Potential impact of climate change on canopy tree species composition of cool‐temperate forests in Japan using a multivariate classification tree model

Abstract

Climate change will likely change the species composition or abundance of plant communities, and it is important to anticipate these changes to develop climate change adaptation policies. We chose beech (Fagus crenata Blume) and its competitive tree species as target species to evaluate potential turnover in forest types under climate change using a multivariate classification tree model. To construct the model, geographical presence/absence data for nine target species were used as multivariate response variables, with five climatic factors were used as predictor variables. Current and future distribution probabilities for the target species were calculated, and the 15 dominant forest types were subjectively classified in approximately 1‐km2 grid cells within the area of the current beech forest distribution. All 16,398 grid cells of the beech‐dominant forest type (FCR‐QCR) were projected to be replaced in the future by five Quercus crispula‐dominant types (59% of FCR‐QCR grid cells), four Q. serrata types (22%), two Q. salicina types (8%), or two Abies firma types (0.1%). The FCR‐QCR type remained unchanged (stable) in only 11.4% of grid cells; these were mainly distributed at high elevations in snowy areas on the Sea of Japan side of the country. In contrast, vulnerable habitats (future probability of beech occurrence less than 1.0%) were found at low elevations on both the Sea of Japan and the Pacific Ocean sides. Northwards or upwards range expansions or increases of Quercus spp., in particular, need to be carefully monitored.

Soil Nutrients Drive Function and Composition of phoC-Harboring Bacterial Community in Acidic Soils of Southern China

“…Monte Carlo simulation tests were used to evaluate the relationship between each soil variable and the community composition variances (Legendre and Legendre, 2012). A multiple regression tree (MRT) was built to identify most important soil variables influencing the community structure (Matsui et al, 2018). VPA, CCA, and Monte Carlo simulation tests were conducted using the vegan package in R software (version 2.15.0), and MRT was performed using the mvpart package of R.…”

A new formal classification for Japanese forest vegetation based on traditional phytosociological concepts

“…In the last 30–40 years, since the traditional phytosociological system in Japan was first proposed, the species composition and habitat of forest vegetation have changed. These changes are attributed to the progress of succession caused by the abandonment of coppice forests (Tsuji & Hoshino, 1992; Saito et al, 2004), the expansion of deer (Ohashi et al, 2007; Ohashi & Hoshino, 2014), and climate change (Nakazono et al, 2016; Matsui et al, 2018). Therefore, it is necessary to confirm that the traditional phytosociological system, which was based on investigation 30–40 years ago, can be applied to present forest vegetation data sets to advance the formulation of new vegetation classification methods for Japan.…”

“…In the last 30-40 years, since the traditional phytosociological system in Japan was first proposed, the species composition and habitat of forest vegetation have changed. These changes are attributed to the progress of succession caused by the abandonment of coppice forests (Tsuji & Hoshino, 1992;Saito et al, 2004), the expansion of deer (Ohashi et al, 2007;Ohashi & Hoshino, 2014), and climate change (Nakazono et al, 2016;Matsui et al, 2018).…”

Climate‐based approach for modeling the distribution of montane forest vegetation in Taiwan

“…The vegetation–climate relationship has long been recognized by ecologists, and the concept has been applied to depict the regionalization of ecoregions or vegetation types for decades (Holdridge, ; Bailey, ; Su, ; Fang, Song, Liu, & Piao, ). Recent progress in ecological niche modeling and the accessibility of accurate and fine‐scale climate data has enabled vegetation–climate relationships to be used in numerous studies for a variety of purposes, including projection of the historical and current distribution of biomes and forests for management purposes (Rehfeldt, Crookston, Warwell, & Evans, ), prediction of changes in species (Matsui et al, ) or ecosystems (Brinkmann, Patzelt, Schlecht, & Buerkert, ; Rehfeldt, Crookston, Sáenz‐Romero, & Campbell, ; Wang, Campbell, O'Neill, & Aitken, ) under various global warming scenarios, and provision of strategic tools for conservation and adaptation to the impact of climate change (Hansen & Phillips, ; Klassen & Burton, ; Wang, Wang, et al, ).…”