Spatio-Temporal Changes in Wildlife Habitat Quality in the Greater Serengeti Ecosystem

Wildlife habitat suitability analysis and mapping the former dhidhessa wildlife sanctuary using GIS-based analytical hierarchal process and weighted linear combination methods

Management of wildlife populations and the creation of conservation programs depend on the evaluation of wildlife habitats. Habitat suitability mapping is a technique typically used to map appropriate environmental factors and assess species existence in different areas. This study aims to map wildlife habitat suitability sites in Former Dhidhessa wildlife sanctuary, Ethiopia, using GIS-based Analytical Hierarchal Process and Weighted Linear Combination Methods. This study used both primary and secondary data sources. Datasets used to collect data include Digital Elevation Model (DEM), Landsat 9 (OLI/TIRS) and population data. Beside, large mammalian species occurrence data obtained from field survey was used. To map wildlife habitat suitability sites in Former Dhidhessa wildlife sanctuary, environmental factors such as proximity of road network, distance to surface water, land use land cover types, slope, population density and topography were used with the integration of species occurrence data recorded from the study area. These environmental factors scaled to common ranges, and assigned appropriate weights. The quantile classification method was utilized to classify suitability index into five zones (unsuitable, less suitable, moderately suitable, suitable, and highly suitable) to produce the map. Accordingly, the model revealed that 18.9 % of the study area is highly suitable, 19.5 % is suitable, 19.9 % is moderately suitable, 19.5 % is less suitable, and 22.2 % is unsuitable for wildlife. About 58.3 % of the study area is currently identified as suitable for wildlife whereas 41.7 % is unsuitable. This showed that the former Dhidhessa wildlife sanctuary is still having large suitable habitats that can support wide ranges of wildlife. Hence, based on the developed preliminary habitat suitability indices and maps, the federal and local governments shall reevaluate the status of former Dhidhessa wildlife sanctuary and develop future conservation and management plans to enhance the conservation of wildlife and their habitats in the area.

A meta-analysis of human disturbance effects on glucocorticoid hormones in free-ranging wild vertebrates

Free-ranging wild vertebrates need to cope with natural and anthropogenic stressors that cause short and/or long-term behavioural and physiological responses. In areas of high human disturbance, the use of glucocorticoid (GC) hormones as biomarkers to measure stress responses is an increasingly common tool for understanding how animals cope with human disturbance. We conducted a meta-analysis to investigate how human disturbances such as habitat conversion, habitat degradation, and ecotourism influence baseline GC hormones of free-ranging wild vertebrates, and we further test the role of protected areas in reducing the impact of such disturbances on these hormones. A total of 58 studies met the inclusion criteria, providing 152 data points for comparing levels of GC hormones under disturbed and undisturbed conditions. The overall effect size suggests that human disturbance does not cause a consistent increase in levels of GC hormones (Hedges' g = 0.307, 95% CI = -0.062 to 0.677). However, when the data were analysed by disturbance type, living in unprotected areas or in areas with habitat conversion were found to increase GC hormone levels compared to living in protected or undisturbed areas. By contrast, we found no evidence that ecotourism or habitat degradation generates a consistent increase in baseline GC hormone levels. Among taxonomic groups, mammals appeared more sensitive to human disturbance than birds. We advocate the use of GC hormones for inferring major human-caused contributors to the stress levels of free-ranging wild vertebrates - although such information needs to be combined with other measures of stress and interpreted in the context of an organism's life history, behaviour, and history of interactions with human disturbance.

The Change in Habitat Quality for the Yunnan Snub-Nosed Monkey from 1975 to 2022

The reduction in habitat quality (as shown, in part, by the increase in habitat rarity) is an important challenge when protecting the Yunnan snub-nosed monkey. We used the InVEST model to quantitatively analyze the dynamic changes in the habitat of the Yunnan snub-nosed monkey from 1975 to 2022. The results show that in the study period, the degree of habitat degradation increased, with the degradation range at its widest in the south, and the degradation intensity highest in the north, especially along a center "spine" area in the north. Over the latter part of the study period, the habitat quality of most monkey groups improved, which is conducive to the survival and reproduction of the population. However, the habitat quality and monkey populations are still at significant risk. The results provide the basis for formulating the protection of the Yunnan snub-nosed monkey and provide research cases for the protection of other endangered species.

Habitat quality assessment of wintering migratory birds in Poyang Lake National Nature Reserve based on InVEST model

Poyang Lake National Nature Reserve (PLNNR) is an important resting place for wintering migratory birds on the East Asian-Australasian Flyway (EAAF). In recent years, due to human activities and climate change, the area of wetlands has shown a downward trend, and the number and habitat of wintering migratory birds have been threatened. It is urgent to evaluate the habitat quality of wintering migratory birds in PLNNR. Therefore, the InVEST model and landscape index were used to evaluate the habitat quality of wintering migratory birds, and the grey correlation theory was used to reveal the response of typical wintering migratory bird population to habitat quality. The results showed that the habitat quality of the PLNNR was still at a high level, but showed a downward trend, with the average index of habitat quality decreasing from 0.872 to 0.817. The area of the highest quality habitat decreased by 3394.92 hm², the area of the lowest, low, and medium quality habitats increased by 3112.11 hm², and the area of the high quality habitat remained stable. The lowest, low, and medium quality habitat expanded from the middle to the south of the PLNNR mainly because of the expansion of construction land and cultivated land. The area with deterioration in habitat quality was 10,477.53 hm², mainly concentrated in the center and south of the PLNNR. The area with restoration in habitat quality was 6148.26 hm², mainly concentrated in the Bang Lake and Dacha Lake. The area with no change in habitat quality remained stable. The fragmentation degree and shape complexity of highest and high quality habitats increased, dominance degree and connectivity decreased, and the landscape pattern of habitat quality showed a downward trend. Typical wintering migratory birds have a strong correlation with highest, high, and low habitat quality, and there is a downward trend with the deterioration of habitat quality. Finally, this paper puts forward constructive suggestions on the degradation of habitat quality caused by land-use change.

Evolution of Habitat Quality and Its Response to Topographic Gradient Effect in a Karst Plateau: A Case Study of the Key Biodiversity Conservation Project Area of Wuling Mountains

Habitat quality (HQ) is widely considered to be a proxy indicator for biodiversity. Assessing the dynamic changes in HQ induced by land-use and land-cover (LULC) changes could provide a scientific perspective for regional sustainable development, especially in the ecologically fragile karst plateau mountainous areas. We selected nine landscape metrics to examine LULC dynamics in the Key Biodiversity Conservation Project Area of Wuling Mountains in Guizhou province, China, based on the land-use data for the 1990-2018 period. HQ was evaluated using the InVEST model and the topographic gradient effect on HQ was analyzed using the topographic position index. The results showed that the dominant land categories in the study area were arable land, grassland, and forestland. Land transformation was mainly characterized by a shift from cultivated land to construction land and forestland, and a mutual conversion between grassland and forestland. The changes improved landscape heterogeneity and the degree of fragmentation. The HQ of the study area was high, although exhibited a declining trend from 1990 to 2018. The eastern and western parts had relatively high HQ, whereas the southern and northern parts had low HQ. The topographic gradient had a significant effect on spatial patterns of HQ. High HQ distribution was consistent with that of forestland and was dominant along the topographic gradient, while low HQ distribution was consistent with that of construction land and cultivated land and was dominant along the topographic gradient.

Evolution of habitat quality and analysis of influencing factors in the Yellow River Delta Wetland from 1986 to 2020

The assessment of habitat quality plays an important role in the effective conservation of wetland biodiversity. The Yellow River Delta Wetland is located in the intertwining zone of sea, terrestrial, and river ecosystems, increasing human activities and climate change posed a great threat to wetland biodiversity. This study first analyzed the spatial and temporal evolution characteristics of habitat quality in the Yellow River Delta Wetland under the evolution of the shoreline after runoff-sediment variability (1986–2020) using the InVEST-habitat quality model and then identified the dominant influence factors on habitat quality based on Geographical Detector. Finally, elasticity index was introduced to analyze the impacts of different reclamation activities on habitat quality. Results showed that the habitat quality decreased from 0.4798 in 1986 to 0.4078 in 2020, with high values of habitat quality concentrated in mudflat wetlands and low values of habitat quality concentrated in construction land and salt pans. The results of the Geographical Detector analysis showed that the influence of human activities, especially reclamation activities, had stronger effects on habitat quality than climatic factors. The elasticity index analysis showed that the elasticity of all three types of reclamation activities, namely, culture ponds, construction land, and salt pans, were negative from 1986 to 2005, 2005 to 2020, and 1986 to 2020. The reclamation activities had a negative impact on habitat quality. The habitat quality of the Yellow River Delta Wetland was most sensitive to the change in reclamation intensity of construction land from 1986 to 2020, and the sensitivity of the change of habitat quality to the change of reclamation intensity of culture ponds and salt pans was strengthening. This study explicitly revealed the effect of climate change and human activities on the habitat quality of the Yellow River Delta Wetland and proposed to analyze the response intensity of habitat quality to different reclamation activities by using the elasticity index, thus providing a scientific basis for mitigating the tradeoff between biodiversity conservation and rapid social development in the Yellow River Delta Wetland in the future.

Assessing the Impact of Village Development on the Habitat Quality of Yunnan Snub-Nosed Monkeys Using the INVEST Model

Simple Summary

The Yunnan snub-nosed monkey is one of the most endangered species on the IUCN Red List. The study of its population and habitat quality is important in identifying opportunities for balancing socio-economic development against species conservation in the area’s villages. Such balances are important to protecting and improving habitat diversity and biodiversity. Our habitat quality analysis indicates that increases in socio-economic developments in the villages around the habitat area have decreased both the habitat area and the habitat quality over time. This has resulted in a decline in biodiversity persistence, resilience, and breadth. It also has exacerbated the risk of declining species populations, potentially to extinction. Though focused on the Yunnan snub-nosed monkey, our approach toward the assessment of habitat quality based on species habitat suitability introduces a new perspective for assessing village development impacts on the habitat quality for the conservation of other species.

Abstract

The habitats of the already endangered Yunnan snub-nosed monkey (Rhinopithecus bieti) are degrading as village economies develop in and around these habitat areas, increasing the depopulation and biodiversity risk of the monkey. The paper aims to show the areas of these monkeys’ high-quality habitats that are at highest risk of degradation by continued village development and hence be the focus of conservation efforts. Our analysis leveraged multiple tools, including primary component analysis, the InVEST Habitat-Quality model, and GIS spatial analysis. We enhanced our analysis by looking at habitat quality as it relates to the habitat suitability for the monkey specifically, instead of general habitat quality. We also focused on the impact of the smallest administrative scale in China—the village. These foci produced a clearer picture of the monkeys’ and villages’ situations, allowing for more targeted discussions on win–win solutions for both the monkeys and the village inhabitants. The results show that the northern habitat for the monkey is currently higher quality than the southern habitat, and correspondingly, the village development in the north is lower than in the south. Hence, we recommend conservation efforts be focused on the northern areas, though we also encourage the southern habitats to be protected from further degradation lest they degrade beyond the point of supporting any monkeys. We encourage developing a strategy that balances ecological protection and economic development in the northern region, a long-term plan for the southern region to reduce human disturbance, increase effective habitat restoration, and improve corridor design.

Multi-Scenario Simulation of Land Use and Habitat Quality in the Guanzhong Plain Urban Agglomeration, China

Regional habitat quality is a proxy of biodiversity. Simulating changes in land use and habitat quality in urban agglomerations is the scientific basis for promoting the optimal allocation of land resources and building ecological civilizations in urban agglomerations. Therefore, we established a research framework mainly consisting of the Future Land Use Simulation (FLUS) model with the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model to predict the spatial and temporal distribution of habitat quality. In addition, we set three scenarios which were a natural development scenario, a cultivated land protection scenario, and an ecological protection scenario to analyze the changes of habitat quality in the Guanzhong Plain urban agglomeration in 2035. The results showed that: (1) the FLUS model had an excellent effect on the simulation of land-use change in the Guanzhong Plain urban agglomeration, with an overall accuracy of 0.952 and a kappa coefficient of 0.924. (2) From 2000 to 2035, the cultivated land area of the study area, which was mainly transferred into construction land and grassland, shrank due to the process of urbanization. (3) The habitat quality score of this region gradually decreased from 2000 to 2020, and it continued to decrease to 0.6921 in 2035 under the natural development scenario, while it increased under the other two scenarios. The low-value areas of habitat quality were mainly located in the middle of this region with Xi’an as the core, whereas the high-value areas were mainly distributed in the southern Qinling Mountains and the northern Loess Plateau. (4) Of the different scenarios, the ecological protection scenario had the highest habitat quality, while the natural development scenario had the lowest. Besides this, we also found that the cultivated protection scenario had high habitat quality, which was mainly because the rate of occupation of ecological land was controlled. The results are expected to provide a scientific basis for optimizing the spatial allocation of land resources and promoting the sustainable use of land space in other ecologically fragile urban agglomerations.

Quantifying and Analyzing the Responses of Habitat Quality to Land Use Change in Guangdong Province, China over the Past 40 Years

Guangdong Province is an important ecological barrier and the primary pillar of economic development in China. Driven by high-speed urbanization and industrialization, unreasonable land use change in Guangdong Province has exacerbated habitat degradation and loss, seriously affecting habitat quality. Thus, taking Guangdong Province as the study area, this paper quantifies the response of habitat quality on land use change using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and constructs a contribution index (CI). The following conclusions can be drawn from the results: (1) The habitat quality exhibits a spatial distribution pattern of low quality in plain areas and high quality in hilly and mountainous areas. (2) The annual average habitat quality gradually decreases from 1980 to 2020, with a total decrease of 0.0351 and a reduction rate of 4.83%; (3) The impact of land use change on habitat quality is mainly negative, and the habitat quality mainly decreases by the conversion of forest land to orchards, paddy field to urban land, and forest land to dry land, with CI values of −24.09, −11.67, and −8.04, respectively. Preventing the destruction of natural forests, increasing the diversity of plantation orchards, and rationalizing and mitigating the growth rate of construction land are key to maintaining and improving the habitat quality.

Fusion of Sentinel-1 and Sentinel-2 data in mapping the impervious surfaces at city scale

Urbanization creates new development in open spaces and agricultural fields, synonymous with increasing impervious surfaces. Such surfaces restrain the natural infiltration of water, and directly affect the non-point source pollution. Thus, consequential events like flooding and surface water degradation require spatial and quantitative information on impervious surfaces. Remote sensing technologies are widely used in impervious surface mapping of various geographical locations for environmental monitoring. In this study, the datasets from recently launched European Space Agency satellites (Sentinel-1 and Sentinel-2) and random forest classifier are used. The impervious surface growth of the study area, Lahore city, in 2015 and 2021, and growth trends are assessed. Results are validated with classification accuracy and comparison with similar datasets. The objective is to develop a reliable impervious surface mapping method with land cover quantification technique from multisource datasets. With a chi-square value of greater than 3.84 obtained from the McNemar test, the performance of fused data was superior to that of optical alone data in the classification. Over a 5-year period, Lahore grew at an annual rate of 2.14% comparable to the findings of Copernicus Land Services and the Atlas of Urban Expansion with an underestimation of 1% and 8.75%, respectively. Improvements in overall accuracy (2.7%) and kappa coefficient (5%) were seen in classified maps from fused datasets. Fusion of Sentinel datasets provide a reliable means of impervious surface mapping at city scale as an indicator of environmental quality which is valuable for the sustainable management of the city.

Spatiotemporal Differentiation of Territorial Space Development Intensity and Its Habitat Quality Response in Northeast China

Studying the spatiotemporal distribution characteristics of territorial space development intensity (TSDI) and its habitat quality (HQ) response is of substantial theoretical and practical significance to optimize regional development patterns and coordinate the relationship between territorial space development and eco-environmental protection. This study establishes a comprehensive assessment model across various aspects, including land, population, economy, and input, to assess the TSDI of each county in Northeast China. We used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to evaluate the HQ of each county and investigated the HQ response to TSDI. The results showed that the TSDI in Northeast China was high in the south and west, low in the north and east, and prominent in urban agglomeration areas, which increased between 2000 and 2015. The spatial pattern of HQ was low in the east and south, high in the west and north, and the HQ was degraded as a whole. Bivariate spatial autocorrelation analysis showed a significant negative spatial correlation between TSDI and HQ, and distinct patterns of local spatial agglomeration were identified. Our findings provide guidelines for territorial space planning and may offer a reference for the ecological civilization construction and the coordinated development of Northeast China.

Study of habitat quality assessment using geospatial techniques in Keoladeo National Park, India

Wetlands are one of the most productive ecosystems on the Earth. They are generally considered a transitional state between terrestrial-aquatic habitats and provide numerous vital ecosystem services to mankind. Wetlands are under a tremendous pressure due to growing human interference, urbanization, conventional agriculture, industrial expansions, and overexploitation of ecological services. The Keoladeo National Park (KNP) is a manmade wetland, world heritage site and a designated Ramsar site in India, widely known for its avian biodiversity. Due to insufficient amount of water supply and widespread invasion of Prosopis juliflora, notable spatio-temporal changes are observed in the land cover affecting habitat quality of the park. The present study is designed to highlight the importance of very high-resolution satellite data for characterization of the wetland ecosystem. It assesses the spatio-temporal dynamics of land use/land cover (LULC) and habitat quality, a model built in the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) tool, is utilized to analyze the effect of land cover changes and increase in P. juliflora on habitat quality in the park. The study concludes that drastic changes in LULC and rampant spread of P. juliflora have deteriorated the quality of habitat for bird species. Furthermore, it highlights importance of geospatial tools in mapping, monitoring, and managing wetland ecosystems.

Integrating stakeholders' perspectives and spatial modelling to develop scenarios of future land use and land cover change in northern Tanzania

Rapid rates of land use and land cover change (LULCC) in eastern Africa and limited instances of genuinely equal partnerships involving scientists, communities and decision makers challenge the development of robust pathways toward future environmental and socioeconomic sustainability. We use a participatory modelling tool, Kesho, to assess the biophysical, socioeconomic, cultural and governance factors that influenced past (1959-1999) and present (2000-2018) LULCC in northern Tanzania and to simulate four scenarios of land cover change to the year 2030. Simulations of the scenarios used spatial modelling to integrate stakeholders' perceptions of future environmental change with social and environmental data on recent trends in LULCC. From stakeholders' perspectives, between 1959 and 2018, LULCC was influenced by climate variability, availability of natural resources, agriculture expansion, urbanization, tourism growth and legislation governing land access and natural resource management. Among other socio-environmental-political LULCC drivers, the stakeholders envisioned that from 2018 to 2030 LULCC will largely be influenced by land health, natural and economic capital, and political will in implementing land use plans and policies. The projected scenarios suggest that by 2030 agricultural land will have expanded by 8-20% under different scenarios and herbaceous vegetation and forest land cover will be reduced by 2.5-5% and 10-19% respectively. Stakeholder discussions further identified desirable futures in 2030 as those with improved infrastructure, restored degraded landscapes, effective wildlife conservation, and better farming techniques. The undesirable futures in 2030 were those characterized by land degradation, poverty, and cultural loss. Insights from our work identify the implications of future LULCC scenarios on wildlife and cultural conservation and in meeting the Sustainable Development Goals (SDGs) and targets by 2030. The Kesho approach capitalizes on knowledge exchanges among diverse stakeholders, and in the process promotes social learning, provides a sense of ownership of outputs generated, democratizes scientific understanding, and improves the quality and relevance of the outputs.

Measuring Multifunctional Agricultural Landscapes

Multifunctional agriculture (MFA) has attracted increased attention from academics and policymakers in recent years. Academic researchers have utilised various approaches to assess and measure the multifunctionality of agriculture and rural landscapes. This paper outlines the nature of MFA and key supporting policies, before reviewing the applied research approaches, drawing primarily from the European Union and China where specific policies on MFA have been implemented to support rural development and promote sustainable rural communities. Four distinct types of valuation of modern MFA are recognised: economic, biophysical, socio-cultural, and holistic. Following a search of both the recent and older MFA literature, evaluations of the strengths and weaknesses of quantitative, qualitative, and mixed methods applications are provided using examples from a range of recent studies. The review illustrates the diversity of approaches to measure MFA. While noting that many studies operate at a landscape scale, the challenge remains that the lack of commonality in the research approaches applied means it is difficult to provide effective comparisons between studies or to compare findings. A future research agenda will need to emphasise the need for more consideration of the roles of MFA research to support decision-makers, especially policy makers, but also farmers who largely make decisions for individual farms but, if considered collectively, can transform production systems at a landscape scale.