Relative importance of environmental variables for the distribution of the invasive marsh species Spartina alterniflora across different spatial scales
Huiyu Liu A B C D E , Haibo Gong A B C D , Xiangzhen Qi A B C D , Yufeng Li A B C D and Zhenshan Lin A B C D
+ Author Affiliations
- Author Affiliations
A College of Geography Science, Nanjing Normal University, 1 Wenyuan Road, Qixia District, Nanjing, 210023, P.R. China.
B State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), 1 Wenyuan Road, Nanjing, 210023, P.R. China.
C Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, 1 Wenyuan Road, Nanjing, 210023, P.R. China.
D Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing, 210023, P.R. China.
E Corresponding author. Email: liuhuiyu@njnu.edu.cn
Marine and Freshwater Research 69(5) 790-801 https://doi.org/10.1071/MF17100
Submitted: 14 April 2017 Accepted: 1 November 2017 Published: 6 February 2018
Abstract
The relative importance of environmental variables for Spartina alterniflora distribution was investigated across different spatial scales using maximum entropy modelling (MaxEnt), a species distribution modelling technique. The results showed that elevation was the most important predictor for species presence at each scale. Mean diurnal temperature range and isothermality were the second most important predictors at national and regional scales respectively. Soil drainage class, pH and organic carbon were important on the northern Chinese coast. The importance of climatic variable type was highest at global and national scales and declined as the scale decreased. The importance of soil variable type was lower at coarser scales, but varied greatly at finer scales. The relationships between environmental variables and species presence changed as the variables’ ranges changed across different scales. Climatic and soil variables were substantially affected by interactions among variables, which changed their relationships with species presence and relative importance. The modelled suitable area on the Chinese coast decreased from 54.16 to 12.64% limited by elevation from the global to national scale, and decreased to 8.04% limited by soil drainage, pH and organic carbon from the national to regional scale. The findings of the present study emphasise the importance of spatial scale for understanding relationships between environmental variables and the presence of S. alterniflora.
Additional keywords: interaction, MaxEnt, multiple scale, species distribution.
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