Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models

Zhao, Mingwei; He, Zhibin; Du, Jun; Chen, Longfei; Lin, Pengfei; Fang, Shu

doi:10.1016/j.ecolind.2018.10.052

Cited by 261 publications

(124 citation statements)

References 46 publications

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“…Throughout the urban expansion activities, unplanned LULC transformations have triggered many environmental consequences, specifically in the highly populous, small, developing countries [1]. For instance, the conversion of LULC to various settlements and agricultural purposes causes threats to several ecosystem services (ESs), for example, recreational opportunities [2], biodiversity and habitat quality [2], soil formation and nutrient cycling [4], climate regulation [2,5], erosion control [4,6], and water regulation [2,4]. The effect of these LULC alterations has resulted in the debasement of ESs, which are defined as the cumulative form of ecosystem goods and services, that benefit human life, from various ecosystem functions (e.g., provision, regulation, support, and culture) [7].…”

Section: Introductionmentioning

confidence: 99%

“…To this end, the modeling approach has become a useful tool to predict in what way land use could transform in the future under different land management scenarios [1]. Meanwhile, a large number of working models are available to simulate possible LULC change [5]. Among these models, CA-Markov (Cellular Automata -Markov), FLUS, CLUE-S (Conversion of Land Use and its Effects at Small regional extent), and LUSD (Land Use Scenario Dynamics) are most widely used for the simulation of LULC change [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, a large number of working models are available to simulate possible LULC change [5]. Among these models, CA-Markov (Cellular Automata -Markov), FLUS, CLUE-S (Conversion of Land Use and its Effects at Small regional extent), and LUSD (Land Use Scenario Dynamics) are most widely used for the simulation of LULC change [5,6]. However, it is important to note that linking among the various modeling techniques and developing a multidisciplinary model can produce a better output while simulating the LULC change dynamics [1].…”

Section: Introductionmentioning

confidence: 99%

“…In this research, we focused on monitoring the existing land use management and forecasting future LULC changes under different land management scenarios, to assess the effects of future LULC transformation on ESVs-an evaluation for which a CA-Markov model is indeed applicable [1,5]. It has been extensively mentioned in the ongoing research discussions that the CA-Markov model, along with a GIS (geographic information system) tool, performs best for demonstrating the likelihood of spatiotemporal conversion in LULC [5]. This model is considered as a hybrid model that has interlinked two sub-models: (i) Markov chain, and (ii) Cellular Automata (CA).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the CA-Markov model is considered as a suitable tool for simulating the spatiotemporal variation of LULC change. In addition, it has an outstanding capability to quantify policy proposals as a constraint, and socio-environmental and climatic factors as a factor, producing suitability maps [5].…”

Section: Introductionmentioning

confidence: 99%

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Future Impact of Land Use/Land Cover Changes on Ecosystem Services in the Lower Meghna River Estuary, Bangladesh

et al. 2020

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Assessing the effects of different land use scenarios on subsequent changes in ecosystem service has great implications for sustainable land management. Here, we designed four land use/land cover (LULC) scenarios, such as business-as-usual development (BAUD), economic development priority (EDP), ecological protection priority (EPP), and afforestation development priority (ADP), through a Cellular Automata-Markov (CA-Markov) model, and their effects on ecosystem service values (ESVs) were predicted, using historical LULC maps and ESV coefficients of the Lower Meghna River Estuary, Bangladesh. Findings revealed that agricultural and mangrove forest lands experienced the greatest decreases, while rural and urban settlement land had the greatest increases, leading to a total ESV decrease of US$105.34 million during 1988-2018. The scenario analysis indicated that ESV in 2038 would also decrease by US$41.37 million and US$16.38 million under the BAUD and EDP scenarios, respectively, while ESV will increase by US$60.61 million and US$130.95 million under the EPP and ADP scenarios, respectively. However, all the future land use scenarios will lead to 1.65%, 10.21%, 7.58%, and 6.75% gaps in total food requirements, respectively. Hence, from the perspective of maximizing ESVs and minimizing the trade-offs in food gaps, the ADP scenario could be the optimal land management policy for the studied landscape.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Future Impact of Land Use/Land Cover Changes on Ecosystem Services in the Lower Meghna River Estuary, Bangladesh

et al. 2020

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Changes in carbon stocks and its economic valuation under a changing land use pattern—A multitemporal study in Konar catchment, India

Rajbanshi

Das

2021

Land Degrad Dev

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Land use and land cover (LULC) changes influence the global terrestrial carbon pools and carbon sequestration processes to great extents. Therefore, the understanding of the soil carbon dynamics under the dire pressure of LULC changes is highly necessary. The subhumid tropical catchment of Konar, India, has endured immense LULC transitions over the years and this is likely to promote altered carbon exchanges with atmosphere and, thus, has a significant impact on climate regulation and ecosystem services. Our study analyzed the change in total carbon storage in the past (1992-2004 and 2004-2016) and predicted the future (2030) with respect to the changing land use scenario in the catchment. In addition, the monetary valuation of the carbon loss and/or gain in that area has been performed considering its economic value in the society. The Markov chain model was used in this work in order to predict the LULC map for the future period, and integrated valuation of ecosystem services and trade-offs (InVEST) model was applied to measure the changes in total carbon stocks. The results show that 129,273.75 Mg carbon has already been lost from 2004 to 2016 that is worth of $US 20.06 million ($US 212.69 ha À1 ), and another 66,050.25 Mg of carbon which is worth of $US 9.73 million ($US 103.21 ha À1 ) is expected to be lost in future by 2030. A thorough understanding of the carbon scenario of the study area may help to promote feasible mitigation actions to conserve the carbon pools.

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Projection of landscape ecological risk and exploration of terrain effects in the Qilian Mountains, China

et al. 2023

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The development of a reasonable landscape ecological risk (LER) assessment system is the key means to establish an eco‐safety early warning mechanism, promote ecological protection, and achieve sustainable management of regional ecosystems. Based on the Cellular Automaton‐Markov (CA‐Markov) model, we predicted the land use/cover changes (LUCC) in 2026 and 2034 in the typical arid and semiarid mountainous area of the Qilian Mountains. We constructed an LER model to analyze the spatial–temporal changes in LER, quantified the driving mechanism, and synthesized the constraining effect of terrain features. The results showed that the study area was dominated by ecologically stable areas in 1980–2000 and 2010–2018. Ecologically improved and deteriorated areas in the central and northwest expanded in 2000–2010 and 2018–2036, which was attributed to ecological restoration policies (returning farmland to forest and grassland, closing mountains to forest and grassland, etc.) and economic development (livestock and mineral development, etc.). Due to the frequent interference of human activities in flat and complex terrain areas, the degree of landscape fragmentation, separation, and vulnerability is enhanced, and the ecological conditions of bare land and snow cover are relatively fragile, resulting in high ecological risk. Therefore, we could focus on zoning management and rational land use planning. This study provides a new framework for controlling LER in the Qilian Mountains, and will provide a scientific reference for the formulation of risk mitigation strategies in other arid and semiarid mountains worldwide.

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Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models

Cited by 261 publications

References 46 publications

Future Impact of Land Use/Land Cover Changes on Ecosystem Services in the Lower Meghna River Estuary, Bangladesh

Future Impact of Land Use/Land Cover Changes on Ecosystem Services in the Lower Meghna River Estuary, Bangladesh

Changes in carbon stocks and its economic valuation under a changing land use pattern—A multitemporal study in Konar catchment, India

Projection of landscape ecological risk and exploration of terrain effects in the Qilian Mountains, China

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