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Background: Understanding temporal trends and varying responses of water use efficiency (WUE) to environmental changes of diverse ecosystems is key to predicting vegetation growth. WUE dynamics of major ecosystem types (e.g., forest, grassland and cropland) have been studied using various WUE definitions/metrics, but a comparative study on WUE dynamics and their driving forces among different ecosystem types using multiple WUE metrics is lacking. We used eddy covariance measurements for 42 FLUXNET2015 sites (396 site years) from 1997 to 2014, as well as three commonly used WUE metrics (i.e., ecosystem, inherent, and underlying WUE) to investigate the commonalities and differences in WUE trends and driving factors among deciduous broadleaf forests (DBFs), evergreen needleleaf forests (ENFs), grasslands, and croplands. Results: Our results showed that the temporal trends of WUE were not statistically significant at 73.8% of the forest, grassland and cropland sites, and none of the three WUE metrics exhibited better performance than the others in quantifying WUE. Meanwhile, the trends observed for the three WUE metrics were not significantly different among forest, grassland and cropland ecosystems. In addition, WUE was mainly driven by atmospheric carbon dioxide concentration at sites with significant WUE trends, and by vapor pressure deficit (VPD) at sites without significant trends (except cropland). Conclusions: Our findings revealed the commonalities and differences in the application of three WUE metrics in disparate ecosystems, and further highlighted the important effect of VPD on WUE change. [ABSTRACT FROM AUTHOR]

Human intervention and climate change jointly influence the functions and dynamics of marine ecosystems. Studying the impacts of human and climate on ecosystem dynamics is challenging. Unlike experimental studies, research on natural systems is not amendable at the scale of time, space, and biology. With confounding factors well balanced for two adjacent subtropical estuaries except urbanized disturbances, we conducted ecosystem modelling using indirect reasoning by exclusion to quantify the relative impacts of human disruption on estuarine ecosystems under climate variability. One major finding of this study is that the human intervention tends to magnify species fluctuations, complicate the species interaction network, and enhance species interaction strength combined with disclosed downscaling climate effects (indexed as North Atlantic Oscillation and Atlantic Multi-decadal Oscillation) on estuarine hydrology and biological communities. In addition, functional groups appeared to respond more diversely to external forcing in company with human interventions. While human perturbation was shown to destabilize the estuarine ecosystems, making them vulnerable to environmental variability under climate change, buffering effects of species diversity and trophic interaction tend to underpin the ecosystem functions. The findings of this study contribute to the holistic assessment and strategic management of estuarine ecosystems subjected to human and natural disturbances in the face of climate change. [ABSTRACT FROM AUTHOR]

Drought events are projected to be more extreme and frequent in the future and have profound influences on the structure and functions of terrestrial ecosystems. Thus, better understanding the mechanisms of recovery is critical for predicting the future dynamics of terrestrial ecosystems. We performed a 7‐year field precipitation experiment to examine recovery of a grassland ecosystem from different magnitudes of sustained drought, from slight to extreme. The ecosystem was exposed to precipitation treatments in the first 3 years (2010–2012) and recovered during the last 4 years (2013–2016) without precipitation treatments. Overall, large reductions of aboveground net primary productivity (ANPP, −43.3%) and perennial forb biomass (−83.1%) were observed in the third year (2012) of extreme drought only. Nevertheless, ANPP fully recovered within 1 year after the drought treatments were terminated, and the rapid recovery was mainly due to increased soil total nitrogen and root biomass allocation after drought. Surprisingly, large increases of ANPP under the extreme drought treatment occurred during the recovery periods from 2013 to 2015 (+74.1, +88.5, and +119.8 g m−2 year−1) compared to the control. The overcompensation offset the extreme drought‐induced reduction of ANPP in the treatment years and was primarily ascribed to the enhanced biomass of perennial grasses (PG). Higher resistance to drought and fast resource acquisition strategy might drive the rapid recovery and expansion of PG. Our findings revealed the rapid recovery of grasslands and the critical role of community overcompensation in maintaining grassland ecosystem function and stability under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Climate change has led to intensification and poleward migration of the Southeastern Pacific Anticyclone, forcing diverging regions of increasing, equatorward and decreasing, poleward coastal phytoplankton productivity along the Humboldt Upwelling Ecosystem, and a transition zone around 31° S. Using a 20-year dataset of barnacle larval recruitment and adult abundances, we show that striking increases in larval arrival have occurred since 1999 in the region of higher productivity, while slower but significantly negative trends dominate poleward of 30° S, where years of recruitment failure are now common. Rapid increases in benthic adults result from fast recruitment–stock feedbacks following increased recruitment. Slower population declines in the decreased productivity region may result from aging but still reproducing adults that provide temporary insurance against population collapses. Thus, in this region of the ocean where surface waters have been cooling down, climate change is transforming coastal pelagic and benthic ecosystems through altering primary productivity, which seems to propagate up the food web at rates modulated by stock–recruitment feedbacks and storage effects. Slower effects of downward productivity warn us that poleward stocks may be closer to collapse than current abundances may suggest. [ABSTRACT FROM AUTHOR]

Unprecedented and dramatic transformations are occurring in the Arctic in response to climate change, but academic, public, and political discourse has disproportionately focussed on the most visible and direct aspects of change, including sea ice melt, permafrost thaw, the fate of charismatic megafauna, and the expansion of fisheries. Such narratives disregard the importance of less visible and indirect processes and, in particular, miss the substantive contribution of the shelf seafloor in regulating nutrients and sequestering carbon. Here, we summarise the biogeochemical functioning of the Arctic shelf seafloor before considering how climate change and regional adjustments to human activities may alter its biogeochemical and ecological dynamics, including ecosystem function, carbon burial, or nutrient recycling. We highlight the importance of the Arctic benthic system in mitigating climatic and anthropogenic change and, with a focus on the Barents Sea, offer some observations and our perspectives on future management and policy. [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]

Populations of many long-lived plants exhibit spatially synchronized seed production that varies extensively over time, so that seed production in some years is much higher than on average, while in others, it is much lower or absent. This phenomenon termed masting or mast seeding has important consequences for plant reproductive success, ecosystem dynamics and plant–human interactions. Inspired by recent advances in the field, this special issue presents a series of articles that advance the current understanding of the ecology and evolution of masting. To provide a broad overview, we reflect on the state-of-the-art of masting research in terms of underlying proximate mechanisms, ontogeny, adaptations, phylogeny and applications to conservation. While the mechanistic drivers and fitness consequences of masting have received most attention, the evolutionary history, ontogenetic trajectory and applications to plant–human interactions are poorly understood. With increased availability of long-term datasets across broader geographical and taxonomic scales, as well as advances in molecular approaches, we expect that many mysteries of masting will be solved soon. The increased understanding of this global phenomenon will provide the foundation for predictive modelling of seed crops, which will improve our ability to manage forests and agricultural fruit and nut crops in the Anthropocene. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'. [ABSTRACT FROM AUTHOR]

Climate change has multiple direct and indirect potentially synergistic effects on Baltic Sea species, organism communities, and on ecosystem functioning, through physical and biogeochemical environmental characteristics of the sea. Associated indirect and secondary effects on species interactions, trophic dynamics and ecosystem function are expected to be significant. Evidence on effects of climate are compiled from and reviewed for field studies, experimental work, as well as modelling studies primarily from published literature after 2010. The responses vary within and between species groups, even between sibling species. Such subtle differences, as well as secondary feedbacks and altered trophic pathways, make projections difficult. Some common patterns arise from the wealth of recent studies, however. It is likely that the combined effects of increased external nutrient loads, stratification and internal loading will improve the conditions for cyanobacterial blooms in large parts of the Baltic. In the northernmost areas the increasing allochtonous DOM may further complicate the picture by increasing heterotrophy and by decreasing food web efficiency. This effect may, however, be counteracted by the intensification of the bacteria-flagellate-microzooplankton-mesozooplankton link, which may change the system from a bottom-up controlled one to a top-down controlled one. In deep benthic communities, continued eutrophication may promote higher sedimentation of organic matter and increase zoobenthic biomasses, but eventually increasing stratification and hypoxia/anoxia will disrupt benthic-pelagic coupling, leading to reduced benthic biomass. In the photic benthic systems warmer winters with less ice and nutrient increase enhances eutrophication. The projected salinity decline suppresses marine species, and temperature increase overgrowth of perennial macroalgae by annual filamentous alga throughout the growing-season, and major changes in the marine entire ecosystem are expected. The changes in environmental conditions probably also lead to increased establishment of non-indigenous species, potentially affecting food web dynamics in large areas of the Baltic Sea. However, several modelling studies have concluded that nutrient reductions according to the Baltic Sea Action Plan of Helsinki Commission may be a stronger driver for ecosystem functions in the Baltic Sea than climate change. Such studies highlight the importance of studying the Baltic Sea as an interlinked socio-ecological system. Knowledge gaps include uncertainties in projecting the future salinity level as well as stratification under different climate forcings. This weakens our ability to project how overall biodiversity, pelagic productivity, fish populations, and macroalgal communities may change in the future. Experimental work must be better integrated into studies of food web dynamics, to get a more comprehensive view of the responses of the pelagic and benthic systems to climate change, from bacteria to fish. Few studies have holistically investigated the shallow water ecosystems holistically. There are complex climate-induced interactions and multiple feedbacks between algae, grazers and their predators, that are poorly known, as are the effects of non-native invasive species. Finally, both 2D species distribution models and 3D ecosystem models could benefit from better integration of approaches including physical, chemical and biological parameters. [ABSTRACT FROM AUTHOR]

Climate warming is facilitating the expansion of many cold‐sensitive woody species in woodland–grassland ecotones worldwide. Recent research has demonstrated that this range expansion can be further enhanced by positive vegetation–microclimate feedbacks whereby woody canopies induce local nocturnal warming, which reduces freeze‐induced damage and favors the establishment of woody plants. However, this local positive feedback can be counteracted by biotic drivers such as browsing and the associated consumption of shrub biomass. The joint effects of large‐scale climate warming and local‐scale microclimate feedbacks on woody vegetation dynamics in these ecotones remain poorly understood. Here, we used a combination of experimental and modeling approaches to investigate the effects of woody cover on microclimate and the consequent implications on ecological stability in North American coastal ecosystems. We found greater browsing pressure and significant warming (~2°C) beneath shrub canopies compared to adjacent grasslands, which reduces shrub seedlings' exposure to cold damage. Cold sensitivity is evidenced by the significant decline in xylem hydraulic conductivity in shrub seedlings when temperatures dropped below −2°C. Despite the negative browsing–vegetation feedback, a small increase in minimum temperature can induce critical transitions from grass to woody plant dominance. Our framework also predicts the threshold temperature of −7°C for mangrove–salt marsh ecotones on the Atlantic coast of Florida. Above this reference temperature a critical transition may occur from salt marsh to mangrove vegetation, in agreement with empirical studies. Thus, the interaction between ongoing global warming trends and microclimate feedbacks may significantly alter woody vegetation dynamics and ecological stability in coastal ecosystems where woody plant expansion is primarily constrained by extreme low temperature events. [ABSTRACT FROM AUTHOR]

The rapid anthropogenic climate change that is being experienced in the early twenty-first century is intimately entwined with the health and functioning of the biosphere. Climate change is impacting ecosystems through changes in mean conditions and in climate variability, coupled with other associated changes such as increased ocean acidification and atmospheric carbon dioxide concentrations. It also interacts with other pressures on ecosystems, including degradation, defaunation and fragmentation. There is a need to understand the ecological dynamics of these climate impacts, to identify hotspots of vulnerability and resilience and to identify management interventions that may assist biosphere resilience to climate change. At the same time, ecosystems can also assist in the mitigation of, and adaptation to, climate change. The mechanisms, potential and limits of such nature-based solutions to climate change need to be explored and quantified. This paper introduces a thematic issue dedicated to the interaction between climate change and the biosphere. It explores novel perspectives on how ecosystems respond to climate change, how ecosystem resilience can be enhanced and how ecosystems can assist in addressing the challenge of a changing climate. It draws on a Royal Society-National Academy of Sciences Forum held in Washington DC in November 2018, where these themes and issues were discussed. We conclude by identifying some priorities for academic research and practical implementation, in order to maximize the potential for maintaining a diverse, resilient and well-functioning biosphere under the challenging conditions of the twenty-first century. [ABSTRACT FROM AUTHOR]

The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes. Over the past decade, China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming. However, the changes in the trends of terrestrial net ecosystem production (NEP) in China under climate changes are not well documented. Here, we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982–2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country. Our results revealed a decadal-scale shift in NEP from a downtrend of –5.95 Tg C/yr2 (reduced sink) during 1982–2000 to an uptrend of 14.22 Tg C/yr2 (enhanced sink) during 2000–10. This shift was essentially induced by the strengthened summer monsoon, which stimulated carbon uptake, and the warming hiatus, which lessened the decrease in the NEP trend. Compared to the contribution of 56.3% by the climate effect, atmospheric CO2 concentration and nitrogen deposition had relatively small contributions (8.6 and 11.3%, respectively) to the shift. In conclusion, within the context of the global-warming hiatus, the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration. Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades, but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas. [ABSTRACT FROM AUTHOR]

The Gulf of Mexico is an ecologically and economically important marine ecosystem that is affected by a variety of natural and anthropogenic pressures. These complex and interacting pressures, together with the dynamic environment of the Gulf, present challenges for the effective management of its resources. The recent adoption of Bayesian networks to ecology allows for the discovery and quantification of complex interactions from data after making only a few assumptions about observations of the system. In this study, we apply Bayesian network models, with different levels of structural complexity and a varying number of hidden variables to account for uncertainty when modeling ecosystem dynamics. From these models, we predict focal ecosystem components within the Gulf of Mexico. The predictive ability of the models varied with their structure. The model that performed best was parameterized through data-driven learning techniques and accounted for multiple ecosystem components’ associations and their interactions with human and natural pressures over time. Then, we altered sea surface temperature in the best performing model to explore the response of different ecosystem components to increased temperature. The magnitude and even direction of predicted responses varied by ecosystem components due to heterogeneity in driving factors and their spatial overlap. Our findings suggest that due to varying components’ sensitivity to drivers, changes in temperature will potentially lead to trade-offs in terms of population productivity. We were able to discover meaningful interactions between ecosystem components and their environment and show how sensitive these relationships are to climate perturbations, which increases our understanding of the potential future response of the system to increasing temperature. Our findings demonstrate that accounting for additional sources of variation, by incorporating multiple interactions and pressures in the model layout, has the potential for gaining deeper insights into the structure and dynamics of ecosystems. [ABSTRACT FROM AUTHOR]

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types. [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]

This paper provides an analysis of adaptation to extreme climate changes using the Australian animal husbandry data. The paper finds that farmers have adapted to a hot and arid climate regime through animal husbandry. The number of sheep vastly increases into arid ecosystems while the number of beef cattle does not decline in high temperatures. In the future climate system in which Australia becomes hotter and more arid, we predict that farmers will increase by large percentages the numbers of beef cattle and/or sheep owned in order to adapt to a highly unfavorable climate condition, especially into the arid ecosystems. This paper shows how humanity has adapted to climate extremes taking into account changing ecosystems. [ABSTRACT FROM AUTHOR]

The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections. The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type. Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is years (95 per cent confidence interval). On average, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75° north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semi-arid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models. [ABSTRACT FROM AUTHOR]

Boreal ecosystems and their large carbon stocks are strongly shaped by extensive wildfires. Coupling climate projections with records of area burned during the last 3 decades across the North American boreal zone suggests that area burned will increase by 30-500% by the end of the 21st century, with a cascading effect on ecosystem dynamics and on the boreal carbon balance. Fire size and the frequency of large-fire years are both expected to increase. However, how fire size and time since previous fire will influence future burn rates is poorly understood, mostly because of incomplete records of past fire overlaps. Here, we reconstruct the length of overlapping fires along a 190-km-long transect during the last 200 y in one of the most fire-prone boreal regions of North America to document how fire size and time since previous fire will influence future fire recurrence. We provide direct field evidence that extreme burn rates can be sustained by a few occasional droughts triggering immense fires. However, we also show that the most fire-prone areas of the North American boreal forest are resistant to high burn rates because of overabundant young forest stands, thereby creating a fuel-mediated negative feedback on fire activity. These findings will help refine projections of fire effect on boreal ecosystems and their large carbon stocks. [ABSTRACT FROM AUTHOR]

From the planning days preceding the establishment of the US Global Ocean Ecosystem Dynamics (GLOBEC) program, modeling was recognized as one of the program's pillars. In particular, predictions of future ecosystem states in an evolving climate system required new interdisciplinary approaches that brought together physicists, biologists, modelers, and observational scientists. The GLOBEC program coincided with, took advantage of, and contributed to significant advances in ocean modeling capabilities. During the GLOBEC years, computer power increased substantially to the point where coupled physical-biological models, at resolutions where important interactions are resolved, became feasible. Ocean models were maturing so that complex coastal processes were explicitly represented, and advances in different ways of modeling the biosphere, from Lagrangian individuals to Eulerian community-based, multitrophic models, were emerging. The US GLOBEC program addressed the question: How can we use all these developments to help us understand how ecosystems will respond to climate change? his paper includes a review of state-of-the-science modeling at the onset of the GLOBEC program and highlights the evolution of physical and biological models used for the program' s target regions and species throughout the GLOBEC years, 1992-2012. [ABSTRACT FROM AUTHOR]

1: Given the predictions of increased drought probabilities under various climate change scenarios, there have been numerous experimental field studies simulating drought using transparent roofs in different ecosystems and regions. Such roofs may, however, have unknown side effects, called artifacts, on the measured variables potentially confounding the experimental results. A roofed control allows the quantification of potential artifacts, which is lacking in most experiments. 2: We conducted a drought experiment in experimental grasslands to study artifacts of transparent roofs and the resulting effects of artifacts on ecosystems relative to drought on three response variables (aboveground biomass, litter decomposition and plant metabolite profiles). We established three drought treatments, using (1) transparent roofs to exclude rainfall, (2) an unroofed control treatment receiving natural rainfall and (3) a roofed control, nested in the drought treatment but with rain water reapplied according to ambient conditions. 3: Roofs had a slight impact on air (+0.14°C during night) and soil temperatures (−0.45°C on warm days, +0.25°C on cold nights), while photosynthetically active radiation was decreased significantly (−16%). Aboveground plant community biomass was reduced in the drought treatment (−41%), but there was no significant difference between the roofed and unroofed control, i.e., there were no measurable roof artifact effects. 4: Compared to the unroofed control, litter decomposition was decreased significantly both in the drought treatment (−26%) and in the roofed control treatment (−18%), suggesting artifact effects of the transparent roofs. Moreover, aboveground metabolite profiles in the model plant species Medicago x varia were different from the unroofed control in both the drought and roofed control treatments, and roof artifact effects were of comparable magnitude as drought effects. 5: Our results stress the need for roofed control treatments when using transparent roofs for studying drought effects, because roofs can cause significant side effects. [ABSTRACT FROM AUTHOR]

Intense human activities and rapid climate changes both have obvious impacts on alpine ecosystems. However, the magnitudes and directions of the impacts by these two drivers remain uncertain due to a lack of a reasonable assessment method to distinguish between them. The impact of natural resilience is also generally included in the dynamics of a disturbed ecosystem and is liable to be mixed into the impact of human activity. It is urgent that we quantitatively discriminate human activity impacts on the ecosystem under climate change, especially for fast-developing alpine regions. Here, we propose an assessment method to determine human activity impacts under a dynamic climate, taking the potential net primary production (NPP) of an ecosystem as a benchmark. The potential NPP (NPPP) series under the changing climate was retrieved by an improved integrated biosphere simulator based on the initial disturbed ecosystem status of the assessment period. The actual NPP (NPPA) series monitored by remote sensing was considered as the results derived from the joint impacts of climate change, natural resilience and human activity. Then, the impact of human activity was quantified as the difference between the NPPP and NPPA. The contributions of human activity and natural forces to ecosystem NPP dynamics were then calculated separately and employed to explore the dominant driver(s). This assessment method was demonstrated in a typical alpine ecosystem in Northwest China. The results indicate that this method capably revealed the positive impacts of local afforestation and land-use optimization and the negative impacts caused by grazing during the assessment period of 2001–2017. This assessment method provides a quantitative reference for assessing the performances of ecological protections or human damage to alpine ecosystems at the regional scale. [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]

• 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]