EGU2020-4344
https://doi.org/10.5194/egusphere-egu2020-4344
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

The application of Species Distribution Modeling for wetland restoration: A case study in the Songnen Plain, Northeast China

Yehui Zhong1,2,3, Ming Jiang1,2, Zhenshan Xue1,2, Bo Liu1,2, and Guodong Wang1,2
Yehui Zhong et al.
  • 1Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China (zhongyehui@iga.ac.cn)
  • 2Jilin Provincial Joint Key Laboratory of Changbai Mountain Wetland and Ecology, Changchun, China
  • 3University of Chinese Academy of Sciences, Beijing, China

Species distribution models (SDMs) are an effective tool for measuring and predicting plant response to climate change, but their application to wetland species has been relatively limited. Here, we investigate the application of SDMs to study the current and future delimitation of wetlands in the Songnen Plain, one of the densest areas of natural wetlands in China. Specifically, we focus on the iconic wetland species Phragmites australis, one of the dominant species in the Songnen plain, which has been widely used for wetland restoration efforts.

Our study has four main goals: (i) to test and improve the applicability of SDM in our study; (ii) to delimit wetland areas for prioritization; (iii) to investigate the projected change in wetland distributions under future climate change scenarios; and (iv) to identify regions that appear more (or less) stable in the face of change, and to propose areas for suitable restoration efforts with land-use.

To achieve our goals, we apply a broad variety of environmental variables using MaxEnt, to project present and future (2050s) suitable areas under two representative concentration pathways (RCP4.5 and RCP8.5). AUC (area under the curve) is used as the test measure for model evaluation. To obtain a rich representative sampling of this species’ distribution, we use field-observational records from the National Science and Technology Fundamental Research Project “Investigation on Wetland Resource of China and Its Ecological and Environmental Benefits” (2013FY111800). In addition to exploring key abiotic parameters that influence P. australis distribution, we also explore the impact of different spatial resolutions (1 km2, 250 m2, 90 m2, 30 m2) of topographic information to assess model performance.

Our results demonstrated that the performance of the MaxEnt projection of P. australis was excellent (AUC=0.922), and improved with the addition of soil, topographic and hydrological variables, but did not improve significantly with increased resolutions of topographic variables. Using the optimized model, we delimited 28,644 km2 of suitable areas and 7,959 km2 of highly suitable areas under current scenarios. The future model under RCP4.5 scenario predicted a 9.5% and 3.1% increase in the suitable and highly suitable areas, respectively. The model under RCP8.5 predicted a much smaller increase in suitable areas, and a slight reduction in highly suitable habitat compared with the current scenario. Under both future scenarios, the geographic centers of potential habitat moved toward the southeast, with the mean latitude slightly rising. Finally, we delimited 2,364 km2 of priority restoration areas under RCP4.5, including 152 km2 of paddy field, 950 km2 of dry field and 1,262 km2 of saline-alkali land. The priority areas under RCP8.5 were smaller in all three land-use types.

Our study illuminates potential priority areas of the Songnen Plain for consideration in future wetland restoration efforts. For future research, we recommend more applications of SDMs with multiple species in wetland restoration, especially over larger scales and higher resolutions.

How to cite: Zhong, Y., Jiang, M., Xue, Z., Liu, B., and Wang, G.: The application of Species Distribution Modeling for wetland restoration: A case study in the Songnen Plain, Northeast China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4344, https://doi.org/10.5194/egusphere-egu2020-4344, 2020

Displays

Display file