scholarly journals Divergent socioeconomic drivers of land use at various times in the Hulunber grassland area, China

2021 ◽  
Vol 132 ◽  
pp. 108243
Author(s):  
Zhu Xiaoyu ◽  
Dong Gang ◽  
Xin Xiaoping ◽  
Shao Changliang ◽  
Xu Dawei ◽  
...  
2017 ◽  
Vol 24 (1) ◽  
pp. 113-123 ◽  
Author(s):  
Finn Müller-Hansen ◽  
Manoel F. Cardoso ◽  
Eloi L. Dalla-Nora ◽  
Jonathan F. Donges ◽  
Jobst Heitzig ◽  
...  

Abstract. Changes in land-use systems in tropical regions, including deforestation, are a key challenge for global sustainability because of their huge impacts on green-house gas emissions, local climate and biodiversity. However, the dynamics of land-use and land-cover change in regions of frontier expansion such as the Brazilian Amazon are not yet well understood because of the complex interplay of ecological and socioeconomic drivers. In this paper, we combine Markov chain analysis and complex network methods to identify regimes of land-cover dynamics from land-cover maps (TerraClass) derived from high-resolution (30 m) satellite imagery. We estimate regional transition probabilities between different land-cover types and use clustering analysis and community detection algorithms on similarity networks to explore patterns of dominant land-cover transitions. We find that land-cover transition probabilities in the Brazilian Amazon are heterogeneous in space, and adjacent subregions tend to be assigned to the same clusters. When focusing on transitions from single land-cover types, we uncover patterns that reflect major regional differences in land-cover dynamics. Our method is able to summarize regional patterns and thus complements studies performed at the local scale.


2015 ◽  
Vol 6 (2) ◽  
pp. 1129-1162 ◽  
Author(s):  
K. F. Ahmed ◽  
G. Wang ◽  
L. You ◽  
M. Yu

Abstract. Agriculture is a key component of anthropogenic land use and land cover changes that influence regional climate. Meanwhile, in addition to socioeconomic drivers, climate is another important factor shaping agricultural land use. In this study, we compare the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa using a prototype land use projection (LandPro) algorithm. The algorithm is based on a balance between food supply and demand, and accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. The impact of human decision-making on land use is explicitly considered through multiple "what-if" scenarios. In the application to West Africa, future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes in food demand were projected using a model for policy analysis of agricultural commodities and trade. Without agricultural intensification, the climate-induced decrease in crop yield together with increase in food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century. The increase in agricultural land use is primarily climate-driven in the western part of West Africa and socioeconomically driven in the eastern part. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.


2019 ◽  
Vol 21 (4) ◽  
pp. 425-431 ◽  
Author(s):  
J. Calvo-Alvarado ◽  
V. Jiménez ◽  
A. Calvo-Obando ◽  
M. Castillo

The main goal of this study was to evaluate whether the trends in the recovery of forest cover in Guanacaste continued during the past decade and to evaluate if the socioeconomic drivers of recovery have been altered. Our analysis found that forest cover in Guanacaste province increased marginally from 48.14% in 2005 to 50.74% in 2012. This implies that the forest recovery process during this period has continued but with a much smaller pace, showing signs of stagnation. The province landscape has changed since the 1970s, when it was dominated by livestock ranching and was the most deforested province with only 23.6% of forest cover. Today Guanacaste is a good example of an economic development forest transition region, with a matrix of land use that is dominated by new forests in different successional stages, which has resulted in great benefits to society given the ecosystem services that this landscape provides.


2021 ◽  
Author(s):  
Matthew Binsted ◽  
Gokul Iyer ◽  
Pralit Patel ◽  
Neal Graham ◽  
Yang Ou ◽  
...  

Abstract. This paper describes GCAM-USA v5.3_water_dispatch, an open source model that represents key interactions across economic, energy, water, and land systems in a consistent global framework, with subnational detail in the United States. GCAM-USA divides the world into 31 geopolitical regions outside the United States (U.S.) and represents the U.S. economic and energy systems in 51 state-level regions (50 states plus the District of Columbia). The model also includes 235 water basins and 384 land-use regions; 23 of each fall at least partially within the United States. GCAM-USA offers a level of process and temporal resolution rare for models of its class and scope, including detailed subnational representation of U.S. water demands and supplies and sub-annual operations (day/night for each month) in the U.S. electric power sector. GCAM-USA can be used to explore how changes in socioeconomic drivers, technological progress, or policy impact demands for, and production of, energy, water, and crops at a subnational level in the United States, while maintaining consistency with broader national and international conditions. This paper describes GCAM-USA’s structure, inputs, and outputs, with emphasis on new model features. Four illustrative scenarios encompassing varying socioeconomic and energy system futures are used to explore subnational changes in energy, water, and land-use outcomes. We conclude with information about how public users can access the model.


2016 ◽  
Vol 7 (1) ◽  
pp. 151-165 ◽  
Author(s):  
Kazi Farzan Ahmed ◽  
Guiling Wang ◽  
Liangzhi You ◽  
Miao Yu

Abstract. Agriculture is a key component of anthropogenic land use and land cover changes that influence regional climate. Meanwhile, in addition to socioeconomic drivers, climate is another important factor shaping agricultural land use. In this study, we compare the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa using a prototype land use projection (LandPro) algorithm. The algorithm is based on a balance between food supply and demand, and accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. The impact of human decision-making on land use is explicitly considered through multiple "what-if" scenarios. In the application to West Africa, future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. Without agricultural intensification, the climate-induced decrease in crop yield together with future increases in food demand is found to cause a significant increase in cropland areas at the expense of forest and grassland by the mid-century. The increase in agricultural land use is primarily climate-driven in the western part of West Africa and socioeconomically driven in the eastern part. Analysis of results from multiple scenarios of crop area allocation suggests that human adaptation characterized by science-informed decision-making can potentially minimize future land use changes in many parts of the region.


Author(s):  
D. L. Cornelio

Abstract. Shifting cultivation is a common agricultural practice in the Pacific Islands rarely sustainable today since fallow periods are ever shorter due to the demographic growth, farms fragmentation, uncertain land tenure, and pressures from the market economy among other factors (drivers). Official statistical data and maps were utilized to build up chloropleth maps indicating the areas of high land use intensity (LUI) according to farm size ranges and socioeconomic parameters (treatments) for the country. Twenty vector layers were digitized from published maps for eight ranges of farm sizes (from less than 1 to more than 100 ha), and converted to raster format with a 170 m2 pixel size. Critical maps were then built by boolean operations displaying areas in which both the land use and the socioeconomic driver were simultaneously ranked as high or very high. Treatments showed significant differences among them (p < 0.05), being the most influential those related to human demography. In farms smaller than 3 ha size land use is intense when (in order of importance) Indo-fijian population, household size and land availability values are high; while in farms of 20–50 ha size it is intense when the values of (in order of importance) population change, Indo-fijian population, land availability, fishing and sugar farming are also high. LUI patterns normally decrease with the increase of farm size, but increases on farms over 20 ha size. It is recommended to propose policies that will des-accelerate the rates of land use, such as the facilitation of land ownership over farms of bigger sizes, the gradual replacement of mono cropping by agroforestry systems, and the creation of more employment opportunities in the industry, tourism and services sectors.


Author(s):  
Jessica Penny ◽  
Slobodan Djordjević ◽  
Albert S Chen

Abstract This paper aims to improve the understanding of environmental and socioeconomic drivers on land use change (LUC) through public participation (PP), and provide recommendations for long-term policy making to support sustainable land use management. Public participation (PP) was necessary to help understand and address the problem and concerns of stakeholders within the study area. Through two collaboration workshops seven individual future land use scenarios were created. Using the FLUS (Future land use simulation) model, land use was projected up till 2060, after which logistic regression analysis took place to find the most significant driver. Results found that LUC within the baseline scenario and the ones chosen by stakeholders were very different, however concluded that Paddy field extent would decrease in the future to be replaced by more drought resilient agriculture; Perennials & Orchards and Field Crops. Outcomes from future scenarios propose that future LUC was driven by environment spatial factors such as elevation and climate, not soil suitability. With, first hand interviews suggesting it is indirect external factors such as, crop price that drive LUC. Overall the study provides steps towards dynamic LUC modelling where future scenarios have been tailored to details specified by the public through their participation.


2021 ◽  
Author(s):  
Ianna Raissa Moreira Dantas ◽  
Mareike Söder

&lt;p&gt;In times of international agreements and efforts to mitigate climate change and meet sustainable development, ecosystem management and forest conservation deserve special attention to promote human and environmental sustenance. Tropical forests have been declining worldwide, and biodiversity is under constant threat. Understanding the future potential of environmental services requires analysis of the relationship of socioeconomic drivers and anthropogenic land use change (LUC). Population and economic growth, agricultural production, and human capital have a dual relationship of cause and consequence with LUC. Likewise, changing patterns of land use, through agriculture and silviculture activities, is directly associated to market and technical progress, but also to political, institutional, and socioeconomic development. Studying such relationships enhances the analyses on the ability of institutional factors to promote environmental conservation, economic growth, and social welfare. Studies on LUC are historically based on physical variables; however, institutional and political drivers have shown to be core to forest degradation. The present paper aims at investigating the role of physical and institutional factor on global deforestation. This paper draws from recent global remote sensing data on land use from ESA Climate Change Initiative (ESA/CCI) from 1992 and 2015. To assess drivers of deforestation, we employ a logit model regression accounting for a global spatially explicit dataset on land use, regressed with physical, economic, and socioeconomic variables. We make use of the suitability indicators calculated by IIASA for different agricultural crops within the Global Agro-Ecological Zones modelling. As institutional factors we consider areas under protection based on spatial datasets provided by UNEP and wetland international, and include the country level corruption index of Transparency International. Our preliminary analysis shows that institutional instability is significantly related to LUC. In areas where land should be under protection due to non-market ecosystem services, political instability is likely to stimulate land use. Likewise, insecurity in land tenure might lead to a short-term maximization of profits, through full deforestation and exploitation of the soil fertility, instead of a long-term sustainable use.&lt;/p&gt;


Sign in / Sign up

Export Citation Format

Share Document