Quantifying ecosystem service interactions to support environmental restoration in a tropical semi-arid basin

Abstract

Understanding the role of ecosystem services (ESs) within environmental management has become a critical issue of the twenty-first century. This is because scientific study of ES interactions can aid effective planning and management of ESs, thus curtailing degradation and enhancing restoration. In this study, ES interactions of the climate-sensitive West African Sokoto-Rima basin were quantified using land cover and a series of GIS-derived data as inputs into the InVEST model. Crop production (CP), seasonal water yield (SWY), habitat quality (HQ), and nutrient retention ratio (NRR) between 1992 and 2015 were assessed. Climate change assessment was based Mann-Kendall trend of precipitation and temperature for both past and future climates. The climate dynamics present a drying-warming trend with localised cooling-warming spells in some locations and a general future wetting-warming trend. Areas dominated by cropland and CP exert significant influence on the spatiotemporal dynamics of ES interactions contributing to the manifestation of substantial trade-offs and synergies across the past ( 2015) and the future ( 2050) climates. This also regulates the overbearing pattern of multiple ES interactions such that the relationship CP > SWY > HQ > EVI > NRR was observed over the study area. The persistence of these diverse relationships will stimulate the possible degradation of natural regulating ESs. Improvement of existing crop cultivation clusters, cultivation of flood-resistant crop varieties, and agroforestry expansion were proposed as climate and ESs interaction-based restoration measures. When adopted, these measures will douse the increasing ES pressures within this semi-arid zone. KeywordsEcosystem service interactions • InVEST model • Climate change • Ecological restoration • Sokoto-Rima basin * Saheed A. Raji

Forecast of policy‐driven land use change and its impact on ecosystem services in China: A case study of the Yangtze River Economic Belt

“…The land expansion analysis strategy (Raji et al, 2021) calculation formula is: $$${P}_{i,k}^{d}(x)=\frac{\sum _{n=1}^{M}I({h}_{n}(x)=d)}{M},$$$where $${k}$$ is the land use type; $$i$$ is a cell of $$k$$; $$M$$ is the total number of decision trees; $$x$$ is a vector composed of multiple driving factors; $$d$$ is 0 or 1 (1 means there are other land use types converted to $$k$$, 0 means none); $${P}_{i,k}^{d}$$ is the land expansion probability; $$I()$$ is the set of decision trees; and $${h}_{n}(x)$$ is the $$n$$ decision tree prediction type of vector $$x$$.…”

“…The random seed of cellular automata (CARS; Raji et al, 2021) calculation formula is: $$$O{P}_{i,k}^{1,t}=\left\{\begin{array}{cc}{p}_{i,k}^{1}\times (r\times {\mu }_{k})\times {D}_{k}^{t} & \text{if}{\,\Omega }_{i,k}^{t}=0\,\text{and}\,r\lt {p}_{i,k}^{1}\\ {p}_{i,k}^{1}\times {\Omega }_{i,k}^{t}\times {D}_{k}^{t} & \text{all ot}{\rm{h}}\text{ers},\end{array}\right.,$$$where $$t$$ is the threshold reduction value; r is a random value in the range of $$0\mbox{--}1$$; $${\mu }_{k}$$ is the threshold for producing patches of new land use types; $$O{P}_{i,k}^{1,t}$$ is the overall probability of land use; $${\Omega }_{i,k}^{t}$$ is the neighborhood effect of land use type $$k$$ in cell $$i$$; and $${D}_{k}^{t}$$ is the impact of future development demand of land use type $$k$$.…”

“…Land expansion analysis strategy. The land expansion analysis strategy (Raji et al, 2021) calculation formula is:…”

Study of Spatiotemporal Changes and Driving Factors of Habitat Quality: A Case Study of the Agro-Pastoral Ecotone in Northern Shaanxi, China

“…The habitat quality module needs data, including land-use type data, habitat threat factors, threat source factor weights, influence distances, and the landscape types' sensitivity to threat sources [16]. This study is based on the InVEST model manual [29] and on previous studies [30][31][32][33][34][35], combined with the actual situation of the study area to determine the relevant parameters and to design the habitat quality module input parameter table (Tables 3 and 4).…”

Water Conservation Ecological Service Function and Its Value Response Mechanism in a Nested Water Conservancy Project Area

“…The integrated valuation of ecosystem services and tradeoffs (InVEST) model has been widely used in water conservation services research. This model has been used in many regions, such as the Chindwin River Basin in Myanmar, the Portuguese Continental Basin, the Sokoto-Rima Basin in West Africa, Chile in South America, and the middle and lower reaches of the Yangtze River in China (Almeida and Cabral, 2021;Benra et al, 2021;Raji et al, 2021;Shrestha et al, 2021;Chen et al, 2022). This model can be used not only to evaluate the ecological service functions of different regions but also to predict the changes in ecological services by simulating different scenarios in order to identify the best scenario for sustainable regional development.…”