The InVEST Habitat Quality Model Associated with Land Use/Cover Changes: A Qualitative Case Study of the Winike Watershed in the Omo-Gibe Basin, Southwest Ethiopia

Abstract

The contribution of biodiversity to the global economy, human survival, and welfare has been increasing significantly, but the anthropogenic pressure as a threat to the pristine habitat has followed. This study aims to identify habitat suitability, analyze the change in habitat quality from 1988 to 2018, and to investigate the correlation between impact factors and habitat quality. The InVEST habitat quality model was used to analyze the spatiotemporal change in habitat quality in individual land-use types in the Winike watershed. Remote sensing data were used to analyze the land use/land cover changes. Nine threat sources, their maximum distance of impact, mode of decay, and sensitivity to threats were also estimated for each land-use cover type. The analysis illustrates that habitat degradation in the watershed was continuously increasing over the last three decades (1988 to 2018). Each threat impact factor and habitat sensitivity have increased for the last 30 years. The most contributing factor of habitat degradation was the 25.41% agricultural expansion in 2018. Population density, land-use intensity, elevation, and slope were significantly correlated with the distribution of habitat quality. Habitat quality degradation in the watershed during the past three decades suggested that the conservation strategies applied in the watershed ecosystem were not effective. Therefore, this study helps decision makers, particularly regarding the lack of data on biodiversity. It further looks into the conflict between economic development and conservation of biodiversity.

Spatiotemporal Distribution of Zika Virus and Its Spatially Heterogeneous Relationship with the Environment

“…A higher habitat quality value indicates richer biodiversity, and richer biodiversity indicates higher habitat quality [ 29 ]. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST 3.8) model was used to calculate habitat quality by analyzing land cover and the degree of threat to biodiversity [ 30 ]. The formula for calculating habitat quality is as follows: where Q xj is the habitat quality index of landscape type j in grid unit x , H j is the habitat suitability score of landscape type j , z and k are constants, and D xj is the habitat degradation index, indicating the degree of degradation of a habitat after being stressed.…”

Habitat Degradation: A Comparative Study Between Tomar (PT) and Potenza (IT)

“…As regards the interpretation of final results, it should be noted that the linear overlap of the effects related to different threats has the disadvantage of neglecting a certainly non-linear interaction between different sources of impact which, acting simultaneously, can amplify the effects of the other. The proposed method, applicable to the different planning scales [ 40 , 41 ], provides a low-precision biodiversity indicator, but may provide a synthetic support for land-use assessment in terms of reducing the habitats quality [ 42 ]and may provide appropriate information on a land-use planning [ 43 ] and management system that ensures [ 44 ], among other quality objectives, the reduction of soil consumption, taking into account territorial characteristics and their ecosystem functionality, with a view to the conservation of biodiversity not considering natural processes as, for example, landslides [ 45 ]. As highlighted in previous works [ 46 – 49 ], the ecosystem services approach reveal to be particularly useful in supporting decision making and in designing conservation policies, but also in offering the possibility to use an effective monitoring tool of territorial transformation [ 35 ] and in overcoming a piecemeal structure of the normative framework [ 50 ].…”

Natura 2000 Areas and Sites of National Interest (SNI): Measuring (un)Integration between Naturalness Preservation and Environmental Remediation Policies

“…The habitat quality model, that belongs to the InVEST suite and is based on the hypothesis that a higher HQ corresponds to a higher abundance of species and vice versa [40,[42][43][44][45], draws up two maps: habitat quality (Q xj ) and degradation (D xj ).…”