AUTHOR=Hou Guanglei , Zhang Haobin , Liu Zhaoli , Chen Ziqi , Cao Yakun 

TITLE=Historical reconstruction of aquatic vegetation of typical lakes in Northeast China based on an improved CA-Markov model

JOURNAL=Frontiers in Ecology and Evolution

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2022.1031678

DOI=10.3389/fevo.2022.1031678

ISSN=2296-701X

ABSTRACT=Aquatic vegetation is an important marker of lake ecosystem change. It plays an important supporting role in the lake ecosystem, and its abundance and cover changes affect the ecosystem’s balance. Collecting accurate long-term distribution data about aquatic vegetation can help to monitor lake ecosystem change, thereby providing scientific support for efforts to maintain the balance of the ecosystem. However, due to the lack of historical data, it is difficult to estimate the spatial distribution of aquatic vegetation. As a result, the areas and spatial distribution of aquatic vegetation in historical periods are important for understanding historical processes and change patterns. Therefore, we analyzed remote sensing data on the spatial distribution of aquatic vegetation data in two typical lakes (Xingkai Lake and Hulun Lake) in Northeast China in six periods from the 1970s to 2015. Then, we built a transfer probability matrix for changes in hydrothermal conditions (temperature and precipitation) based on similar periods, and we designed suitability images using the spatial frequency and temporal continuity of the constraints. Finally, we established an improved CA-Markov model based on the transfer probability matrix and suitability images to reconstruct the potential distributions of aquatic vegetation in the two northeastern lakes during the 1950s and 1960s. The improved CA-Markov model can effectively reconstruct the historical potential distribution of aquatic vegetation. The areas of aquatic vegetation in the 1950s and 1960s were 102.37 km2 and 100.7 km2 for the Xinkai Lakes and 90.81km2 and 88.15km2 for Hulun Lake, respectively. Compared with the traditional CA-Markov model, the overall accuracy of the improved model increased by more than 50%. This study provides an accurate methodology for simulating the potential historical distributions of aquatic vegetation to enrich the study of lake ecosystems’ historical evolution.