Feedback of coastal marshes to climate change: Long‐term phenological shifts

Yu, Mei; Kearney, Michael; Turner, R. Eugene

doi:10.1002/ece3.5215

Cited by 14 publications

(8 citation statements)

References 77 publications

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“…Additionally, certain combinations of vegetation indices boost some crops' spectral traits while inhibiting others [16]. The wide use of RS imagery for monitoring land and environmental changes was proofed for soil sealing [17][18][19], human or natural factors that cause the loss of forests [20][21][22], effects of global warming [23,24], a wildfire's damage [25,26], and additional humanmade and natural dynamics. Particularly for SD investigations, which are frequently thought of as being over a lengthy period of time, data acquisition costs and time of coverage are the main limits of observation data such as SPOT [27,28] and Sentinel-2 [29,30].…”

Section: Introductionmentioning

confidence: 99%

Determining the Extent of Soil Degradation Processes Using Trend Analyses at a Regional Multispectral Scale

AbdelRahman

Metwalli

Gao

et al. 2023

Land

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In order to ensure the sustainability of production from agricultural lands, the degradation processes surrounding the fertile land environment must be monitored. Human-induced risk and status of soil degradation (SD) were assessed in the Northern-Eastern part of the Nile delta using trend analyses for years 2013 to 2023. SD hotspot areas were identified using time-series analysis of satellite-derived indices as a small fraction of the difference between the observed indices and the geostatistical analyses projected from the soil data. The method operated on the assumption that the negative trend of photosynthetic capacity of plants is an indicator of SD independently of climate variability. Combinations of soil, water, and vegetation’s indices were integrated to achieve the goals of the study. Thirteen soil profiles were dug in the hotspots areas. The soil was affected by salinity and alkalinity risks ranging from slight to strong, while compaction and waterlogging ranged from slight to moderate. According to the GIS-model results, 30% of the soils were subject to slight degradation threats, 50% were subject to strong risks, and 20% were subject to moderate risks. The primary human-caused sources of SD are excessive irrigation, poor conservation practices, improper utilisation of heavy machines, and insufficient drainage. Electrical conductivity (EC), exchangeable soil percentage (ESP), bulk density (BD), and water table depth were the main causes of SD in the area. Generally, chemical degradation risks were low, while physical risks were very high in the area. Trend analyses of remote sensing indices (RSI) proved to be effective and accurate tools to monitor environmental dynamic changes. Principal components analyses were used to compare and prioritise among the used RSI. RSI pixel-wise residual trend indicated SD areas were related to soil data. The spatial and temporal trends of the indices in the region followed the patterns of drought, salinity, soil moisture, and the difficulties in separating the impacts of drought and submerged on SD on vegetation photosynthetic capacity. Therefore, future studies of land degradation and desertification should proceed using indices as a factor predictor of SD analysis.

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Section: Introductionmentioning

confidence: 99%

Determining the Extent of Soil Degradation Processes Using Trend Analyses at a Regional Multispectral Scale

AbdelRahman

Metwalli

Gao

et al. 2023

Land

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“…The wetland area was estimated using the C version of the Function Mask (CFMask) with the Landsat CDRs. The overall accuracy of the CFMask to estimate the wetland area is 0.89 ± 0.04% (verified with the USGS Digital Orthophoto Quadrangle) (Mo et al ).…”

Section: Methodsmentioning

confidence: 84%

“…The first data set (Data 1) was primarily developed to measure seasonal changes in wetland greenness (revealing phenological changes; Mo et al ). We used 91 cloud‐free Landsat Climatic Data Records (CDRs) images (mosaics of Scenes of Path 22 Row 40 and Path 22 Row 39) collected from 1985 to 2014 to estimate the wetland area (range: 1–4 images/year).…”

Section: Methodsmentioning

confidence: 99%

“…The results from using the two data sets are classified herein as either land or water, but not wetland, because some pixels may be roads or structures, even though overwhelmingly composed of emergent wetland. The first data set (Data 1) was primarily developed to measure seasonal changes in wetland greenness (revealing phenological changes; Mo et al 2019). We used 91 cloud-free Landsat Climatic Data Records (CDRs) images (mosaics of Scenes of Path 22 Row 40 and Path 22 Row 39) collected from 1985 to 2014 to estimate the wetland area (range: 1-4 images/year).…”

Section: Satellite Imagerymentioning

confidence: 99%

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Net land gain or loss for two Mississippi River diversions: Caernarvon and Davis Pond

Turner

Layne

et al. 2019

Restoration Ecology

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Coastal wetland restoration can be complex and expensive, so knowing long‐term consequences makes it important to inform decisions about if, when, and where to conduct restoration. We determined temporal changes in land gain and loss in receiving basins and adjacent reference areas for two diversions of the Mississippi River in south Louisiana (Davis Pond and Caernarvon initiated in 1991 and 2002, respectively). Water from both diversions went into receiving basins with vegetated areas as did the adjoining reference areas. The results from two different types of satellite imagery analyses demonstrate a net land loss after diversions began. The results were confirmed for the Caernarvon diversion using a before–after/control–impact analysis of independently collected data over a larger area of the estuary. These results are consistent with an analysis of land gain and loss after a natural levee break on the Mississippi River in 1973. The positive influences of adding new sediments were apparently counter‐balanced by other factors, and consistent with the conclusion from other studies indicating that increased nutrient supply and flooding are, by themselves, negative influences on marsh health. Modeling the ecosystem effects of diversions can be calibrated and tested using landscape‐scale analyses like this to understand the chronic and delayed effects, including the unintended consequences. Basing the legitimacy of river diversion on ecosystem modeling will be premature without successfully reproducing empirical results like these in ecosystem models.

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“…The Landsat satellite imagery archive offers global coverage and continuous 16-day image collections dating back to 1984, which allows for multidecadal change analyses over large geographic areas (Kennedy et al, 2014;Pasquarella et al, 2016;Wulder et al, 2012;Young et al, 2017). Landsat has been used to monitor wetland habitat distributions and zonation (Bunting et al, 2018;Kearney et al, 2002;Rogers et al, 2017), identify disturbance events (Steyer et al, 2013), estimate biomass and carbon storage (Byrd et al, 2014(Byrd et al, , 2018Doughty et al, 2021;Klemas, 2013;Mo et al, 2018), and to identify patterns and drivers of wetland biomass, health, phenology, and greenness in coastal ecosystems (Brooke et al, 2017;Buffington et al, 2018;Cavanaugh et al, 2013Cavanaugh et al, , 2018Hamilton & Casey, 2016;Kearney et al, 2002;Mo et al, 2015Mo et al, , 2019O'Donnell & Schalles, 2016;Wu et al, 2017). Trends in wetland greening or browning revealed by satellite-based vegetation indices can help uncover long-term changes to biological (plant productivity and growth) and physical (cover composition) properties in vegetated ecosystems (Myers-Smith et al, 2020;Sulla-Menashe et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Climate drivers and human impacts shape 35‐year trends of coastal wetland health and composition in an urban region

Doughty,

Gu,

Ambrose

et al. 2024

Ecosphere

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The future of coastal wetlands will depend on the combined effects of climate change and human impacts from urbanization and coastal management. Disentangling the effects of these factors is difficult, but satellite imagery archives provide a way to track biological and physical changes in wetlands over recent decades to reveal how coastal wetlands have been changing in response to climate and human drivers. In this study, we used Landsat to monitor the conditions of 32 coastal wetlands in southern California from 1984 to 2019 and identify environmental and human drivers of these trends. Wetland conditions were characterized by vegetation greenness, using the normalized difference vegetation index (NDVI), and by habitat composition, derived from areal estimates of wetland and subtidal habitats. Overall, wetlands displayed three types of long‐term response: greening and gaining wetland (10), greening and losing wetland (16), and browning and losing wetland (6). Regional environmental drivers with overall positive effects on wetland NDVI were sea level, wave height, and precipitation, whereas stream discharge, vapor pressure deficit, and air temperature had negative or nonlinear effects. Wetland area change was primarily correlated with sea level, but response was highly contextual among sites. Negative trends in wetland NDVI and area were more common in larger sites with low elevations and in sites with open inlets. Restoration had mixed effects, with only half of the restored sites showing positive changes in NDVI and wetland area post‐restoration. The important work of managing and restoring urban coastal wetlands is complicated by variability and context and requires us to account for the influence of humans and climate as we build a regional understanding of historic, present, and future wetland health.

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Feedback of coastal marshes to climate change: Long‐term phenological shifts

Cited by 14 publications

References 77 publications

Determining the Extent of Soil Degradation Processes Using Trend Analyses at a Regional Multispectral Scale

Determining the Extent of Soil Degradation Processes Using Trend Analyses at a Regional Multispectral Scale

Net land gain or loss for two Mississippi River diversions: Caernarvon and Davis Pond

Climate drivers and human impacts shape 35‐year trends of coastal wetland health and composition in an urban region

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