• Energy Research

A large fraction of Earth’s plant species are faced with increased chances of extinction.

AbstractCorrelative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

AbstractA key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems.

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin1,2, but is increasingly threatened by deforestation and fire3,4. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079-189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3-85.2% of species that are listed as threatened in this region5. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253-10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon.

SummaryWith climate change, heat waves are becoming increasingly frequent, intense and broader in spatial extent. However, while the lethal effects of heat waves on humans are well documented, the impacts on flora are less well understood, perhaps except for crops. We summarize recent findings related to heat wave impacts including: sublethal and lethal effects at leaf and plant scales, secondary ecosystem effects, and more complex impacts such as increased heat wave frequency across all seasons, and interactions with other disturbances. We propose generalizable practical trials to quantify the critical bounding conditions of vulnerability to heat waves. Collectively, plant vulnerabilities to heat waves appear to be underappreciated and understudied, particularly with respect to understanding heat wave driven plant die‐off and ecosystem tipping points.

Abstract Aims Plant height is a key functional trait related to aboveground biomass, leaf photosynthesis and plant fitness. However, large-scale geographical patterns in community-average plant height (CAPH) of woody species and drivers of these patterns across different life forms remain hotly debated. Moreover, whether CAPH could be used as a predictor of ecosystem primary productivity is unknown. Methods We compiled mature height and distributions of 11 422 woody species in eastern Eurasia, and estimated geographic patterns in CAPH for different taxonomic groups and life forms. Then we evaluated the effects of environmental (including current climate and historical climate change since the Last Glacial Maximum (LGM)) and evolutionary factors on CAPH. Lastly, we compared the predictive power of CAPH on primary productivity with that of LiDAR-derived canopy-height data from a global survey. Important Findings Geographic patterns of CAPH and their drivers differed among taxonomic groups and life forms. The strongest predictor for CAPH of all woody species combined, angiosperms, all dicots and deciduous dicots was actual evapotranspiration, while temperature was the strongest predictor for CAPH of monocots and tree, shrub and evergreen dicots, and water availability for gymnosperms. Historical climate change since the LGM had only weak effects on CAPH. No phylogenetic signal was detected in family-wise average height, which was also unrelated to the tested environmental factors. Finally, we found a strong correlation between CAPH and ecosystem primary productivity. Primary productivity showed a weaker relationship with CAPH of the tallest species within a grid cell and no relationship with LiDAR-derived canopy height reported in the global survey. Our findings suggest that current climate rather than historical climate change and evolutionary history determine the geographical patterns in CAPH. However, the relative effects of climatic factors representing environmental energy and water availability on spatial variations of CAPH vary among plant life forms. Moreover, our results also suggest that CAPH can be used as a good predictor of ecosystem primary productivity.