Abstract
Abstract. Climate change is regarded as one of the most significant drivers of biodiversity loss and altered forest ecosystems. This study aimed to model the current species distribution of two dipterocarp species in Mount Makiling Forest Reserve as well as the future distribution under different climate emission scenarios and global climate models. A machine-learning algorithm based on the principle of maximum entropy (Maxent) was used to generate the potential distributions of two dipterocarp species – Shorea guiso and Parashorea malaanonan. The species occurrence records of these species and sets of bioclimatic and physical variables were used in Maxent to predict the current and future distribution of these dipterocarp species. The variables were initially reduced and selected using Principal Component Analysis (PCA). Moreover, two global climate models (GCMs) and climate emission scenarios (RCP4.5 and RCP8.5) projected to 2050 and 2070 were utilized in the study. The Maxent models predict that suitable areas for P. malaanonan will decline by 2050 and 2070 under RCP4.5 and RCP 8.5. On the other hand, S. guiso was found to benefit from future climate with increasing suitable areas. The findings of this study will provide initial understanding on how climate change affects the distribution of threatened species such as dipterocarps. It can also be used to aid decision-making process to better conserve the potential habitat of these species in current and future climate scenarios.
Highlights
It is estimated that 20-30% of plant and animal species will be at higher risk of extinction due to global warming; a significant portion of endemic species may become extinct by the year 2050 or 2100 as global mean temperatures exceed 2-3 °C above pre-industrial levels (Garcia et al, 2013)
This study aims to identify the different variables affecting the habitat distribution of Guijo and Bagtikan; generate the potential habitat distributions of Guijo and Bagtikan in Mount Makiling Forest Reserve (MMFR) using maximum entropy (Maxent); model future distribution of the species under different climate emission scenarios and global climate models; and recommend potential conservation strategy for the dipterocarp species
With jurisdiction under the University of the Philippines Los Baños (UPLB), the forest reserve is managed by the Makiling Center for Mountain Ecosystems (MCME) under the College of Forestry and Natural Resources
Summary
It is estimated that 20-30% of plant and animal species will be at higher risk of extinction due to global warming; a significant portion of endemic species may become extinct by the year 2050 or 2100 as global mean temperatures exceed 2-3 °C above pre-industrial levels (Garcia et al, 2013). Dipterocarps play a significant role in the global timber market industry of South and Southeast Asian countries (Appanah & Turnbull, 1998). The dipterocarps grow in evergreen, semi-evergreen, and deciduous forests. This characteristic of dipterocarps, when it comes to geographical range, flowering phenology, fruiting phenology, and ecological characteristic, makes them highly variable (Deb et al, 2017). Guijo (Shorea guiso) and Bagtikan (Parashorea malaanonan) are part of the dominant dipterocarp trees in (MMFR) and are classified as Critically Endangered and Vulnerable in the International Union for Conservation of Nature (IUCN) Red List (2017), respectively
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