scholarly journals Habitat Quality Valuation Using InVEST Model in Jeju Island

2015 ◽  
Vol 18 (5) ◽  
pp. 1-11 ◽  
Author(s):  
Teayeon Kim ◽  
Cholho Song ◽  
Woo-Kyun Lee ◽  
Moonil Kim ◽  
Chul-Hee Lim ◽  
...  
Keyword(s):  
Habitat Quality ◽  
Jeju Island ◽  
Invest Model

scholarly journals Conservation, Restoration, and Sustainable Use of Biodiversity Based on Habitat Quality Monitoring: A Case Study on Jeju Island, South Korea (1989–2019)

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 774
Author(s):  
Hyun-Jung Hong ◽  
Choong-Ki Kim ◽  
Hyun-Woo Lee ◽  
Woo-Kyun Lee
Keyword(s):  
South Korea ◽  
Habitat Quality ◽  
Sustainable Use ◽  
Habitat Type ◽  
Biodiversity Loss ◽  
Well Being ◽  
Jeju Island ◽  
Natural Habitats ◽  
Invest Model ◽  
Aichi Biodiversity Targets

Biodiversity loss is progressing despite biodiversity being essential for human survival, prosperity, and well-being. Conservation, restoration, and sustainable use of the habitat, given that its change is the most prominent factor causing the deterioration of biodiversity, represents a highly effective way of securing biodiversity. Therefore, we assessed and monitored habitat quality as a proxy for biodiversity with habitat quantity in Jeju Island, South Korea. We used an InVEST model with data on the habitat type, suitability, sensitivity, accessibility, and threat factors. Natural habitats throughout Jeju had rapidly decreased in area by 24.9% from 1989 to 2019, and this change contributed to the degradation of habitat quality by 15.8%. We provided significant evidence on the critical degradation of habitat for a long period of over 30 years and highlighted the urgent need for policies and behaviors that enhance biodiversity. We proposed appropriate strategies to prompt people to conserve better, restore effectively, and use biodiversity sustainably. We expect that our findings will provide scientific and evidence-based guidance for policy-making on biodiversity enhancement and will further support achievement of the Sustainable Development Goals and Aichi Biodiversity Targets, in addition to compliance with the New Deal for Nature and People.

scholarly journals Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island

2020 ◽  
Vol 12 (23) ◽  
pp. 10123
Author(s):  
Dong-jin Lee ◽  
Seong Woo Jeon
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Habitat Quality ◽  
Green Infrastructure ◽  
Roe Deer ◽  
Land Use Changes ◽  
Jeju Island ◽  
Invest Model ◽  
Integrated Valuation

This study predicts future land-use changes and the resulting changes in habitat quality, suggesting a method for establishing land-use management to ensure sustainable wildlife habitats. The conservation effects were verified in terms of wild animal habitat quality according to the designation of protected areas. Land-use change until 2050 was predicted using the Dyna-Conversion of Land Use Change and its effects (Dyna-CLUE) model for Jeju Island, Korea, and the change in the quality of roe deer habitats was predicted using the Integrated Valuation and Environmental Services and Tradeoffs (InVEST) model. Results indicate that, compared to 2030, urbanized area increased by 42.55 km2, farmland decreased by 81.36 km2, and natural area increased by 38.82 km2 by 2050. The average habitat quality on Jeju Island was predicted to decrease from 0.306 in 2030 to 0.303 in 2050. The average habitat quality ranged from 0.477 in 2030 to 0.476 in 2050 in protected areas and 0.281 in 2030 to 0.278 in 2050 outside protected areas. Habitat quality in protected areas was relatively high, and its reduction was limited. Areas with lower habitat quality need approaches such as expanding greenery and improving its quality. By establishing appropriate land-use plans by predicting habitat quality, wildlife habitats can be better maintained and protected, which is a primary goal of green infrastructure.

scholarly journals Multi-Scenario Analysis of Habitat Quality in the Yellow River Delta by Coupling FLUS with InVEST Model

2021 ◽  
Vol 18 (5) ◽  
pp. 2389
Author(s):  
Qinglong Ding ◽  
Yang Chen ◽  
Lingtong Bu ◽  
Yanmei Ye
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Habitat Quality ◽  
Scenario Analysis ◽  
Yellow River ◽  
The Yellow River ◽  
Cultivated Land ◽  
Invest Model ◽  
Unused Land ◽  
Dongying City

The past decades were witnessing unprecedented habitat degradation across the globe. It thus is of great significance to investigate the impacts of land use change on habitat quality in the context of rapid urbanization, particularly in developing countries. However, rare studies were conducted to predict the spatiotemporal distribution of habitat quality under multiple future land use scenarios. In this paper, we established a framework by coupling the future land use simulation (FLUS) model with the Intergrated Valuation of Environmental Services and Tradeoffs (InVEST) model. We then analyzed the habitat quality change in Dongying City in 2030 under four scenarios: business as usual (BAU), fast cultivated land expansion scenario (FCLE), ecological security scenario (ES) and sustainable development scenario (SD). We found that the land use change in Dongying City, driven by urbanization and agricultural reclamation, was mainly characterized by the transfer of cultivated land, construction land and unused land; the area of unused land was significantly reduced. While the habitat quality in Dongying City showed a degradative trend from 2009 to 2017, it will be improved from 2017 to 2030 under four scenarios. The high-quality habitat will be mainly distributed in the Yellow River Estuary and coastal areas, and the areas with low-quality habitat will be concentrated in the central and southern regions. Multi-scenario analysis shows that the SD will have the highest habitat quality, while the BAU scenario will have the lowest. It is interesting that the ES scenario fails to have the highest capacity to protect habitat quality, which may be related to the excessive saline alkali land. Appropriate reclamation of the unused land is conducive to cultivated land protection and food security, but also improving the habitat quality and giving play to the versatility and multidimensional value of the agricultural landscape. This shows that the SD of comprehensive coordination of urban development, agricultural development and ecological protection is an effective way to maintain the habitat quality and biodiversity.

scholarly journals Can Habitat Quality Index Measured Using the InVEST Model Explain Variations in Bird Diversity in an Urban Area?

2021 ◽  
Vol 13 (10) ◽  
pp. 5747
Author(s):  
Dehuan Li ◽  
Wei Sun ◽  
Fan Xia ◽  
Yixuan Yang ◽  
Yujing Xie
Keyword(s):  
Habitat Quality ◽  
Quality Index ◽  
Empirical Studies ◽  
Species Abundance ◽  
Diversity Indices ◽  
Local Scale ◽  
Data Availability ◽  
Bird Diversity ◽  
Invest Model ◽  
Trade Offs

Biodiversity maintenance is a crucial ecosystem service. Due to time limits and data availability, assessing biodiversity using indicators or models has become a hot topic in recent decades. However, whether some proposed indicators can explain biodiversity well at the local scale is still unclear. This study attempted to test whether the habitat quality index (HQI) as measured using the integrated valuation of ecosystem services and trade-offs (InVEST) model could explain variations in bird diversity in New Jiangwan Town, a rapidly urbanized region of Shanghai, China. The relationships from 2002 to 2013 among HQI and the two diversity indices, species richness and species abundance, were analyzed using Fisher’s exact test and gray correlation analysis. No significant association was found. Habitat connectivity was then integrated to develop a new combined indicator of habitat quality and connectivity index (HQCI). The associations between HQCI and the two diversity indices were improved significantly. The results indicated that connectivity may be an important factor explaining the diversity of certain species at a local scale. More empirical studies should be conducted to provide scientific evidence relating habitat quality to biodiversity.

Mapping and assessment of future land use change impacts on habitat quality in Lithuania

2021 ◽  
Author(s):  
Paulo Pereira ◽  
Eduardo Gomes ◽  
Miguel Inacio ◽  
Katarzyna Bogdzevič ◽  
Donalda Karnauskaite ◽  
...  
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Habitat Quality ◽  
Agricultural Intensification ◽  
Land Use Changes ◽  
Land Abandonment ◽  
Comparison Function ◽  
Invest Model ◽  
Landscape Degradation ◽  
Social Fund

<p><strong>Abstract</strong></p><p>Human activity is directly responsible for land use and land cover changes, affecting different ecosystem services. Thus, from the perspective of land use management is critical to project potential future land-use changes. This study aimed: (i) to detect possible changes in land-use structure in response to different four scenarios, namely: business as usual, urbanization, afforestation and land abandonment, and agricultural intensification scenario; and (ii) to measure the landscape habitat quality (an ecosystem services proxy) according to those projected futures. We selected as case study Lithuania due to the potential future increased human pressures on the landscape, and due to the high landscape value of this territory. The projected year was 2050, and we used the Cellular Automata method (applying the Dinamica EGO software) to project future land-use changes, and the InVEST model to assess the habitat quality. The land-use scenarios outcomes were validated using a fuzzy comparison function, and 80% of accuracy was achieved (comparing a simulated land use map of 2018, and the observed map for the same year). The results showed that the agricultural intensification scenario represents the greatest predicted landscape deterioration (from 0.71 in 2018 to 0.64). In the urbanization scenario, the highest landscape degradation prediction is identified around the most important cities (Vilnius, Kaunas, and Klaipėda). In the opposite direction, the afforestation and land abandonment scenario show the highest improvement on the habitat quality, from 0.71 in 2018 to 0.74. </p><p><strong>Acknowledgements</strong></p><p>“Lithuanian National Ecosystem Services Assessment and Mapping (LINESAM)” No. 09.3.3-LMT-K-712-01-0104 is funded by the European Social Fund according to the activity “Improvement of researchers’ qualification by implementing world-class R&D projects” of Measure No. 09.3.3-LMT-K-712.</p>

scholarly journals Evolution and Prediction of Landscape Pattern and Habitat Quality Based on CA-Markov and InVEST Model in Hubei Section of Three Gorges Reservoir Area (TGRA)

2018 ◽  
Vol 10 (11) ◽  
pp. 3854 ◽  
Author(s):  
Lin Chu ◽  
Tiancheng Sun ◽  
Tianwei Wang ◽  
Zhaoxia Li ◽  
Chongfa Cai
Keyword(s):  
Habitat Quality ◽  
Landscape Pattern ◽  
Quality Index ◽  
Three Gorges Reservoir ◽  
Habitat Degradation ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Invest Model ◽  
Pattern Dynamics ◽  
The Impact

The spatial pattern of landscape has great influence on the biodiversity provided by ecosystem. Understanding the impact of landscape pattern dynamics on habitat quality is significant in regional biodiversity conservation, ensuring ecological security guarantee, and maintaining the ecological environmental sustainability. Here, combining CA-Markov and InVEST model, we investigated the evolution of landscape pattern and habitat quality, and presented an explanation for variability of biodiversity linked to landscape pattern in Hubei section of Three Gorges Reservoir Area (TGRA). The spatial-temporal evolution characteristic of landscape pattern from 1990 to 2010 were analyzed by Markov chain. Then, the spatial pattern of habitat quality and its variation in three phases were computed by InVEST model. The driving force for landscape variation was explored by using Logistic regression analysis. Next, the CA-Markov model was used to simulate the future landscape pattern in 2020. Finally, future habitat quality maps were obtained by InVEST model predicted landscape maps. The results concluded that, the overall landscape pattern has changed slightly from 1990 to 2010. Woodland, waters and construction land had the greatest variations in proportion among the landscape types. The area of woodland has been decreasing gradually below the average elevation of 140 m, and the area of waters and construction land increased sharply. Logistics regression results indicated that terrain and climate were the most influencing natural factors compared with human factors. The Kappa coefficient reached 0.92, indicating that CA-Markov model had a good performance in future landscape prediction by adding nighttime light data as restriction factor. The biodiversity has been declining over the past 20 years due to the habitat degradation and landscape pattern variation. Overall, the maximum values of habitat degradation index were 0.1188, 0.1194 and 0.1195 respectively, showing a continuously increasing trend from 1990 to 2010. Main urban areas of Yichang city and its surrounding areas has higher habitat degradation index. The average values of habitat quality index of the whole region were 0.8563, 0.8529 and 0.8515 respectively, showing a continuously decreasing trend. The lower habitat quality index mainly located in the urban land as well as the main and tributary banks of the Yangtze River. Under the business as usual scenario, habitat quality continued to maintain the variation trend of the previous decade, showing a reducing habitat quality index and an increasing area of artificial surface. Under the ecological protection scenario, the variation of habitat quality in this scenario represented reverse trend to the previous decade, exhibiting an increase of habitat quality index and an increasing area of woodland and grassland. Construction of Three Gorges Dam, impoundment of Three Gorges Reservoir (TGR), resettlement of Three Gorges Project and urbanization were the most explanatory driving forces for landscape variation and degradation of habitat quality. The research may be useful for understanding the impact of landscape pattern dynamics on biodiversity, and provide scientific basis for optimizing regional natural environment, as well as effective decision-making support to local government for landscape planning and biodiversity conservation.

Sign in / Sign up

Export Citation Format

Share Document