Prediction of present and future distribution of the Schlegel’s Japanese gecko (Gekko japonicus) using MaxEnt modeling

Abstract

Background: Understanding the geographical distribution of a species is a key component of studying its ecology, evolution, and conservation. Although Schlegel's Japanese gecko (Gekko japonicus) is widely distributed in Northeast Asia, its distribution has not been studied in detail. We predicted the present and future distribution of G. japonicus across China, Japan, and Korea based on 19 climatic and 5 environmental variables using the maximum entropy (MaxEnt) species distribution model. Results: Present time major suitable habitats for G. japonicus, having greater than 0.55 probability of presence (threshold based on the average predicted probability of the presence records), are located at coastal and inland cities of China; western, southern, and northern coasts of Kyushu and Honshu in Japan; and southern coastal cities of Korea. Japan contained 69.3% of the suitable habitats, followed by China (27.1%) and Korea (4.2%). Temperature seasonality (66.5% of permutation importance) was the most important predictor of the distribution. Future distributions according to two climate change scenarios predicted that by 2070, and overall suitable habitats would decrease compared to the present habitats by 18.4% (scenario RCP 4.5) and 10.4% (scenario RCP 8.5). In contrast to these overall trends, range expansions are expected in inland areas of China and southern parts of Korea. Conclusions: Suitable habitats predicted for G. japonicus are currently located in coastal cities of Japan, China, and Korea, as well as in isolated patches of inland China. Due to climate change, suitable habitats are expected to shrink along coastlines, particularly at the coastal-edge of climate change zones. Overall, our results provide essential distribution range information for future ecological studies of G. japonicus across its distribution range.

The effect of climate change on habitat suitability and a distribution model of the Iranian fat-tailed gecko, Eublepharis angramainyu Anderson and Leviton, 1966 (Sauria: Eublepharidae) since the Last Interglacial to 2050

“…Third, some increases in suitable habitats are predicted in Iran (Bohsher, Fars, Kohgiluyeh and Boyer-Ahmad, Chaharmahal and Bakhtiari, Lorestan, and Kermanshah Provinces) as well as in Iraq (Diyala, Salah al-Din, Kirkuk, Nineveh Provinces) (Figure 5). Therefore, depending on the region, climatic changes can cause disappearance/ decrease as well as partial expansion of suitable habitats (Parmesan 2006;Bonino et al 2015;Kim et al 2020). These latter regions might function as potential refuges for conservation of the species under changing climate in the future (Kim et al 2020).…”

“…Therefore, depending on the region, climatic changes can cause disappearance/ decrease as well as partial expansion of suitable habitats (Parmesan 2006;Bonino et al 2015;Kim et al 2020). These latter regions might function as potential refuges for conservation of the species under changing climate in the future (Kim et al 2020).…”

Past, present, and future predictions on the suitable habitat of the Slender racer (Orientocoluber spinalis) using species distribution models

“…A bias in presence can cause overrepresentation, with the environmental variables from that particular region excessively affecting habitat suitability (Boakes et al, 2010 ; Kramer‐Schadt et al, 2013 ). To avoid overfitting of the habitat suitability of O. spinalis in South Korea, we spatially filtered on the data (Anderson & Raza, 2010 ; Radosavljevic & Anderson, 2014 ; Kim, Park, Bae, et al, 2020 ) using a 1 km, 60 km, 75 km, and 100 km radius. For each radius, we selected only one random presence datapoint among the overlapping data.…”

“…We performed the SDMs for past and future prediction based on the Community Climate System Model 4.0 (CCSM4), which is often used for amphibians and reptile SDMs (Borzée et al, 2019 ; González‐Fernández et al, 2018 ; Kim, Park, Bae, et al, 2020 ). For the past modeling, we used three time windows: (1) the last interglacial period about 130,000 years ago, when the average air temperature was 5°C higher and sea level was 2.2 to 3.4 m higher than present (Andersen et al, 2004 ; Otto‐Bliesner et al, 2006 ).…”

“…Species distribution models (SDMs) are used to determine species distribution and can often predict habitat shifts following climate change (Broennimann et al, 2007 ). Reptile SDMs can also be effectively applied to identify unknown reptile populations in a particular region (Franklin et al, 2009 ; Guisan & Hofer, 2003 ; Raxworthy et al, 2003 ), such as done with Uma inornata (Barrows et al, 2010 ), Lacerta lepida , Iberolacerta monticola , Hemidactylus turcicus (Ceia‐Hasse et al, 2014 ), Calodactylodes aureus (Srinivasulu & Srinivasulu, 2016 ), and Gekko japonicus (Kim, Park, Bae, et al, 2020 ; Kim, Park, Fong, et al, 2020 ). SDMs for past timelines can also provide ecological and evolutionary information on the historical shifts of species distribution over time (Acevedo et al, 2012 ; Elith & Leathwick, 2009 ; Franklin, 2010 ; Teixeira & Arntzen, 2002 ).…”