Tree biodiversity of warm drylands is likely to decline in a drier world

Relative decline in density of Northern Hemisphere tree species in warm and arid regions of their climate niches

Although climate change is expected to drive tree species toward colder and wetter regions of their distribution, broadscale empirical evidence is lacking. One possibility is that past and present human activities in forests obscure or alter the effects of climate. Here, using data from more than two million monitored trees from 73 widely distributed species, we quantify changes in tree species density within their climatic niches across Northern Hemisphere forests. We observe a reduction in mean density across species, coupled with a tendency toward increasing tree size. However, the direction and magnitude of changes in density exhibit considerable variability between species, influenced by stand development that results from previous stand-level disturbances. Remarkably, when accounting for stand development, our findings show a significant change in density toward cold and wet climatic conditions for 43% of the species, compared to only 14% of species significantly changing their density toward warm and arid conditions in both early- and late-development stands. The observed changes in climate-driven density showed no clear association with species traits related to drought tolerance, recruitment and dispersal capacity, or resource use, nor with the temperature or aridity affiliation of the species, leaving the underlying mechanism uncertain. Forest conservation policies and associated management strategies might want to consider anticipated long-term species range shifts alongside the integration of contemporary within-distribution density changes.

Microrefugia and microclimate: Unraveling decoupling potential and resistance to heatwaves

Microrefugia, defined as small areas maintaining populations of species outside their range margins during environmental extremes, are increasingly recognized for their role in conserving species in the face of climate change. Understanding their microclimatic dynamics becomes crucial with global warming leading to severe temperature and precipitation changes. This study investigates the phenomenon of short-term climatic decoupling within microrefugia and its implications for plant persistence in the Mediterranean region of southeastern France. We focus on microrefugia's ability to climatically disconnect from macroclimatic trends, examining temperature and Vapor Pressure Deficit (VPD) dynamics in microrefugia, adjacent control plots, and weather stations. Our study encompasses both "normal" conditions and heatwave episodes to explore the role of microrefugia as thermal and moisture insulators during extreme events. Landscape attributes such as relative elevation, solar radiation, distance to streams, and vegetation height are investigated for their contribution to short-term decoupling. Our results demonstrate that microrefugia exhibit notable decoupling from macroclimatic trends. This effect is maintained during heatwaves, underscoring microrefugia's vital role in responding to climatic extremes. Importantly, microrefugia maintain lower VPD levels than their surroundings outside and during heatwaves, potentially mitigating water stress for plants. This study advances our understanding of microclimate dynamics within microrefugia and underscores their ecological importance for plant persistence in a changing climate. As heatwaves become more frequent and severe, our findings provide insights into the role of microrefugia in buffering but also decoupling against extreme climatic events and, more generally, against climate warming. This knowledge emphasizes the need to detect and protect existing microrefugia, as they can be integrated into conservation strategies and climate change adaptation plans.

Automatedly identify dryland threatened species at large scale by using deep learning

Dryland biodiversity is decreasing at an alarming rate. Advanced intelligent tools are urgently needed to rapidly, automatedly, and precisely detect dryland threatened species on a large scale for biological conservation. Here, we explored the performance of three deep convolutional neural networks (Deeplabv3+, Unet, and Pspnet models) on the intelligent recognition of rare species based on high-resolution (0.3 m) satellite images taken by an unmanned aerial vehicle (UAV). We focused on a threatened species, Populus euphratica, in the Tarim River Basin (China), where there has been a severe population decline in the 1970s and restoration has been carried out since 2000. The testing results showed that Unet outperforms Deeplabv3+ and Pspnet when the training samples are lower, while Deeplabv3+ performs best as the dataset increases. Overall, when training samples are 80, Deeplabv3+ had the best overall performance for Populus euphratica identification, with mean pixel accuracy (MPA) between 87.31 % and 90.2 %, which, on average is 3.74 % and 11.29 % higher than Unet and Pspnet, respectively. Deeplabv3+ can accurately detect the boundaries of Populus euphratica even in areas of dense vegetation, with lower identification uncertainty for each pixel than other models. This study developed a UAV imagery-based identification framework using deep learning with high resolution in large-scale regions. This approach can accurately capture the variation in dryland threatened species, especially those in inaccessible areas, thereby fostering rapid and efficient conservation actions.

Risk of tree species decline under aridification

The risk of decline due to climate change varies among different tree species, resulting in both winners and losers. However, quantifying the risk of species decline remains a challenging task, particularly due to regional variability in the rate of climate change. Additionally, the diverse evolutionary histories of species have resulted in a variety of distributions, forms, and functions, leading to diverse responses to climate. Cartereau et al. unravel these complexities by focusing on the vulnerability and exposure of species to global change, and quantify species' risk of decline due to aridification in warm drylands by the end of this century.