Wetland Degradation and Ecological Restoration

Wetlands are among the most important ecosystems on earth and functioned as the “kidneys” of the earth, which play an important role in maintaining ecological service functions. However, with the rapid growth in human populations, wetlands worldwide are suffering from serious degradation or loss as affected by wetland pollution, wetland reclamation, civilization and land use changes, and so forth. Wetland degradation has potential influences on human health, biodiversity, regional climate, and regional ecological security. Therefore, it is an urgent task to recover these degraded wetlands. In recent years, wetland protection, restoration, and its reasonable exploitation have been paid much more attention to by most governments and researchers. Moreover, wetland restoration has become the frontier fields of wetlands science, which has been listed as one of important themes in these recent international wetlands and ecological conferences. Understanding wetland degradation processes can contribute to better effective wetland restoration. Therefore, we organized this special issue on “wetland degradation and ecological restoration.” The objective of this special issue is to emphasize the effects of human activities on wetland ecosystems, the relationships between soil, water, and plant in wetlands, and wetland restoration issues and applications

Spatiotemporally representative and cost-efficient sampling design for validation activities in wanglang experimental site

Altres ajuts: EC Copernicus Global Land Service (CGLOPS-1, 199494-JRC.Spatiotemporally representative Elementary Sampling Units (ESUs) are required for capturing the temporal variations in surface spatial heterogeneity through field measurements. Since inaccessibility often coexists with heterogeneity, a cost-efficient sampling design is mandatory. We proposed a sampling strategy to generate spatiotemporally representative and cost-efficient ESUs based on the conditioned Latin hypercube sampling scheme. The proposed strategy was constrained by multi-temporal Normalized Difference Vegetation Index (NDVI) imagery, and the ESUs were limited within a sampling feasible region established based on accessibility criteria. A novel criterion based on the Overlapping Area (OA) between the NDVI frequency distribution histogram from the sampled ESUs and that from the entire study area was used to assess the sampling efficiency. A case study inWanglang National Nature Reserve in China showed that the proposed strategy improves the spatiotemporally representativeness of sampling (mean annual OA = 74.7%) compared to the single-temporally constrained (OA = 68.7%) and the random sampling (OA = 63.1%) strategies. The introduction of the feasible region constraint significantly reduces in-situ labour-intensive characterization necessities at expenses of about 9% loss in the spatiotemporal representativeness of the sampling. Our study will support the validation activities in Wanglang experimental site providing a benchmark for locating the nodes of automatic observation systems (e.g., LAINet) which need a spatially distributed and temporally fixed sampling design

Intergenomic Rearrangements after Polyploidization of Kengyilia thoroldiana (Poaceae: Triticeae) Affected by Environmental Factors

Polyploidization is a major evolutionary process. Approximately 70–75% species of Triticeae (Poaceae) are polyploids, involving 23 genomes. To investigate intergenomic rearrangements after polyploidization of Triticeae species and to determine the effects of environmental factors on them, nine populations of a typical polyploid Triticeae species, Kengyilia thoroldiana (Keng) J.L.Yang et al. (2n = 6x = 42, StStPPYY), collected from different environments, were studied using genome in situ hybridization (GISH). We found that intergenomic rearrangements occurred between the relatively large P genome and the small genomes, St (8.15%) and Y (22.22%), in polyploid species via various types of translocations compared to their diploid progenitors. However, no translocation was found between the relatively small St and Y chromosomes. Environmental factors may affect rearrangements among the three genomes. Chromosome translocations were significantly more frequent in populations from cold alpine and grassland environments than in populations from valley and lake-basin habitats (P<0.05). The relationship between types of chromosome translocations and altitude was significant (r = 0.809, P<0.01). Intergenomic rearrangements associated with environmental factors and genetic differentiation of a single basic genome should be considered as equally important genetic processes during species' ecotype evolution

Comparative Analysis on Two Schemes for Synthesizing the High Temporal Landsat-like NDVI Dataset Based on the STARFM Algorithm

The NDVI dataset with high temporal and spatial resolution (HTSN) is significant for extracting information about the phenological change of vegetation in regions with a complex earth surface. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been successfully applied to synthesize the HTSN by fusing the data with different characteristics. Based on the model, there are two different schemes for synthesizing the HTSN. One scheme is that red reflectance and near-infrared (NIR) reflectance are synthesized, respectively, and the HTSN is then obtained through algebraic operation (Scheme 1); the other scheme is that the red and NIR reflectance are used to calculate NDVI, which is directly taken as input data to synthesize the HTSN (Scheme 2). In this paper, taking the hill areas in eastern Sichuan China as a case, the two schemes were compared with each other. Seven Landsat images and time-series MOD13Q1 datasets spanning from October 2001 to February 2003 were used as the test data. The results showed the prediction accuracies of both derived HTSNs by the two different schemes were generally in good agreement, and Scheme 2 was slightly superior to Scheme 1 (R2: 0.14 &lt; Scheme 1 &lt; 0.53; 0.15 &lt; Scheme 2 &lt; 0.53). Although the two HTSNs showed high temporal and spatial consistence, the small spatiotemporal difference between them had a different influence on different applications. The coincidence rate of cropping intensity extracted from two derived HTSNs was fairly high, reaching up to 93.86%, while the coincidence rate of crop peak dates (i.e., the emerging dates of peaks in an annual time-series NDVI curve) was only 70.95%. Therefore, it is deemed that Scheme 2 can replace Scheme 1 in the application of extracting cropping intensity, so that more calculation time and memory space can be saved. For extracting more quantitative crop phenological information like crop peak dates, more tests are still needed in order to compare the absolute accuracy for both schemes

A Quantitative Inspection on Spatio-Temporal Variation of Remote Sensing-Based Estimates of Land Surface Evapotranspiration in South Asia

Evapotranspiration (ET) plays a key role in water resource management. It is important to understand the ET spatio-temporal pattern of South Asia for understanding and anticipating serious water resource shortages. In this study, daily ET in 2008 was estimated over South Asia by using MODerate Resolution Imaging Spectroradiometer (MODIS) products combined with field observations and Global Land Data Assimilation System (GLDAS) product through Surface Energy Balance System (SEBS) model. Monthly ET data were calculated based on daily ET and evaluated by the GLDAS ET data. Good agreements were found between two datasets for winter months (October to February) with R2 from 0.5 to 0.7. Spatio-temporal analysis of ET was conducted. Ten specific sites with different land cover types at typical climate regions were selected to analyze the ET temporal change pattern, and the result indicated that the semi-arid or arid areas in the northwest had the lowest average daily ET (around 0.3 mm) with a big fluctuation in the monsoon season, while the sites in the Indo-Gangetic Plain and in southern India has bigger daily ET (more than 3 mm) due to a large water supplement. It is suggested that the monsoon climate has a large impact on ET spatio-temporal variation in the whole region

A Review on Land Surface Processes Modelling over Complex Terrain

Complex terrain, commonly represented by mountainous region, occupies nearly one-quarter of the Earth’s continental areas. An accurate understanding of water cycle, energy exchange, carbon cycle, and many other biogeophysical or biogeochemical processes in this area has become more and more important for climate change study. Due to the influences from complex topography and rapid variation in elevation, it is usually difficult for field measurements to capture the land-atmosphere interactions well, whereas land surface model (LSM) simulation provides a good alternative. A systematic review is introduced by pointing out the key issues for land surface processes simulation over complex terrain: (1) high spatial heterogeneity for land surface parameters in horizontal direction, (2) big variation of atmospheric forcing data in vertical direction related to elevation change, (3) scale effect on land surface parameterization in LSM, and (4) two-dimensional modelling which considers the gravity influence. Regarding these issues, it is promising for better simulation at this special region by involving higher spatial resolution atmospheric forcing data which can reflect the influences from topographic changes and making necessary improvements on model structure related to topographic factors. In addition, the incorporation of remote sensing techniques will significantly help to reduce uncertainties in model initialization, simulation, and validation

SGOT: A Simplified Geometric-Optical Model for Crown Scene Components Modeling over Rugged Terrain

Topography affects the fraction of scene components of the canopy and background, resulting in the observed reflectance distortion. Modeling the canopy reflectance over rugged terrain needs to account for topographic effects. For this purpose, the existing models greatly increased the mathematical complexity while improving description of terrain and crown structure, which dramatically decreased the computational efficiency so as to limit their universal application. In this study, we developed a simplified geometric-optical model (SGOT) for simulating the scene components over rugged terrain. The geotropism of tree growth was considered to make SGOT physically sound. The internal structure of crown was simplified to make SGOT mathematically simpler. Scene component observations derived from Persistence of Vision Ray-tracer (POV-Ray) on surfaces with different normal directions and simulations were made using Geometric-Optical and Mutual Shadowing Coupled with Topography Model (GOMST) and Geometric-Optical for Sloping Terrains Model GOST; models were combined to test the SGOT model. In addition, topographic factors and crown density effect on the scene components modeling were analyzed. The results indicated that SGOT has good accuracy (R2 for the areal proportions of sunlit crown (Kc), sunlit background (Kg), shaded crown (Kt), and shaded background (Kz) are 0.853, 0.857, 0.914, and 0.838, respectively) compared with POV-Ray simulation, and performs better than GOMST, especially in scenes with high crown density. Moreover, SGOT outperformed the compared models in computational efficiency (4% faster than GOMST and 29.5% faster than GOST). Finally, the simulations of the scene components distribution in different topographic factors and crown density were further discussed. SGOT and GOST can both capture scene component variations caused by terrain better than GOMST, but comparatively, SGOT provides a more efficient tool to simulate the crown scene components because of its physical soundness and mathematical simplicity, and consequently, it will facilitate the modeling of canopy reflectance over mountainous regions

How is the performance of satellite-based product suites in monitoring long-term dynamics of vegetation photosynthesis over global mountainous areas?

Monitoring the mountain vegetation photosynthesis is essential to understanding global climate change. Currently, several long-term satellite-based product suites have generated various variables associated with photosynthesis, while little is known about the consistency and accuracy of multiple variables in the same product suite. Here, the performances of three typical product suites during 2000–2018, namely Moderate-resolution Imaging Spectroradiometer (MODIS), Global LAnd Surface Satellite (GLASS), and Global Inventory Modeling and Mapping Studies (GIMMS), were assessed over global mountainous areas. Considering the limited in situ measurements over mountainous areas, high-quality solar-induced chlorophyll fluorescence (SIF) retrievals were adopted innovatively to evaluate multiple variables from different suites, and the consistencies of multiple variables in the same product suite were also assessed by investigating their concurrent extremes. Results illustrated that the combination of multiple variables from GLASS and MODIS tracked the dynamics of mountain vegetation photosynthesis well, with the relative root mean square error (rRMSE) of 41% and 44%, respectively. The concurrent extremes of GLASS matched better with the existing conclusions than those of MODIS, suggesting a better consistency of GLASS over mountainous areas. GLASS and MODIS presented a better ability (1) over flat areas than over mountainous areas (with a lower rRMSE of ∼5%) and (2) in vegetation types with obvious leaf phenology. Results also showed that GLASS leaf area index (LAI) had a better ability to track the dynamics of photosynthesis than GIMMS LAI. This work can provide essential references in modeling mountain vegetation photosynthesis based on satellite-based product suites

A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data

Soil moisture is a vital parameter in various land surface processes, and microwave remote sensing is widely used to estimate regional soil moisture. However, the application of the retrieved soil moisture data is restricted by its coarse spatial resolution. To overcome this weakness, many methods were proposed to downscale microwave soil moisture data. The traditional method is the microwave-optical/IR synergistic approach, in which land surface temperature (LST), vegetation index and surface albedo are key parameters. However, due to the uncertainty in absolute LST estimation, this approach is partly dependent on the accuracy of LST estimation. To eliminate the impacts of LST estimation, an improved downscaling method is proposed in this study to downscale Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) Land Parameter Retrieval Model (LPRM) soil moisture product with visible and thermal data of Meteosat Second Generation (MSG)—Spinning Enhanced Visible and Infrared Imager (SEVIRI). Two temperature temporal variation parameters related to soil moisture, including mid-morning rising rate and daily maximum temperature time, are introduced in the proposed method to replace LST. The proposed method and the traditional method are both applied to the Iberian Peninsula area for July and August 2007. Comparison of the two results shows that the coefficient of determination (R-squared) has an average improvement of 0.08 and the root mean square error has a systematic decrease. The downscaled soil moisture by the proposed method was validated by REMEDHUS soil moisture network in the study area, and site specific validation gets poor correlation between the two datasets because of the low spatial representativeness of site measurement for one MSG-SEVIRI pixel. Although the comparisons at 15 km and network scale show an improvement over the site specific comparison, it is found that the downscaling method systematically degrades the accuracy in soil moisture data, with a R-squared of 0–0.4 and 0.218 for the downscaled data set against 0.7–0.8 and 0.571 for AMSR-E data at 15 km scale and the network scale respectively