consistent, with both showing that the temperate meadow steppe is a stable carbon sink. Prediction tests were conducted with a baseline and eight alternative climate scenarios for the period 2017–2050. Simulations for the years 2017–2050 found that (1) the temperate meadow steppe will be a carbon sink under the baseline climate conditions; (2) the decelerated warming and drier climate scenario produced the lowest grass production and lowest carbon sequestration; and (3) the accelerated warming and wetter climate scenario produced the highest biomass and highest carbon sequestration. By using DNDC model we can understand carbon dynamics in temperate meadow steppe. The ecosystem production is limited by precipitation, a wetter future climate would substantially elevate the carbon sequestration capacity of the ecosystem. However, the carbon sequestration potential could significantly decrease if the climate is more arid from 2017 to 2050. [ABSTRACT FROM AUTHOR]

Ecological rehabilitation is subject to a variety of risks affecting the likely return on investment. We propose an options approach to allocating scarce conservation funds that explicitly allows for the irreversibility of investment and risks to investment payoffs. The approach captures ecosystem dynamics from extinction debt, as well as ecological and climatic risks at the project scale. Climatic risks are introduced through three channels: the effects of climate change on species loss, future rehabilitation benefits and frequency of catastrophic events. Our results suggest that allocating voluntary rehabilitation contracts on the basis of real options criteria increases cost-efficiency and delivers greater value for money for the Government when compared with the conventional cost-effectiveness criterion as it is illustrated for the case of Box Gum Grassy Woodland rehabilitation in Australia. [ABSTRACT FROM AUTHOR]

• Recent forest changes in relation to climate change were investigated for the first time in Romania. • Countrywide NDVI and climate data were processed within forest boundaries between 1987 and 2018. • General greening (increasing NDVI in 65% of all ecological changes) of forests were detected nationally. • Browning (35% decreasing NDVI) trends were found regionally, mainly in the lowland areas of Romania. • National/regional greening/browning trends are mainly explained by climate warming/evapotranspiration increases. Forests have become increasingly stressed by climate change, including in Romania over recent decades, but their response to climate dynamics has not yet been analysed in this country. This study aims to investigate, for the first time, recent ecological changes in forests across Romania, in relation to climate dynamics that affected the country from 1987 to 2018. To this end, countrywide remote sensing (Landsat) data were processed for forest boundaries over the 32 years, in order to compute annual (summer season data) Normalized Difference Vegetation Index (NDVI) datasets, which were subsequently investigated as trends using the Mann-Kendall test and Sen's slope estimator. Simultaneously, various climatic data (temperature, precipitation and reference evapotranspiration) were processed through interpolation techniques and via the same two statistical tools, and were subsequently used for exploring the impact of climate change on Romanian forestlands after 1987. The results highlighted general greening (increasing NDVI) trends of forests nationally (65% of all NDVI changes, which total over 30.000 km2 across Romania), which were dominated by widespread positive NDVI trends detected in the Carpathians region of Romania. This general ecological dynamic suggests a possible enhancement in vegetation productivity in the country's high-altitude areas. Contrasting browning (decreasing NDVI) trends were found for 35% of Romanian forestlands marked by NDVI changes, especially apparent in the Extra-Carpathians (lowland) region, which indicates that in these cases forests were degraded or devitalized. However, the statistical significance of both greening and browning trends is limited across the country. The analysis of climatic trends and of correlations between annual NDVI and climate data indicated that recent warming throughout Carpathians may be an important driving force of forest greening in temperature-limited mountain regions. This finding is supported by an at least moderate intensity of air temperature – NDVI relationships (r correlation coefficient values of ∼50%, the highest of all eco-climatic relationships analysed), generally detected throughout mountain environments. At the same time, it seems that evapotranspiration increase accounted at least in part for forest browning in lowland areas, while the impact of precipitation in forest ecological dynamics remains unclear. All these findings can be useful for a better forest management under the future climate change conditions in Romania. [ABSTRACT FROM AUTHOR]

[Display omitted] • The PUE of Eurasian grasslands was in uptrend from 1982 to 2015. • Greatest decrease and increase trend of PUE was found in alpine and forest steppe. • The temporal variation of PUE was mainly controlled by precipitation. • Climate shaped PUE pattern by cascading effect networks of T, P—VPD—LAI—ANPP—PUE. Precipitation-use efficiency (PUE) is an important ecosystem indicator of the efficiency of carbon–water conversion. The trend and interannual variation of precipitation-use efficiency (PUE) response to climatic factors provide a theoretical foundation for understanding how Eurasian grasslands adapt to climate change. However, the long-term trends and regulating factors of PUE in Eurasian grasslands at the continental scale are still unclear. Here, we integrated long-term Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI), field surveys of aboveground net primary production (ANPP) and meteorological datasets during 1982–2015 to reveal the temporal variations and controls of PUE in Eurasian grasslands. We found that there was an overall uptrend of PUE (3 × 10−3 g C m−2 mm−1/10 yr) in Eurasian grasslands. The greatest increasing trends of PUE was found in forest steppe at the rate of 13 × 10−3 g C m−2 mm−1/10 yr, while greatest decreasing trend presented in alpine steppe at the rate of −2.6 × 10−3 g C m−2 mm−1/10 yr. The PUE showed linearly decreasing patterns with precipitation at the biome and continental scales, while it was uncorrelated with temperature at the continental scale and showed diverse patterns of linear increase, concave-down and no correlation with temperature for different biomes. The temporal variation of PUE was mainly controlled by precipitation in Eurasian grasslands. This result further revealed that climatic factors shaped the temporal pattern of PUE by the cascading effects networks of climatic factors (precipitation and temperature) − vapor pressure deficit (VPD) – leaf area index (LAI) – ANPP – PUE (CVLP-CENet). This study identified the long-term trends, interannual variations and controls of PUE in Eurasian grasslands over the past three decades, and provided crucial insights into understanding grassland ecosystems dynamics and response to climate change. [ABSTRACT FROM AUTHOR]

The Baltic Proper is a semi-enclosed, highly productive basin of the Baltic Sea with a low biodiversity, where only a few key species drive the system's dynamics. Recently, an ecosystem regime shift was described having pronounced changes at all trophic levels, driven by changes in fishery and climate and leading to a food–web reorganisation. An Ecopath with Ecosim Baltic Proper food–web model (BaltProWeb) was developed to simulate and better understand trophic interactions and their flows. The model contains 22 functional groups that represent the main food–web components. BaltProWeb was calibrated to long-term monitoring data (1974–2006), covering multiple trophic levels and is forced by fisheries and environmental drivers. Our model enables the quantification of the flows through the food–web from primary producers to top predators including fisheries over time. The model is able to explain 51% of the variation in biomass of multiple trophic levels and to simulate the regime shift from a cod dominated to a sprat dominated system. Results show a change from benthic to more pelagic trophic flows. Before the reorganisation macrozoobenthos was identified as an important functional group transferring energy directly from lower trophic levels to top predators. After the regime shift, the pelagic trophic flows dominated. Uncertainties and limitations of the modelling approach and results in relation to ecosystem-based management are discussed. [Copyright &y& Elsevier]

• Physical and biological variables identified as strong indicators of ecosystem change. • Contrasting regions provided useful insights on ecosystem responses to disturbances. • Interactions between indicators can dramatically change over time. • Ecosystem change linked to physical pressures and primary production changes. • Hidden variable modelled ecosystem changes. Understanding ecosystem dynamics within shallow shelf seas is of great importance to support marine spatial management of natural populations and activities such as fishing and offshore renewable energy production to combat climate change. Given the possibility of future changes, a baseline is needed to predict ecosystems responses to such changes. This study uses Bayesian techniques to find the data-driven estimates of interactions among a set of physical and biological variables and a human pressure within the last 30 years in a well-studied shallow sea (North Sea, UK) with four contrasting regions and their associated ecosystems. A hidden variable is incorporated to model functional ecosystem change, where the underlying interactions dramatically change, following natural or anthropogenic disturbance. Data-driven estimates of interactions were identified, highlighting physical (e.g. bottom temperature, potential energy anomaly) and biological variables (e.g. sandeel larvae, net primary production) to be strong indicators of ecosystem change. There was consistency in the physical and biological variables, identified as good indicators in three of the regions, however the shallower region (with depths < 50 m, that is targeted for static offshore wind developments) was the most dissimilar. The use of contrasting regions provided useful insights on responses linked to ecosystem disturbances and identified the top predators as better indicators for each region, with the harbour porpoise being a particularly valuable indicator of ecosystem change across most regions. Another important finding was the dramatic changes in the strength of many interactions over time. This suggests that physical and biological indicators should only be used with additional temporal information, as changes in strength led to the identification of two potentially significant periods of ecosystem change (after 2005 and after 2010), linked to physical pressures (e.g. cold-water anomalies, seen in bottom temperatures; salinity changes, seen in the potential energy anomaly) and primary production changes. The hidden variable also modelled a change in the early 2000s for all the regions and identified maximum chlorophyll-a and sea surface temperature as some of the better indicators of these ecosystem changes. [ABSTRACT FROM AUTHOR]

• China's water use efficiency showed an increasing trend from 2001 to 2017. • The water use efficiency of forest land is higher than that of low vegetation. • Human activities have a greater contribution to the increase in water use efficiency. • China has more areas with positive correlation between water use efficiency and meteorology. In the context of increasing global carbon emissions, and the relative shortage of water resources, research on the relationships between climate change, human activities and the carbon–water coupling response of China's ecosystems is crucial. Water use efficiency (WUE) is an important indicator reflecting the coupling of ecosystem carbon and water cycles. Based on trend analysis, correlation analysis and multiple regression residual analysis, this paper analyzes the spatiotemporal distributions, change trends, correlations with meteorological factors, changes in different vegetation coverage types, and relative contributions of the main driving factors of China's vegetation WUE from 2001 to 2017. The results show the following: (1) For the past 17 years, the multiyear average value of vegetation WUE in China is 1.08 g C m - 2 mm - 1 , the average annual growth rate is 0.003 g C m - 2 mm - 1 a - 1 . The area with increasing trend of WUE accounts for 59.09% of the total area. (2) The seasonal WUE is highest in autumn, followed by summer, spring and winter. (3) The areas in which vegetation WUE is positively correlated with temperature and precipitation account for approximately 50.21% and 66.16% of the total area, respectively. (4) In terms of the relative annual average value of the WUE, the different vegetation cover types, in descending order, are mixed forests > needleleaf forests > broadleaf forests > shrublands > grasslands > croplands > wetlands > barren lands. (5) Human activities and climate change contributed 66.75% and 33.25%, respectively, to the increase in vegetation WUE in China in the past 17 years. The research results have important scientific significance for clarifying the impacts of climate change and human activities on the carbon–water cycle of the terrestrial ecosystems of China and assessing regional differences in the potential of terrestrial ecosystems to increase carbon sinks. [ABSTRACT FROM AUTHOR]

• Belowground bud bank might affect the response of plant community to global changes. • N addition suppressed belowground bud bank but facilitated aboveground productivity. • ANPP is driven by both individual shoot growth and belowground bud bank demography. • The bud banks of grasses and forbs responded to global changes in an opposite way. In temperate perennial grasslands, the recruitment/regeneration of aboveground vegetation predominantly relies on belowground bud bank. Thus, understanding how belowground bud bank density and composition respond to global changes is essential to explain and predict plant community dynamics and ecosystem functions under global change context. The belowground bud bank and aboveground vegetation under the simulated precipitation changes and nitrogen deposition (by watering and N addition) were investigated in the temperate semiarid steppe of Inner Mongolia, China. N addition decreased total bud density but facilitated aboveground productivity, however, watering itself and its combination with N addition had little influence on total bud density. Different bud bank types showed specific responses to watering and N addition, especially, buds of grasses and forbs responded in an opposite way. Overall, shoot abundance were positively related to bud density, and showed similar responses with those of bud banks, especially for forbs, which are more sensitive to global changes. Our results imply that the changes in belowground bud bank might affect subsequent responses of plant communities to precipitation change and/or nitrogen deposition under future global change scenarios. [ABSTRACT FROM AUTHOR]

The insufficient information on water conservation dynamics and potential in ecological engineering areas often restrict the selection and implementation of ecological restoration measures in arid and semiarid climates. Based on the regional water balance equation and GIS spatial analysis tools, this article assessed the spatial-temporal changes in water conservation in Xilin Gol League, a representative region of the Beijing–Tianjin Sandstorm Source Control Project Area. The results indicated that the yearly amount of water conservation in Xilin Gol League reached 1.27 billion cubic meters, and annual precipitation of approximately 6.36 mm was retained per hectare. The water conservation capacity in Xilin Gol League showed a notably increasing tendency during the period of 2000–2015 and increased from west to east. The northeast of East Ujimqin Banner had the highest capacity, contributing 16.19% of the total water conservation amount. Compared to 2000, approximately 65.86% of Xilin Gol League presented water conservation capacity increases in 2015, 15.25% of which were significant. The water conservation in Xilin Gol League correlated with the changes in precipitation, temperature, and vegetation coverage, and unfavorable changes in these factors led to a significant decline in regional water conservation capacity. Therefore, multiple ecological restoration strategies are proposed for the improvement of water conservation capacity in the low-efficiency areas. • Dynamic changes in water conservation in ecological engineering area were quantified. • The water conservation capacity notably increased from west to east during 2000–2015. • The water conserved increased in 66% of the study area and decreased in western area. • Rainfall, temperature, and vegetation determine the changes in water conservation. [ABSTRACT FROM AUTHOR]

Although climate change occurs alongside other anthropogenic ecosystem impacts, little is known about how sea-surface temperature variability influences the ecotoxicology of persistent organic pollutants (POPs). We analyzed POP contaminant levels, and stable isotopes δ15N and δ13C as measures of trophic position, in eggs collected from the Gulf of Alaska and Bering Sea between 1999 and 2010 from two similar avian species with different trophic positions: common murres (Uria aalge) and thick-billed murres (Uria lomvia). The ebb and flow of the Pacific Decadal Oscillation (PDO), a long-lived El Niño-like pattern of climate variability in the Pacific Ocean, predicted both trophic position and polychlorinated biphenyl (PCB) levels in thick-billed murres, but not in common murres. There was a similar pattern of association of the PDO with organochlorine pesticide levels in thick-billed murres, but not in common murres. The magnitude of association in thick-billed murres of PDO with the level of a specific PCB congener was a function of the number of chlorine groups on the PCB congener. Although this statistical analysis does not account for all factors contributing to climate variation, this contrast between the species suggests that facultative changes in foraging behavior, reflected in trophic position, can determine how POPs flow through and thereby alter ecosystems under climate change. • Climate variability indicated by sea surface temperature is associated with altered trophic dynamics in marine ecosystems. • We found differential effects on feeding behavior and accumulation of pollutants in two sympatric seabirds. • Differences in trophic vulnerability may affect the risk of exposure to POPs in seabirds in light of climate variability. [ABSTRACT FROM AUTHOR]

• Environmental/climate changes cause hydrological and vegetation shifts in peatlands. • The methods used to study peatland hydrology agree on large-scale changes. • Minor or rapid changes, and even their timing, can vary between approaches. • Warm/dry conditions cause low water tables, more trees, but reduced moss growth. • Warm/dry conditions can thus reduce carbon storage ability of peatlands. In this study, six approaches were used to characterize hydrological changes in the Čepkeliai wetland complex (southeast Lithuania), namely (i) local water-table measurements (WTM), (ii) testate amoebae analysis, (iii) tree-ring width (TRW) series, (iv) peat stratigraphic data, (v) (hydro-) meteorological data (precipitation and river runoff), and (vi) a diachronic analysis of aerial photographs as well as historical maps. This multi-proxy framework provides complementary information on the hydrological evolution of the peatland and offers a unique opportunity to discuss the pros and cons of each approach. Local water-table measurements, for example, generated monthly resolved and precise (±0.01 m) hydrological information, but were limited to a 16-year period. On the other hand, the TRW data generated annually-resolved information linked to hydrological shifts over the period 1848–2018, but did not allow reconstruction of the amplitude of hydrological variations. Amongst the proxy records, the testate amoebae distribution is the only approach that gives a direct measurement of changes in water-table depths. At the same time, the approach is limited by chronological inaccuracies and weaker resolutions, similar to peat stratigraphic records. The meteorological data are theoretically representing the most highly resolved records. However, due to hydrological lags and feedbacks in peatlands, it was difficult to link regional changes observed in meteorological records to local changes in the peatland. The aerial photographs and historical maps offered an opportunity to document large-scale vegetation changes, which is useful for upscaling local results, but they may not capture rapid changes. Despite all these limitations, at Čepkeliai, most of the proxy records are in agreement with each other and suggest relatively moist conditions with water levels close to the peat surface during the late 1800s and early 1900s, followed by more detailed information towards the present showing shifts towards drier peat surface conditions during the 1930s and 1940s. The 1960s were dry, followed by a short, moist episode during the 1970s, and returning to drier conditions during the 1980s. A gradual change towards moister conditions was recorded over the 1990s and 2000s. The last decade in our records started with relatively wet conditions to end with lower water levels over the most recent years. [ABSTRACT FROM AUTHOR]