1. Introduction
The
Suaeda salsa (
S. salsa) community is a common vegetation in coastal wetland ecosystems, usually growing in the shallows near the coast, and is highly salt tolerant.
S. salsa is widely distributed in coastal and north-western China, Central Asia and Europe, and it has a role in improving the physical and chemical properties of soils, providing habitat for animals, coping with climate change and maintaining the ecological functions of wetlands [
1,
2,
3,
4,
5]. The Liao River Estuary National Nature Reserve in China is also home to a community of
S. salsa, which grows in April and May each year and turns from green to red in August and September, creating the famous ‘red beach’ landscape, which has become an important ecotourism resource for increasing revenue [
5].
However, from 1988 to 2009, the entire wetland has been in a state of degradation due to natural and human factors (e.g., aquaculture ponds and drought), especially the ‘red beach’ landscape consisting of the
S. salsa community, which not only constrains the development of the local tourism industry but also threatens the wetland’s ecological health [
6,
7]. Degradation also exists in other coastal wetlands in China, such as the Yellow Sea [
8]. In recent years, the shrinking of the “red beach” has received widespread attention from the government, and, in 2015, a wetland ecological restoration project was launched to restore the beach to its original state. However, there have been few reports on whether the degradation of the
S. salsa community has improved after the implementation of the project. Evaluating the degradation of the
S. salsa community objectively is of great importance for the scientific protection and management of the Liao River estuary wetland.
Researchers often develop models or frameworks to assess the ecosystem health of landscapes such as rivers, lakes and wetlands to provide a scientific reference. At present, the commonly used ecosystem evaluation models or frameworks include the Analytic Hierarchy Process (AHP) model [
9,
10,
11,
12], the comprehensive evaluation model based on entropy weight [
13,
14,
15] and the pressure state response (PSR) frameworks [
16,
17,
18]. The AHP method and entropy weighting method are mainly used to determine indicator weights [bai18]. Many studies have used the AHP method to determine the weights of individual indicators before constructing PSR models to assess ecosystem health, including many wetland types, such as plains [
19], river basins [
16], bays [
12], mangroves [
17] and so on. The health of wetlands can be easily assessed by PSR models, and the causes of wetland degradation can be identified as agricultural expansion or otherwise [
20]. Thus, the pressure state response evaluation model has the advantages of strong internal logical relationships and clear causal relationships, making it suitable for the study of
S. salsa community degradation in the Liao River estuary. In summary, previous studies found that PSR models can successfully assess wetland ecosystem health issues, but their application to coastal wetlands has been less common, especially for single vegetation species.
Accurate spatial and temporal distribution information about the
S. salsa community is required for degradation assessment. However, the environmental conditions of coastal wetlands are complex, and it is difficult to carry out a traditional field investigation. Remote sensing methods have the advantages of saving manpower, material resources and financial resources and are a more effective method for coastal area monitoring [
21,
22,
23,
24]. Sentinel-2 A and B satellite data, which were put into use in 2015 and 2017, have the advantages of high spatial resolution (10 m), a short revisit period (3 to 5 days), rich waveband, a large image coverage area and free access, and have broad application potential in wetland change research [
25,
26,
27]. There have been many successful cases of using Sentinel 2 satellite data to monitor or assess the condition of wetlands, e.g., Mahdianpari et al. [
28] used Sentinel-1 and Sentinel-2 data on the Google Earth Engine cloud computing platform to produce the first wetland inventory map of Newfoundland at a spatial resolution of 10 m. Chatzaintoniou et al. [
29] based on co-orbital Sentinel 1 and 2 using machine learning algorithms to map the land use/land change of wetlands in the Mediterranean Sea. Compared to MODIS and Landsat imagery data, the Sentinel series has richer spectral reflectance information and higher spatial resolution for more suitable and clear monitoring of surface changes in small-scale areas. Additionally, an application in classifying wetland land cover found that the machine learning algorithm random forest slightly outperformed support vector machines in concert with Sentinel 1 and 2 [
30]. Zhang et al. [
31] successfully classified wetland vegetation in the Yellow River estuary using a random forest classification model based on spatio-temporal spectral multidimensional features using Sentinel 2 data. Recently, Heimhuber et al. [
32] developed a new open-source Python toolkit for historical and near real-time monitoring of inlet wetlands using Landsat and Sentinel-2 images. Overall, Sentinel-2 is a high-quality source of satellite data and is increasingly valued in the assessment and monitoring of wetlands.
The objective of this study was to assess the health of S. salsa communities in the Liao River Estuary National Nature Reserve using the PSR model and Sentinel-2 satellite imagery. Firstly, the surface landscape evolution of the Liao River estuary wetlands is explored based on Sentinel-2 satellite imagery and an object-oriented random forest machine learning classification algorithm. Then, the PSR model was used to assess the health of the S. salsa community between 2016 and 2019 and to analyze the driving factors. The results provided a data basis and support for the scientific management and protection of wetland ecosystems in the Liao River Estuary National Nature Reserve.
4. Discussion
In order to bring back the “red beach” landscape and restore the environment suitable for the survival of S. salsa in the Liao River Estuary National Nature Reserve, Panjin City carried out a wetland restoration project of “returning the land to the beach” in 2015. However, according to the results of this study, the area of S. salsa communities in the Liao River estuary continued to decrease from 2016 to 2019, from 8.027 km2 to 3.115 km2, with a loss rate of 1.228 km2·year−1. Part of the original S. salsa community was converted to bare mudflats.
Since 1992, aquaculture ponds have been constructed by local residents within the reserve to increase economic income. Until 2015, the expansion of aquaculture was an important factor in the degradation of the
S. salsa community. Although no new aquaculture ponds were constructed after 2015, abandoned aquaculture ponds also remained in place. However, it is undeniable that the existing abandoned aquaculture ponds continue to have a negative impact on the survival of the
S. salsa community. This is because the
S. salsa community on the eastern side of the inlet near the aquaculture ponds is degrading faster than that on the western side. Another theory is that herbivorous crabs can adversely affect the growth of
S. salsa, but the source of crabs may be abandoned breeding ponds [
45].
S. salsa grows on both sides of the coastal tidal ditch or in the low-lying areas affected by the tide. Generally speaking, the main environmental factors affecting the growth of
S. salsa are soil salinity and water content [
46]. The self-regulation of
S. salsa allows it to generate a range of salinities, but, if the salinity is too low, it will not turn red and lose its tourist value, while, if the salinity is too high, it will directly lead to the death of
S. salsa [
47]. Some previous studies have suggested that human activities, including some economic activities such as land use changes, have led to the ecological degradation of coastal wetlands in China [
6,
48]. However, Li et al. [
49] used hydrodynamic modeling and statistical methods to find that limited tidal amplitude may be responsible for wetland degradation. The closure of the gates resulted in a low-flow water flow environment, where the evaporation of water and scarce freshwater recharge led to the deposition of soil salts in the upper layers of the mudflats. This may have contributed to the degradation of
S. salsa and coincides with the decrease in the hydrological regulation index in this study. Changes in tidal amplitude can also lead to changes in the shallow water table, which further leads to changes in the water content and salinity of the upper soil layer, thus affecting the health of the wetland vegetation [
50]. In summary, therefore, the degradation of
S. salsa communities may be caused by anthropogenic activities such as abandoned aquaculture ponds, sluice management systems and changes in water salinity from tidal amplitudes and exposed mudflats.
Environmental changes such as soil salinity due to sea level rise caused by climate change can also adversely affect saline vegetation in coastal wetlands [
51]. However, the shoreline of the mudflats in the Liao River estuary pushed toward the ocean from 2016 to 2019 is mainly influenced by the sediment carried by rivers [
52]. The change of beach area leads to the change of beach salinity and water content, which in turn affects the growth of
S. salsa. Therefore, sea level rise is not the main factor for the degradation of
S. salsa in the Liao River estuary, but the change of soil salinity due to climate change, which affects the vegetation, cannot be excluded [
53]. Another concern is the impact of tourism on the wetlands of the Liao River estuary, such as the construction of viewing corridors and garbage [
54].
The cultural and ecological services of the S. salsa community are mainly reflected in its tourism value, where its high landscape aesthetics bring ornamental value while creating a healthy mood among tourists and generating income for the government [
55]. Its ecosystem services are mainly in sand fixation and providing a good living environment for other organisms, such as birds and crabs. On balance, the over-exploitation of its cultural and ecological services can compromise its ecosystem services, so wetland managers need to be aware of this as a trade-off [
56].
The present study constructed an integrated health index to evaluate the health of
S. salsa communities based on the PSR model, which is similar to the study by Wang et al. [
17] in that both can assess the health of a single vegetation cover. However, the limitation of this study is the lack of measured soil water content and salinity data, especially in areas where
S. salsa community degradation occurs. However, as the mechanism of water and salt transport in the soil is clear, especially in areas with shallow groundwater depths, and salt in the surface soil is mainly influenced by capillary forces, it is generally feasible to construct a PSR model to assess the health of
S. salsa communities and to analyze the causes of their degradation.