Examining the effects of green revolution led agricultural expansion on net ecosystem service values in India using multiple valuation approaches.

Ecosystem Services (ESs) are bundles of natural processes and functions that are essential for human well-being, subsistence, and livelihoods. The 'Green Revolution' (GR) has substantial impact on the agricultural landscape and ESs in India. However, the effects of GR on ESs have not been adequately documented and analyzed. This leads to the main hypothesis of this work - 'the incremental trend of ESs in India is mainly prompted by GR led agricultural innovations that took place during 1960 - 1970'. The analysis was carried out through five successive steps. First, the spatiotemporal Ecosystem Service Values (ESVs) in Billion US$ for 1985, 1995, and 2005 were estimated using several value transfer approaches. Second, the sensitivity and elasticity of different ESs to land conversion were carried out using coefficient of sensitivity and coefficient of elasticity. Third, the Geographically Weighted Regression model was performed using five explanatory factors, i.e., total crop area, crop production, crop yield, net irrigated area, and cropping intensity, to explore the cumulative and individual effects of these driving factors on ESVs. Fourth, Multi-Layer Perceptron based Artificial Neural Network was employed to estimate the normalized importance of these explanatory factors. Fifth, simple and multiple linear regression modeling was done to assess the linear associations between the driving factors and the ESs. During the observation periods, cropland, forestland and water bodies contributed to 80%-90% of ESVs, followed by grassland, mangrove, wetland and urban built-up. In all three evaluation years, the highest estimated ESVs among the nine ES categories was provided by water regulation, followed by soil formation and soil-water retention, biodiversity maintenance, waste treatment, climate regulation, and greenhouse gas regulation. Among the five explanatory factors, total crop area, crop production, and net irrigated area showed strong positive associations with ESVs, while cropping intensity exhibited a negative association. Therefore, the study reveals a strong association between GR led agricultural expansion and ESVs in India. This study suggests that there should be an urgent need for formulation of rigorous ecosystem management strategies and policies to preserve ecological integrity and flow of uninterrupted ESs and to sustain human well-being.

Identification of Conservation Priority Zones Using Spatially Explicit Valued Ecosystem Services: A Case from the Indian Sundarbans.

Demarcation of conservation priority zones (CPZs) using spatially explicit models is the new challenge in ecosystem services (ESs) research. This study identifies the CPZs of the Indian Sundarbans by integrating 2 different approaches, that is, ESs and ecosystem health (EH). Five successive steps were followed to conduct the analysis: First, the ESs were estimated using biophysical and economic methods and a hybrid method (that combines biophysical and economic methods); second, the vigor-organization-resilience (VOR) model was used for estimating EH; third, the risk characterization value (RCV) of ESs was measured using the function of EH and ESs; fourth, Pearson correlation test was performed to analyze the interaction between ESs and EH components; and fifth, the CPZs were defined by considering 7 relevant components: ecosystem vigor, ecosystem organization, ecosystem resilience, RCV, EH, ESs, and the correlation between EH and ESs. Among the major ecoregions of the Sundarbans, the highest ESs value in economic terms is provided by the mangrove ecosystem (US$19 144.9 million per year). The highest conservation priority score was projected for the Gosaba block, which is dominated by dense mangrove forests. The estimated CPZs were found to be highly consistent with the existing biodiversity zonations. The outcome of this study could be a reference for environmentalists, land administrators, researchers, and decision makers to design relevant policies to protect the high values of the Sundarbans ecosystem. Integr Environ Assess Manag 2020;16:773-787. © 2020 SETAC.

Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem.

Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India. We carry out the analysis following five successive steps: (1) quantifying biophysical and economic values of ESs using three valuation approaches; (2) identifying six major driving forces on ESs; (3) categorizing principal data components with dimensionality reduction; (4) constructing multivariate regression models with variance partitioning; (5) implementing six spatial regression models to examine the causal effects of natural and anthropogenic forcings on ESs. Results show that climatic factors, biophysical factors, and environmental stressors significantly affect the ESs. Among the six driving factors, climate factors are highly associated with the ESs variation and explain the maximum model variances (R2 = 0.75-0.81). Socioeconomic (R2 = 0.44-0.66) and development (R2 = 27-0.44) factors have weak to moderate effects on the ESs. Furthermore, the joint effects of the driving factors are much higher than their individual effects. Among the six spatial regression models, Geographical Weighted Regression (GWR) performs the most accurately and explains the maximum model variances. The proposed hybrid valuation method aggregates biophysical and economic estimates of ESs and addresses methodological biases existing in the valuation process. The presented framework can be generalized and applied to other ecosystems at different scales. The outcome of this study could be a reference for decision-makers, planners, land administrators in formulating a suitable action plan and adopting relevant management practices to improve the overall socio-ecological status of the region.

Ecosystem service value assessment of a natural reserve region for strengthening protection and conservation.

Ecosystem Services (ESs) refer to the direct and indirect contributions of ecosystems to human well-being and subsistence. Ecosystem valuation is an approach to assign monetary values to an ecosystem and its key ecosystem goods and services, generally referred to as Ecosystem Service Value (ESV). We have measured spatiotemporal ESV of 17 key ESs of Sundarbans Biosphere Reserve (SBR) in India using temporal remote sensing (RS) data (for years 1973, 1988, 2003, 2013, and 2018). These mangrove ecosystems are crucial for providing valuable supporting, regulatory, provisioning, and cultural ecosystem services. We have adopted supervised machine learning algorithms for classifying the region into different ecosystem units. Among the used machine learning models, Support Vector Machine (SVM) and Random Forest (RF) algorithms performed the most accurate and produced the best classification estimates with maximum kappa and an overall accuracy value. The maximum ESV (derived from both adjusted and non-adjusted units, million US$ year-1) is produced by mangrove forest, followed by the coastal estuary, cropland, inland wetland, mixed vegetation, and finally urban land. Out of all the ESs, the waste treatment (WT) service is the dominant ecosystem service of SBR. Additionally, the mangrove ecosystem was found to be the most sensitive to land use and land cover changes. The synergy and trade-offs between the ESs are closely associated with the spatial extent. Therefore, accurate estimates of ES valuation and mapping can be a robust tool for assessing the effects of poor decision making and overexploitation of natural resources on ESs.

Is Decoupling GDP Growth from Environmental Impact Possible?

The argument that human society can decouple economic growth-defined as growth in Gross Domestic Product (GDP)-from growth in environmental impacts is appealing. If such decoupling is possible, it means that GDP growth is a sustainable societal goal. Here we show that the decoupling concept can be interpreted using an easily understood model of economic growth and environmental impact. The simple model is compared to historical data and modelled projections to demonstrate that growth in GDP ultimately cannot be decoupled from growth in material and energy use. It is therefore misleading to develop growth-oriented policy around the expectation that decoupling is possible. We also note that GDP is increasingly seen as a poor proxy for societal wellbeing. GDP growth is therefore a questionable societal goal. Society can sustainably improve wellbeing, including the wellbeing of its natural assets, but only by discarding GDP growth as the goal in favor of more comprehensive measures of societal wellbeing.

Accounting for "land-grabbing" from a biocapacity viewpoint.

The comparison of the Ecological Footprint and its counterpart (i.e. biocapacity) allow for a classification of the world's countries as ecological creditors (Ecological Footprint lower than biocapacity) or debtors (Ecological Footprint higher than biocapacity). This classification is a national scale assessment on an annual time scale that provides a view of the ecological assets appropriated by the local population versus the natural ecological endowment of a country. We show that GDP per capita over a certain threshold is related with the worsening of the footprint balance in countries classified as ecological debtors. On the other hand, this correlation is lost when ecological creditor nations are considered. There is evidence that governments and investors from high GDP countries are playing a crucial role in impacting the environment at the global scale which is significantly affecting the geography of sustainability and preventing equal opportunities for development. In particular, international market dynamics and the concentration of economic power facilitate the transfer of biocapacity related to "land grabbing", i.e. large scale acquisition of agricultural land. This transfer mainly occurs from low to high GDP countries, regardless of the actual need of foreign biocapacity, as expressed by the national footprint balance. A first estimation of the amount of biocapacity involved in this phenomenon is provided in this paper in order to better understand its implications on global sustainability and national and international land use policy.

Temperature and population density determine reservoir regions of seasonal persistence in highland malaria.

A better understanding of malaria persistence in highly seasonal environments such as highlands and desert fringes requires identifying the factors behind the spatial reservoir of the pathogen in the low season. In these 'unstable' malaria regions, such reservoirs play a critical role by allowing persistence during the low transmission season and therefore, between seasonal outbreaks. In the highlands of East Africa, the most populated epidemic regions in Africa, temperature is expected to be intimately connected to where in space the disease is able to persist because of pronounced altitudinal gradients. Here, we explore other environmental and demographic factors that may contribute to malaria's highland reservoir. We use an extensive spatio-temporal dataset of confirmed monthly Plasmodium falciparum cases from 1995 to 2005 that finely resolves space in an Ethiopian highland. With a Bayesian approach for parameter estimation and a generalized linear mixed model that includes a spatially structured random effect, we demonstrate that population density is important to disease persistence during the low transmission season. This population effect is not accounted for in typical models for the transmission dynamics of the disease, but is consistent in part with a more complex functional form of the force of infection proposed by theory for vector-borne infections, only during the low season as we discuss. As malaria risk usually decreases in more urban environments with increased human densities, the opposite counterintuitive finding identifies novel control targets during the low transmission season in African highlands.

A thermodynamic geography: night-time satellite imagery as a proxy measure of emergy.

Night-time satellite imagery enables the measurement, visualization, and mapping of energy consumption in an area. In this paper, an index of the "sum of lights" as observed by night-time satellite imagery within national boundaries is compared with the emergy of the nations. Emergy is a measure of the solar energy equivalent used, directly or indirectly, to support the processes that characterize the economic activity in a country. Emergy has renewable and non-renewable components. Our results show that the non-renewable component of national emergy use is positively correlated with night-time satellite imagery. This relationship can be used to produce emergy density maps which enable the incorporation of spatially explicit representations of emergy in geographic information systems. The region of Abruzzo (Italy) is used to demonstrate this relationship as a spatially disaggregate case.

Global Distribution and Density of Constructed Impervious Surfaces.

We present the first global inventory of the spatial distribution and density ofconstructed impervious surface area (ISA). Examples of ISA include roads, parking lots,buildings, driveways, sidewalks and other manmade surfaces. While high spatialresolution is required to observe these features, the new product reports the estimateddensity of ISA on a one-km² grid based on two coarse resolution indicators of ISA - thebrightness of satellite observed nighttime lights and population count. The model wascalibrated using 30-meter resolution ISA of the USA from the U.S. Geological Survey.Nominally the product is for the years 2000-01 since both the nighttime lights andreference data are from those two years. We found that 1.05% of the United States landarea is impervious surface (83,337 km²) and 0.43 % of the world's land surface (579,703km²) is constructed impervious surface. China has more ISA than any other country(87,182 km²), but has only 67 m² of ISA per person, compared to 297 m² per person in theUSA. The distribution of ISA in the world's primary drainage basins indicates that watersheds damaged by ISA are primarily concentrated in the USA, Europe, Japan, China and India. The authors believe the next step for improving the product is to include reference ISA data from many more areas around the world.