scholarly journals Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

2015 ◽  
Vol 7 (8) ◽  
pp. 10184-10226 ◽  
Author(s):  
Kevan Moffett ◽  
William Nardin ◽  
Sonia Silvestri ◽  
Chen Wang ◽  
Stijn Temmerman
Keyword(s):  
Remote Sensing ◽  
Coastal Wetlands ◽  
Stable States ◽  
Challenges And Opportunities ◽  
Multiple Stable States ◽  
Catastrophic Shifts

scholarly journals Population dynamics of synthetic Terraformation motifs

2016 ◽  
Author(s):  
Ricard V. Solé ◽  
Raúl Montañez ◽  
Salvador Duran Nebreda ◽  
Daniel Rodriguez-Amor ◽  
Blai Vidiella ◽  
...  
Keyword(s):  
Habitat Degradation ◽  
Ecological Engineering ◽  
Ecological Interactions ◽  
Stable States ◽  
Population Extinction ◽  
Intensive Exploitation ◽  
Engineering Designs ◽  
Synthetic Organisms ◽  
Multiple Stable States ◽  
Catastrophic Shifts

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation, and human-driven habitat degradation. Such threats are pushing ecosystems to the brink of collapse. Because of a general presence of multiple stable states, including states involving population extinction, and due to intrinsic nonlinearities associated with feedback loops, collapse can occur in a catastrophic manner. Such catastrophic shifts have been suggested to pervade many of the future transitions affecting ecosystems at many different scales. Many studies have tried to delineate potential warning signals predicting such ongoing shifts but little is known about how such transitions might be effectively prevented. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. Four classes of such ecological engineering designs orTerraformation motifshave been defined in a qualitative way. Here we develop the simplest mathematical models associated with these motifs, defining the expected stability conditions and domains where the motifs shall properly work.

Multiple Stable States and Catastrophic Shifts in Ecosystems

Ecology ◽  
2019 ◽  
Author(s):  
Sonia Kéfi
Keyword(s):  
Alternative Stable States ◽  
Direct Consequence ◽  
Theoretical Models ◽  
Economic Consequences ◽  
Design Management ◽  
Stable States ◽  
Natural Systems ◽  
Restoration Strategies ◽  
Multiple Stable States ◽  
Catastrophic Shifts

The idea that ecosystems may have multiple alternative stable states dates back to the late 1960s–early 1970s, when ecologists realized that this type of behavior could arise in simple mathematical models. A direct consequence is that such ecosystems can suddenly switch (or “tip”) between their alternative stable states rather than gradually responding to changes. In other terms, in these ecosystems, a small environmental perturbation can cause large, discontinuous, and irreversible changes, referred to as catastrophic shifts. This idea has attracted increasing interest in the literature over the years, and has become even more relevant in the current context of global change. Examples of catastrophic shifts in ecosystems include the eutrophication of shallow lakes, the desertification of drylands, and the degradation of coral reefs. Theoretical models have investigated the conditions under which alternative stable states and catastrophic shifts occur. A well-recognized cause of alternative stable states is the presence of strong positive—or self-reinforcing—feedback processes that maintain each of the stable ecosystem states. Understanding the mechanisms underlying the emergence of alternative stable states can help design management as well as restoration strategies for ecosystems. Because catastrophic shifts can have dramatic ecological and economic consequences, approaches have been proposed to detect possible alternative stable states in natural systems, and indicators of approaching ecosystem transitions have been identified (so-called early warning signals of critical slowing down).

scholarly journals Remote Sensing Methods for the Biophysical Characterization of Protected Areas Globally: Challenges and Opportunities

2021 ◽  
Vol 10 (6) ◽  
pp. 384
Author(s):  
Javier Martínez-López ◽  
Bastian Bertzky ◽  
Simon Willcock ◽  
Marine Robuchon ◽  
María Almagro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Global Scale ◽  
Area Network ◽  
Biophysical Characterization ◽  
Challenges And Opportunities ◽  
Scale Characterization

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

scholarly journals Remote-Sensing Monitoring of Tide Propagation Through Coastal Wetlands

Oceanography ◽  
2013 ◽  
Vol 26 (3) ◽  
pp. 64-69 ◽  
Author(s):  
Shimon Wdowinski ◽  
Sang-Hoon Hong ◽  
Amanda Mulcan ◽  
Brian Brisco
Keyword(s):  
Remote Sensing ◽  
Coastal Wetlands ◽  
Remote Sensing Monitoring ◽  
Tide Propagation

scholarly journals The importance of being coupled: Stable states and catastrophic shifts in tidal biomorphodynamics

2010 ◽  
Vol 115 (F4) ◽  
Author(s):  
Marco Marani ◽  
Andrea D'Alpaos ◽  
Stefano Lanzoni ◽  
Luca Carniello ◽  
Andrea Rinaldo
Keyword(s):  
Stable States ◽  
Catastrophic Shifts

Trapped liquid drop in a microchannel: Multiple stable states

2013 ◽  
Vol 87 (6) ◽  
Author(s):  
Zhengjia Wang ◽  
Cheng-Chung Chang ◽  
Siang-Jie Hong ◽  
Yu-Jane Sheng ◽  
Heng-Kwong Tsao
Keyword(s):  
Liquid Drop ◽  
Stable States ◽  
Multiple Stable States

Remote sensing of coastal wetlands and estuaries

2004 ◽  
Author(s):  
V. V. Klemas ◽  
R. T. Field ◽  
O. Weatherbee
Keyword(s):  
Remote Sensing ◽  
Coastal Wetlands

scholarly journals Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China

2021 ◽  
Vol 13 (20) ◽  
pp. 4106
Author(s):  
Shuai Wang ◽  
Mingyi Zhou ◽  
Qianlai Zhuang ◽  
Liping Guo
Keyword(s):  
Remote Sensing ◽  
Organic Carbon ◽  
Coastal Wetlands ◽  
Environmental Variables ◽  
Northeast China ◽  
Vegetation Index ◽  
Coastal Wetland ◽  
Wetland Ecosystems ◽  
Flat Terrain ◽  
Soc Density

Wetland ecosystems contain large amounts of soil organic carbon. Their natural environment is often both at the junction of land and water with good conditions for carbon sequestration. Therefore, the study of accurate prediction of soil organic carbon (SOC) density in coastal wetland ecosystems of flat terrain areas is the key to understanding their carbon cycling. This study used remote sensing data to study SOC density potentials of coastal wetland ecosystems in Northeast China. Eleven environmental variables including normalized difference vegetation index (NDVI), difference vegetation index (DVI), soil adjusted vegetation index (SAVI), renormalization difference vegetation index (RDVI), ratio vegetation index (RVI), topographic wetness index (TWI), elevation, slope aspect (SA), slope gradient (SG), mean annual temperature (MAT), and mean annual precipitation (MAP) were selected to predict SOC density. A total of 193 soil samples (0–30 cm) were divided into two parts, 70% of the sampling sites data were used to construct the boosted regression tree (BRT) model containing three different combinations of environmental variables, and the remaining 30% were used to test the predictive performance of the model. The results show that the full variable model is better than the other two models. Adding remote sensing-related variables significantly improved the model prediction. This study revealed that SAVI, NDVI and DVI were the main environmental factors affecting the spatial variation of topsoil SOC density of coastal wetlands in flat terrain areas. The mean (±SD) SOC density of full variable models was 18.78 (±1.95) kg m−2, which gradually decreased from northeast to southwest. We suggest that remote sensing-related environmental variables should be selected as the main environmental variables when predicting topsoil SOC density of coastal wetland ecosystems in flat terrain areas. Accurate prediction of topsoil SOC density distribution will help to formulate soil management policies and enhance soil carbon sequestration.

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