Wetland Change Mapping Using Machine Learning Algorithms, and Their Link with Climate Variation and Economic Growth: A Case Study of Guangling County, China

Wetlands are a distinctive terrestrial ecosystem that benefits living things, including people, in various ways. Sustainable wetland ecosystem resources are needed to protect the global environment. Wetlands in China have undergone positive and negative changes in response to several factors, but studies documenting their long-term dynamicity have been few, particularly in Guangling County. This study examines the change of wetlands area based on remotely sensed data while exploring trends associated with climate variations and economic growth in Guangling County, China. Analysis of remotely sensed imagery, mainly in hilly and nonhomogeneous environments is problematic, largely as a result of interference and their high spectral non-homogeneity. We conducted experiments using five classical machine learning algorithms based on the Google Earth Engine (GEE) and obtained the greatest robustness and accuracy using a Support Vector Machine (SVM)—Radial Basis Function (RBF) kernel approach, with overall accuracy and kappa statistics ranging from 86% to 98.1% and from 0.789 to 0.960, respectively. Based on the SVM-RBF model’s outperformance of four other algorithms, we identified spatial distributions of wetland in the study area and associated change trends. We found that 45.71 km2 of wetland area was lost over the past 3.7 decades (January 1984–December 2020), or 81.82% of wetland area coverage. In this paper, we explore how factors such as county economic growth (GDP), humidity, and temperature variations are tightly linked with wetland change.

Analysis of Wetland Landcover Change in Great Lakes Urban Areas Using Self-Organizing Maps

Wetland loss and subsequent reduction of wetland ecosystem services in the Great Lakes region has been driven, in part, by changing landcover and increasing urbanization. With landcover change data, digital elevation models (DEM), and self-organizing maps (SOM), this study explores changing landcover and the flood mitigation attributes of wetland areas over a 15-year period in Toronto and Chicago. The results of this analysis show that (1) in the city of Toronto SOM clusters, the landcover change correlations with wetland volume and wetland area range between −0.1 to −0.5, indicating that a more intense landcover change tends to be correlated with small shallow wetlands, (2) in the city of Chicago SOM clusters, the landcover change correlations with wetland area range between −0.1 to −0.7, the landcover change correlations with wetland volume per area range between −0.1 to 0.8, and the landcover change correlations with elevation range between −0.2 to −0.6, indicating that more intense landcover change tends to be correlated with spatially small wetlands that have a relatively high water-storage capacity per area and are located at lower elevations. In both cities, the smallest SOM clusters represent wetland areas where increased landcover change is correlated with wetland areas that have high flood mitigation potential. This study aims to offer a new perspective on changing urban landscapes and urban wetland ecosystem services in Toronto and Chicago.

Spatiotemporal Evolution of Wetland Eco-Hydrological Connectivity in the Poyang Lake Area Based on Long Time-Series Remote Sensing Images

Hydrological connectivity is important for maintaining the stability and function of wetland ecosystems. Small-scale hydrological connectivity restricts large-scale hydrological cycle processes. However, long-term evolutionary studies and quantitative evaluation of the hydrological connectivity of wetlands in the Poyang Lake area have not been sufficiently conducted. In this study, we collected 21 Landsat remote sensing images and extracted land use data from 1989 to 2020, introducing a morphological spatial pattern analysis model to assess the wetland hydrological connectivity. A comprehensive method for evaluating the hydrological connectivity of wetlands was established and applied to the Poyang Lake area. The results showed that, over the course of 31 years, the wetland landscape in the Poyang Lake area changed dramatically, and the wetland area has generally shown a decreasing and then increasing trend, among which the core wetland plays a dominant role in the hydrological connectivity of the Poyang Lake area. In addition, the hydrological connectivity decreases as the core wetland area decreases. From 1989 to 2005, the landscape in the Poyang Lake area focused mainly on the transition from wetland to non-wetland. From 2005 to 2020, the conversion of wetland landscape types shows a clear reversal compared to the previous period, showing a predominant shift from non-wetland to wetland landscapes. The eco-hydrological connectivity of the wetlands in the Poyang Lake area from 1989 to 2020 first decreased, and then increased after 2005. In the early stage of the study (1989−2005), we found that the connectivity of 0.3444 in 2005 was the lowest value in the study period. A resolution of 30 m and an edge effect width of 60 m were optimal for studying the hydrological connectivity of wetlands in the Poyang Lake area. The main drivers of the changes in hydrological connectivity were precipitation and the construction of large-scale water conservation projects, as well as changes in land use. This study provides a good basis for assessing hydrological connectivity in a meaningful way, and is expected to provide new insights for maintaining and restoring biodiversity and related ecosystem services in the Poyang Lake area.

Finding Out Suitable Index for Wetland Mapping in Barind Plain of India and Predicting Dynamics of Its Area and Depth

Remote Sensing and GIS play an important role in mapping and monitoring natural resources and their management. The present study attempts to delineate wetland in the lower Tangon river basin in the Barind flood plain region using suitable water body extraction indices. The main objectives of this present study are mapping and monitoring the flood plains wetlands along with the future status of wetland areas of 2028 and 2038 using the advanced Artificial Neural Network-based Cellular Automata (ANN-CA) model. Apart from wetland area prediction, wetland depth simulation and prediction are also carried out using statistical (Adaptive Exponential Smoothing) as well as advanced machine learning algorithms such as Bagging, Random subspace, Random forest, Support vector machine, etc. for the year 2028. The result shows a remarkable change in the overall wetland area in the upcoming two decades. The small wetland patches away from the master stream are expected to dry out during the forecast period, where the major wetland patches nearer to the master stream with greater depth are rather sustainable but their depth of water may be reduced in the next decades. All models show satisfactory performance for wetland depth mapping, but the Random subspace model was identified as the best-suited depth predicting method and machine learning models explored better results that adaptive exponential smoothing. This recent study will definitely be very helpful for the policymakers for managing wetland landscape as well as the natural environment.

Dyke demolition led to a sharp decline in waterbird diversity due to reduction in habitat quality: A case study of Dongting Lake, China

Waterbird responses to habitat changes are of great concern in ecology. Dongting Lake is the second-largest freshwater lake in China, and its vast wetland area provides an important wintering habitat for migratory waterbirds of the East Asian–Australasian Flyway. However, lake reclamation and illegal human-made dykes have degraded the Dongting Lake wetland area at different degrees in the recent decades, seriously threatening the ecology of this area. In 2017, to restore the natural properties of Dongting Lake, the Chinese government completely demolished 459 dykes and preserved 14 dykes for various purposes (biodiversity conservation and flood control). However, the direct impact of dyke demolition on wintering waterbirds has not been comprehensively assessed. In this study, based on annual (2013/14–2020/21) waterbird census data, we compared the differences in species composition of waterbirds in the dyke-demolished and dyke-preserved areas. The results indicated that waterbird diversity, in terms of species number, abundance, the proportion of abundance, number of rare waterbirds species, and exclusive species, was higher in the dyke preserved areas than in the previously demolished areas. Species turnover and reordering further identified dynamic differences in the spatial and temporal distributions of waterbirds. Therefore, we used long-term habitat data to explore whether habitat changes were responsible for the changes in waterbirds; the results showed significantly decreased water and mudflat areas, but a significantly increased vegetation area in the dyke-demolished areas. The water area was significantly positively correlated with waterbirds in this habitat. Compared to the dyke-demolished areas, the stable and suitable habitat area in the dyke-preserved areas might be closely related to the higher waterbird diversity. Our study revealed habitat changes in the context of large-scale dyke demolition in Dongting Lake and demonstrated the dynamic response of waterbirds to habitat changes.

New Recorded of Saltwater Crocodile Crocodylus porosus Schneider, 1801 from East Coast Mangrove Ecosystem in Surabaya, East Jawa, Indonesia

A single specimen of saltwater crocodile Crocodylus porosus Schneider, 1801 (1.50 cm in length) was captured and photographed by a local fisherman by gill net at fishpond around mangrove ecosystem of east coast Surabaya on December 2020. The location where the estuarine crocodile caught is an important wetland area in Surabaya with an excellent mangrove cover. Wonorejo mangrove location is about 10 km from the centre of Surabaya, the second-largest city in Indonesia. This finding is considered as a first reported of C. porosus in Surabaya, and at the same time is proof of the importance of the mangrove area on the east coast of Surabaya as a habitat for wildlife that must be conserved appropriately. Routine monitoring of mangrove areas, including their wildlife, is essential so that they are not displaced by the development of the city which changes the land function to become a residential area.

POTENSI DARI EKSTRAK DAN FRAKSI KULIT BUAH MUNDAR (Garcinia forbesii) SEBAGAI TABIR SURYA BERDASARKAN NILAI SUN PROTECTION FACTOR (SPF)

UV rays cause skin damage such as loss of skin elasticity, wrinkles, sagging, and skin cancer. South Kalimantan is a wetland area with more than 4,000 species of medicinal plants. Mundar (Garcinia forbesii) is one of the plants in South Kalimantan. Mundar pericarp is empirically used for cosmetics which is believed to protect the skin from ultraviolet rays. The purpose of the study was to determine the sunscreen potency of the extract and fraction from pericarp of mundar (Garcinia forbesii) based on the Sun Protection Factor (SPF) parameter. The research started from material drying, making simplicia powder, extraction, and fractions. The extracts and fractions were measured for SPF values ??using a UV-Vis Spectrophotometer. The results showed that the ethanol extract and ethyl acetate fraction had weak protection, while the n-hexane fraction had extreme protective power with SPF values ??in the range of 6.51 – 30.00

A STUDY OF DIATOMS (BACILLARIOPHYTA) IN HOOR-AL-AZIM WETLAND, SOUTH-WEST IRAN, AND THEIR SEASONAL CHANGES

This study was aimed to identify the planktonic diatoms and their seasonal change in Hoor-AL-Azim wetlands, Iran. Diatoms are important algal groups in different aquatic ecosystem and considered as bioindicators for water quality and environmental health. Hoor-AL-Azim or Hoor-al-Hawizeh is one of the most extensive and ecologically important wetlands in the Middle East which is shared between Iran (south-west) and Iraq(south). A major part of the wetland area was exposed to drying completely or partially during last few decades due to two Country politics. The samples were taken on a monthly basis from four stations for year from January to end of December, for identification and seasonal changes of Diatoms (Bacillariophyta). In this study, totally 69 taxa belonging to 28 different genera were identified of which Nitzschia genus had the highest species diversity (13 species) and followed by Navicula genus (10 species) while the highest species diversity observed in autumn. The average density ranged from 4818 cells/ liter to 58625 cells /liter in spring and winter, respectively.