Effect of fire and post-fire management on soil microbial communities in a lower subtropical forest ecosystem after a mountain fire

Wildfires and post-fire management exert profound effects on soil properties and microbial communities in forest ecosystems. Understanding microbial community recovery from fire and what the best post-fire management should be is very important but needs to be sufficiently studied. In light of these gaps in our understanding, this study aimed to assess the short-term effects of wildfire and post-fire management on both bacteria and fungi community composition, diversity, structure, and co-occurrence networks, and to identify the principal determinants of soil processes influencing the restoration of these communities. Specifically, we investigated soil bacterial and fungal community composition, diversity, structure, and co-occurrence networks in lower subtropical forests during a short-term (<3 years) post-fire recovery period at four main sites in Guangdong Province, southern China. Our results revealed significant effects of wildfires on fungal community composition, diversity, and co-occurrence patterns. Network analysis indicated reduced bacterial network complexity and connectivity post-fire, while the same features were enhanced in fungal networks. However, post-fire management effects on microbial communities were negligible. Bacterial diversity correlated positively with soil microbial biomass nitrogen, soil organic carbon, and soil total nitrogen. Conversely, based on the best random forest model, fungal community dynamics were negatively linked to nitrate-nitrogen and soil water content. Spearman's correlation analysis suggested positive associations between bacterial networks and soil factors, whereas fungal networks exhibited predominantly negative associations. This study elucidates the pivotal role of post-fire management in shaping ecological outcomes. Additionally, it accentuates the discernible distinctions between bacterial and fungal responses to fire throughout a short-term recovery period. These findings contribute novel insights that bear significance in evaluating the efficacy of environmental management strategies.

Modeling impacts of climate change on the potential distribution of six endemic baobab species in Madagascar

Madagascar, a globally renowned biodiversity hotspot characterized by high rates of endemism, is one of the few remaining refugia for many plants and animal species. However, global climate change has greatly affected the natural ecosystem and endemic species living in Madagascar, and will likely continue to influence species distribution in the future. Madagascar is home to six endemic baobab (Adansonia spp., Bombacoideae [Malvaceae]) species (Adansonia grandidieri, A. suarezensis, A. madagascariensis, A. perrieri, A. rubrostipa, A. za), which are remarkable and endangered plants. This study aimed to model the current distribution of suitable habitat for each baobab species endemic to Madagascar and determine the effect that climate change will have on suitable baobab habitat by the years 2050 and 2070. The distribution was modeled using MaxEnt based on locality information of 245 occurrence sites of six species from both online database and our own field work. A total of seven climatic variables were used for the modeling process. The present distribution of all six Madagascar's baobabs was largely influenced by temperature-related factors. Although both expansion and contraction of suitable habitat are predicted for all species, loss of original suitable habitat is predicted to be extensive. For the most widespread Madagascar baobab, A. za, more than 40% of its original habitat is predicted to be lost because of climate change. Based on these findings, we recommend that areas predicted to contract in response to climate change should be designated key protection regions for baobab conservation.