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AbstractForest growth is sensitive to interannual climatic change in the alpine treeline ecotone (ATE). Whether the alpine treeline ecotone shares a similar pattern of forest growth with lower elevational closed forest belt (CFB) under changing climate remains unclear. Here, we reported an unprecedented acceleration ofPicea schrenkianaforest growth since 1960s in theATEof Tianshan Mountains, northwestern China by a stand‐total sampling along six altitudinal transects with three plots in each transect: one from theATEbetween the treeline and the forest line, and the other two from theCFB. All the sampledP.schrenkianaforest patches show a higher growth speed after 1960 and, comparatively, forest growth in theCFBhas sped up much slower than that in theATE. The speedup of forest growth at theATEis mainly accounted for by climate factors, with increasing temperature suggested to be the primary driver. Stronger water deficit as well as more competition withinthe CFBmight have restricted forest growth there more than that within theATE, implying biotic factors were also significant for the accelerated forest growth in theATE, which should be excluded from simulations and predictions of warming‐induced treeline dynamics.

AbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

AbstractRising atmospheric [CO2] and associated climate change are expected to modify primary productivity across a range of ecosystems globally. Increasing aridity is predicted to reduce grassland productivity, although rising [CO2] and associated increases in plant water use efficiency may partially offset the effect of drying on growth. Difficulties arise in predicting the direction and magnitude of future changes in ecosystem productivity, due to limited field experimentation investigating climate and CO2 interactions. We use repeat near‐surface digital photography to quantify the effects of water availability and experimentally manipulated elevated [CO2] (eCO2) on understorey live foliage cover and biomass over three growing seasons in a temperate grassy woodland in south‐eastern Australia. We hypothesised that (i) understorey herbaceous productivity is dependent upon soil water availability, and (ii) that eCO2 will increase productivity, with greatest stimulation occurring under conditions of low water availability. Soil volumetric water content (VWC) determined foliage cover and growth rates over the length of the growing season (August to March), with low VWC (<0.1 m3 m−3) reducing productivity. However, eCO2 did not increase herbaceous cover and biomass over the duration of the experiment, or mitigate the effects of low water availability on understorey growth rates and cover. Our findings suggest that projected increases in aridity in temperate woodlands are likely to lead to reduced understorey productivity, with little scope for eCO2 to offset these changes.

AbstractClimate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.

AbstractVegetation productivity first increases and then decreases with temperature; and temperature corresponding to the maximum productivity is called optimal temperature (Topt). In this study, we used satellite derived near‐infrared reflectance of vegetation (NIRv) data to map Topt of vegetation productivity at the spatial resolution of 0.1° on the Tibetan Plateau (TP), one of most sensitive regions in the climate system. The average Topt of non‐forest vegetation on the TP is about 14.7°C, significantly lower than the Topt value used in current ecosystem models. A remarkable geographical heterogeneity in Topt is observed over the TP. Higher Topt values generally appear in the north‐eastern TP, while the south‐western TP has relatively lower Topt (<10°C), in line with the difference of climate conditions and topography across different regions. Spatially, Topt tends to decrease by 0.41°C per 100 m increase in elevation, faster than the elevational elapse rate of growing season temperature, implying a potential CO2 regulation of Topt in addition to temperature acclimation. Topt increases by 0.66°C for each 1°C of rising mean annual temperature as a result of vegetation acclimation to climate change. However, at least at the decadal scale, there is no significant change in Topt between 2000s and 2010s, suggesting that the Topt climate acclimation may not keep up with the warming rate. Finally, future (2091–2100) warming could be close to and even surpass Topt on the TP under different RCP scenarios without considering potential climate acclimation. Our analyses imply that the temperature tipping point when the impact of future warming shifts from positive to negative on the TP is greatly overestimated by current vegetation models. Future research needs to include varying thermal and CO2 acclimation effects on Topt across different time scales in vegetation models.

AbstractSpecies extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate‐dependent meta‐population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi‐extinct by 2100. We conclude that the species should be listed as threatened under the ESA.