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While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

Summary Optimal stomatal theory predicts that stomata operate to maximise photosynthesis (Anet) and minimise transpirational water loss to achieve optimal intrinsic water‐use efficiency (iWUE). We tested whether this theory can predict stomatal responses to elevated atmospheric CO2 (eCO2), and whether it can capture differences in responsiveness among woody plant functional types (PFTs). We conducted a meta‐analysis of tree studies of the effect of eCO2 on iWUE and its components Anet and stomatal conductance (gs). We compared three PFTs, using the unified stomatal optimisation (USO) model to account for confounding effects of leaf–air vapour pressure difference (D). We expected smaller gs, but greater Anet, responses to eCO2 in gymnosperms compared with angiosperm PFTs. We found that iWUE increased in proportion to increasing eCO2 in all PFTs, and that increases in Anet had stronger effects than reductions in gs. The USO model correctly captured stomatal behaviour with eCO2 across most datasets. The chief difference among PFTs was a lower stomatal slope parameter (g1) for the gymnosperm, compared with angiosperm, species. Land surface models can use the USO model to describe stomatal behaviour under changing atmospheric CO2 conditions.

Species distribution models (SDMs) provide realistic scenarios to explain the influence of bioclimatic variables on plant pathogen distribution. Diplodia sapinea is most harmful to plantations of both exotic and native pine species in Italy, causing economic consequences expecially to edible seed production. In this study, we developed maximum entropy models for D. sapinea in Italy to reach the following goals: (i) to carry out the pathogen's first geographical distribution analysis in Italy and determine which ecogeographical variables (EGVs) may influence its outbreaks; (ii) to detect the effect of climate change on the potential occurrence of disease outbreaks by 2050 and 2070. We used Maxent ver. 3.4.0 to develop SDMs. We used six global climate models (BCC-CSM1-1, CCSM4, GISS-E2-R, MIROC5, HadGEM2-ES and MPI-ESM-LR) for two representative concentration pathways (4.5 and 8.5) and two time projections (2050 and 2070) to detect future climate projections of D. sapinea. The most important EGVs influencing outbreaks were land cover, altitude, mean temperature of driest and wettest quarter, precipitation of wettest quarter, precipitation seasonality and minimum temperature of coldest month. The distribution of D. sapinea mostly expanded in central and southern Italy and shifted in altitude upwards on average by ca. 93m a.s.l. Moreover the fungus expanded the range where disease outbreaks may be recorded in response to an increase in the mean temperature of wettest and driest quarter by ca. 1.9 C and 5.8 C, respectively in all climate change scenarios. Precipitation of wettest quarter did not differ between current and any of future models. Under different climate change scenarios D. sapinea's disease outbreaks will be likely to affect larger areas of pine forests in the country, probably causing heavy effects on the dynamics and evolution of these stands or perhaps constraining their survival.

This study aimed to simulate oak and beech forest growth under various scenarios of climate change and to evaluate how the forest response depends on site properties and particularly on stand characteristics using the individual process-based model HETEROFOR. First, this model was evaluated on a wide range of site conditions. We used data from 36 long-term forest monitoring plots to initialize, calibrate, and evaluate HETEROFOR. This evaluation showed that HETEROFOR predicts individual tree radial growth and height increment reasonably well under different growing conditions when evaluated on independent sites. In our simulations under constant CO2 concentration ([CO2]cst) for the 2071-2100 period, climate change induced a moderate net primary production (NPP) gain in continental and mountainous zones and no change in the oceanic zone. The NPP changes were negatively affected by air temperature during the vegetation period and by the annual rainfall decrease. To a lower extent, they were influenced by soil extractable water reserve and stand characteristics. These NPP changes were positively affected by longer vegetation periods and negatively by drought for beech and larger autotrophic respiration costs for oak. For both species, the NPP gain was much larger with rising CO2 concentration ([CO2]var) mainly due to the CO2 fertilisation effect. Even if the species composition and structure had a limited influence on the forest response to climate change, they explained a large part of the NPP variability (44% and 34% for [CO2]cst and [CO2]var, respectively) compared to the climate change scenario (5% and 29%) and the inter-annual climate variability (20% and 16%). This gives the forester the possibility to act on the productivity of broadleaved forests and prepare them for possible adverse effects of climate change by reinforcing their resilience.

AbstractIn many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAM For more than five decades, research has been conducted at Ny-Ålesund, in Svalbard, Norway, to understand the structure and functioning of High-Arctic ecosystems and the profound impacts on them of environmental change. Terrestrial, freshwater, glacial and marine ecosystems are accessible year-round from Ny-Ålesund, providing unique opportunities for interdisciplinary obser-vational and experimental studies along physical, chemical, hydrological and climatic gradients. Here, we synthesize terrestrial and freshwater research at Ny-Ålesund and review current knowledge of biodiversity patterns, species population dynamics and interactions, ecosystem processes, biogeochemical cycles and anthropogenic impacts. There is now strong evidence of past and ongoing biotic changes caused by climate change, including negative effects on populations of many taxa and impacts of rain-on-snow events across multiple trophic levels. While species-level characteristics and responses are well under-stood for macro-organisms, major knowledge gaps exist for microbes, inverte-brates and ecosystem-level processes. In order to fill current knowledge gaps, we recommend (1) maintaining monitoring efforts, while establishing a long-term ecosystem-based monitoring programme; (2) gaining a mechanistic under-standing of environmental change impacts on processes and linkages in food webs; (3) identifying trophic interactions and cascades across ecosystems; and (4) integrating long-term data on microbial, invertebrate and freshwater com-munities, along with measurements of carbon and nutrient fluxes among soils, atmosphere, freshwaters and the marine environment. The synthesis here shows that the Ny-Ålesund study system has the characteristics needed to fill these gaps in knowledge, thereby enhancing our understanding of High-Arctic ecosystems and their responses to environmental variability and change