Predicting the distribution of plant associations under climate change: A case study on Larix gmelinii in China

Abstract

Association is the basic unit of plant community classification. Exploring the distribution of plant associations can help improve our understanding of biodiversity conservation. Different associations depend on different habitats and studying the association level is important for ecological restoration, regional ecological protection, regulating the ecological balance, and maintaining biodiversity. However, previous studies have only focused on suitable distribution areas for species and not on the distribution of plant associations. Larix gmelinii is a sensitive and abundant species that occurs along the southern margin of the Eurasian boreal forests, and its distribution is closely related to permafrost. In this study, 420 original plots of L. gmelinii forests were investigated. We used a Maxent model and the ArcGIS software to project the potential geographical distribution of L. gmelinii associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. We used the multi‐classification logistic regression analysis method to obtain the response of the suitable area change for the L. gmelinii alliance and associations to climate change under different climate scenarios. Results revealed that temperature is the most crucial factor affecting the distribution of L. gmelinii forests and most of its associations under different climate scenarios. Suitable areas for each association type are shrinking by varying degrees, especially due to habitat loss at high altitudes in special terrains. Different L. gmelinii associations should have different management measures based on the site conditions, composition structure, growth, development, and renewal succession trends. Subsequent research should consider data on biological factors to obtain more accurate prediction results.

Future Reductions in Suitable Habitat for Key Tree Species Result in Declining Boreal Forest Aboveground Biomass Carbon in China

“…Our results showed that the future distribution of the highly suitable area for coniferous species (L. gmelinii) is projected to shrink primarily in Northeast China, while evergreen broad-leaved tree species (S. superba and C. officinarum) will tend to expand towards the central regions of China from 2015 to 2060 based on the MaxEnt model. Similar conclusions have also been reported, for example, by Bai et al (2016) and Chen et al (2022) [40,41], who found, through research on the relationship between tree rings and temperature changes, that rapid warming will lead to the gradual decline of L. gmelinii in Northeast China. Du et al (2022) [42] found that the future suitable habitat area of eight species of tree species in the Northeast region, including L. gmelinii, will decrease by 10%-30%.…”

Prediction of Potential Distribution Patterns of Three Larix Species on Qinghai-Tibet Plateau under Future Climate Scenarios

“…The precision of the MaxEnt model in predicting species spatial distribution is not significantly affected by the sample size [24]. It performed excellently in terms of its simulation performance, either in the suitability research on Larix gmelinii among the 182 current distribution points or in a study on species suitable distribution areas of Picea smithiana (Pinaceae: Picea) at the extremely low sample size (n = 28) among the current distribution points, further demonstrating that the MaxEnt model well predicted the distribution patterns of rare species [15,25]. Xiao et al [26] employed the MaxEnt and genetic algorithm for rule-set production (GARP) models to predict the suitable distribution area of Procambarus clarkii, finding that the prediction results by MaxEnt were more accurate.…”