Predicting the Potential Habitat of Three Endangered Species of Carpinus Genus under Climate Change and Human Activity

Abstract

The impact of climate change and human activities on endangered plants has been a serious concern in forest ecology. Some Carpinus plants have become extinct. Thus, we need to pay more attention to the Carpinus plants that are not yet extinct but are endangered. Here, we employed the species distribution model (SDM) considering different climate change scenarios and human footprint to test the potential habitat changes of three Carpinus species (C. oblongifolia, C. tientaiensis, and C. purpurinervis) in the future. Our results showed that the mean diurnal range of temperature (MDRT), isothermality, mean temperature of wettest quarter, and human footprint were the most influential factors determining the distribution of C. oblongifolia. Precipitation seasonality (coefficient of variation), MDRT, and precipitation of driest quarter were the most important climatic factors affecting C. tientaiensis. The minimum temperature of the coldest month was the most important factor in the distribution of C. purpurinervis. Our results also showed that the three species had different adaptability and habitat change trends under the future climate change scenarios, although they belong to the same genus. The potential habitats of C. oblongifolia would expand in the future, while the potential habitats of C. tientaiensis and C. purpurinervis would decrease for the same period. The predicted changes of these three endangered species on temporal and spatial patterns could provide a theoretical basis for their conservation strategies.

Predicting Climate Change Impacts on the Rare and Endangered Horsfieldia tetratepala in China

“…Utilizing SDMs to predict the potential geographical distribution of species is a hotspot in biodiversity conservation research, and has great significance for developing effective biodiversity conservation strategies [14,15,34]. Based on current species occurrence data and environmental variables, SDMs have been widely used to evaluate the potential distribution of species without biodiversity observations [28,[35][36][37][38].…”

“…Among these SDMs, MaxEnt modeling integrates machine learning and maximum entropy principles to predict the potential distribution areas of species, and have become the most powerful and extensively used models owing to their operation simplicity, faster operational capability, and high accuracy, even with minimal occurrence data points [40,[42][43][44][45][46][47]. For endangered species that have few observational occurrences and live in areas where it is difficult to collect occurrence data, the MaxEnt model provides an ideal model to predict their potential distributions under global climate change [14,15,34,36].…”

Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana

“…More specifically, CMD was the most important climate variable limiting O. rehderiana distribution as it effects plant growth and yield [42]. Similar to C. oblongifolia and C. tientaiensis, two endangered species, with the same niche, the distribution of O. rehderiana was limited by moisture deficit [43]. In addition, low temperatures and temperature differences are also climate factors limiting O. rehderiana distribution.…”

The Impact of Resources on the Adaptability of State Forest Companies. Some Evidence from the State Forests National Forest Holding

“…However, structural changes [31], the increasing complexity of the business environment [32], and many different driving forces affect significant changes in the forestry sector to date [33]. Climate and weather changes, natural threats, intense human activity [1], economic pressure resulting from the increased demand for wood [3], coupled with EU regulations and activities assuring forest sustainable management [4], increasing costs of forest management [5] results in forestry sector undergoing dynamic changes that affect its functioning to an extent larger than before. Indeed, Senko and Pykäläinen indicate that the forestry sector is now much more dynamic and less predictable than in the past [34] while Näyhä & Pesonen posit that in some respects the forest industry is facing challenges that have already been observed in other sectors [33], forcing the need to implement fundamental changes and compete in global markets [35].…”

“…Third, the intensified economic and human activity, resulting in the increased demand for wood, influences logging practices, and tree harvesting. Due to these stressors, forest ecosystems change dynamically [1,2]. At the same time, the required sustainable forest management is a complex task, as on one hand forest management faces pressure resulting from the increased demand for wood, which requires intensified timber plantations [3]; while on the other hand, efforts need to assure sustainable development of the forest areas and to preserve the ecosystems for endangered species [4].…”