Vegetation Dynamic in a Large Floodplain Wetland: The Effects of Hydroclimatic Regime
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Site
2.2. Data Sources and Preparation
2.3. Habitat Type
2.4. Predictor Variables and Pre-Processing
2.5. Random Forest Models for Wetland Habitat Classification
2.6. Wetland Habitat Dynamics during 1989–2021
2.7. Drivers of Wetland Vegetation Dynamics
3. Results
3.1. Model Accuracy Assessment
3.2. Spatial Extent of Habitat Transitions
3.3. Drivers of Vegetation Development in East Dongting Lake
4. Discussion
4.1. Overall Evaluation of Mapping Approach
4.2. Drivers of Wetland Vegetation Dynamics
4.2.1. Reedbed Is Highly Persistent and Has Rapidly Expanded during the Study Period
4.2.2. Carex Meadow Has No Trend and Fluctuates with the Changes in Flow Regime
4.2.3. Mudflat Is the Most Vulnerable Habitat
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
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Name | Relevance | Formula | Reference |
---|---|---|---|
NDVI (normalized difference vegetation index) | NDVI measures photosynthetically active biomass in plants. It is the most highly used index to monitor plant development dynamics. | [70] | |
NDWI (normalized difference water index) | NDWI detects open water features. | [71] | |
PSRI (plant senescence reflectance index) | PSRI is sensitive to the ratio of carotenoids to chlorophyll in plants, indicating the process of vegetation senescence. | [72] | |
SAVI (soil adjusted vegetation index) | SAVI is used to mitigate the impact of soil brightness to correct NDVI in areas where vegetative cover is low. | [73] | |
GNDVI (green normalized difference vegetation index) | GNDVI is a modification of NDVI to detect wilted or aging plants and to measure nitrogen content in leaves. It is suitable to monitor vegetation with dense canopies or at different maturity stages. | [74] | |
BSI (bare soil index) | BSI is used to differentiate bare soil and other land cover types. Due to the high contrast between bare soil and vegetation, BSI provides a continuum ranging from high vegetation cover to exposed soil. | [75] | |
NDPI (normalized difference phenology index) | NDPI improves the spring greening-up phenology monitoring capacity in snow-contaminated or low vegetation cover areas. | [76] |
Class | Meadow | Mudflat | Reed | Water | Sum | PA (%) |
---|---|---|---|---|---|---|
Meadow | 147 | 8 | 0 | 0 | 155 | 94.8 |
Mudflat | 8 | 55 | 0 | 0 | 63 | 87.3 |
Reed | 0 | 0 | 299 | 0 | 299 | 100 |
Water | 2 | 14 | 0 | 203 | 219 | 92.7 |
Sum | 157 | 77 | 299 | 203 | 736 | |
UA (%) | 93.6 | 71.4 | 100 | 100 | 95.7 (OA) |
Meadow | Mudflat | Reed | Water | Persistence | Gain | Loss | NC | SC | TC | P/T | G/P | L/P | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Meadow | 29.64 | 8.17 | 0.98 | 0.96 | 29.64 | 10.11 | 5.76 | 4.35 | 11.53 | 15.88 | 0.84 | 0.34 | 0.19 |
Mudflat | 1.56 | 12.30 | 0.24 | 4.31 | 12.30 | 6.12 | 16.27 | −10.15 | 12.23 | 22.38 | 0.43 | 0.50 | 1.32 |
Reed | 2.81 | 1.39 | 7.10 | 0.23 | 7.10 | 4.43 | 1.31 | 3.12 | 2.62 | 5.74 | 0.84 | 0.62 | 0.18 |
Water | 1.39 | 6.70 | 0.09 | 22.12 | 22.12 | 8.18 | 5.50 | 2.68 | 11.00 | 13.68 | 0.80 | 0.37 | 0.25 |
Duration Model | Date Model | ||||||||
---|---|---|---|---|---|---|---|---|---|
Parametric Term | Est. | SE | z-Value | p * | Est. | SE | z-Value | p | |
Intercept | −1.264 | 0.453 | −2.793 | 0.005 | Intercept | −2.005 | 0.491 | −4.088 | 0.000 |
DOD | −0.001 | 0.001 | −2.185 | 0.029 | DOYD | 0.002 | 0.001 | 2.464 | 0.014 |
Smooth term | edf | Ref.df | Chi.sq | p | edf | Ref.df | Chi.sq | p | |
s(Year): Meadow # | 0.000 | 9 | 0.000 | 0.690 | s(Year): Meadow | 0.000 | 9 | 0.000 | 0.730 |
s(Year): Mudflat | 2.140 | 9 | 58.778 | 0.000 | s(Year): Mudflat | 2.110 | 9 | 55.954 | 0.000 |
s(Year): Reed | 0.844 | 9 | 6.633 | 0.010 | s(Year): Reed | 0.857 | 9 | 7.368 | 0.008 |
s(Hab) | 1.999 | 2 | 4895.312 | 0.000 | s(Hab) | 1.999 | 2 | 4859.347 | 0.000 |
s(DOD): Meadow | 1.759 | 9 | 11.336 | 0.000 | s(DOYD): Meadow | 0.915 | 9 | 11.851 | 0.000 |
s(DOD): Mudflat | 1.342 | 9 | 3.263 | 0.068 | s(DOYD): Mudflat | 1.774 | 9 | 7.512 | 0.010 |
s(DOD): Reed | 0.000 | 9 | 0.000 | 0.465 | s(DOYD): Reed | 0.000 | 9 | 0.000 | 0.302 |
s(Rain): Meadow | 1.161 | 9 | 2.514 | 0.108 | s(Rain): Meadow | 0.592 | 9 | 0.809 | 0.239 |
s(Rain): Mudflat | 1.795 | 9 | 17.702 | 0.000 | s(Rain): Mudflat | 1.743 | 9 | 16.902 | 0.000 |
s(Rain): Reed | 2.184 | 9 | 15.608 | 0.001 | s(Rain): Reed | 1.993 | 9 | 10.801 | 0.004 |
R2 (adj) | 0.984 | R2 (adj) | 0.984 |
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Jing, L.; Zeng, Q.; He, K.; Liu, P.; Fan, R.; Lu, W.; Lei, G.; Lu, C.; Wen, L. Vegetation Dynamic in a Large Floodplain Wetland: The Effects of Hydroclimatic Regime. Remote Sens. 2023, 15, 2614. https://doi.org/10.3390/rs15102614
Jing L, Zeng Q, He K, Liu P, Fan R, Lu W, Lei G, Lu C, Wen L. Vegetation Dynamic in a Large Floodplain Wetland: The Effects of Hydroclimatic Regime. Remote Sensing. 2023; 15(10):2614. https://doi.org/10.3390/rs15102614
Chicago/Turabian StyleJing, Lei, Qing Zeng, Ke He, Peizhong Liu, Rong Fan, Weizhi Lu, Guangchun Lei, Cai Lu, and Li Wen. 2023. "Vegetation Dynamic in a Large Floodplain Wetland: The Effects of Hydroclimatic Regime" Remote Sensing 15, no. 10: 2614. https://doi.org/10.3390/rs15102614