Applying a biocomplexity approach to modelling farmer decision-making and land use impacts on wildlife

Farmers are the direct users of agricultural land and their decision-making affects the agricultural landscape pattern. The influencing factors for farmer land use decision-making were studied, and a method for elucidating the micro-mechanism of the multi-agent and cellular automata models was proposed. Mengcha village is located in Mizhi County of Shaanxi Province in northwest China. The neighborhoods in the village, as well as the kinship networks and socioeconomic conditions of the farmers, were chosen for the calculation of neighborhood similarity (NBSLY), kinship similarity (KSSLY), and socioeconomic similarity (SESLY). At the parcel level, planted crops figure importantly in farmer decision-making and are expressed by parcel similarity (PCSLY). On the basis of the similarity values and two-dimensional tables of NBSLY-PCSLY, KSSLY-PCSLY, and SESLY-PCSLY, (1) NBSLY was weakly correlated with farmer decision-making (PCSLY), which did not diminish with distance between neighboring buildings in the village. (2) For KSSLY, brotherhood accounted for a considerable proportion of decision-making with 68.92% of brotherhoods having similar or pre-similar decision-making. KSSLY imposed considerable influence on farmer decision-making. (3) Farmer decision-making was correlated with SESLY. With increasing SESLY, PCSLY showed an increasing then decreasing tendency. The 2007 results were verified using 2008 data, and the validation yielded identical results for these years. Farmer decision-making is the result of interaction among many factors, and the comprehensive exploration of this issue necessitates support by detailed micro-data.

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A PYTHON TOOL TO ESTIMATE LAND-USE IMPACTS ON GROUNDWATER NITRATE CONCENTRATIONS OBSERVED AT HIGH-CAPACITY PUMPING WELLS IN AN UNCONFINED GLACIAL AQUIFER

10.1130/abs/2020am-349317 ◽

2020 ◽

Author(s):

Stephanie Lynn DeVries ◽

◽

William Garrett Hooten ◽

William Garrett Hooten

Keyword(s):

Land Use ◽

High Capacity ◽

Land Use Impacts ◽

Pumping Wells ◽

Nitrate Concentrations

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An Integrated Economic, Environmental and Social Approach to Agricultural Land-Use Planning

Land ◽

10.3390/land10040364 ◽

2021 ◽

Vol 10 (4) ◽

pp. 364

Author(s):

Sahar Shahpari ◽

Janelle Allison ◽

Matthew Tom Harrison ◽

Roger Stanley

Keyword(s):

Land Use ◽

Land Use Planning ◽

Agricultural Land ◽

Commodity Prices ◽

Global Scale ◽

Agricultural Land Use ◽

Climate Type ◽

Crop Selection ◽

Regional Impacts ◽

Farmer Decision Making

Agricultural land-use change is a dynamic process that varies as a function of social, economic and environmental factors spanning from the local to the global scale. The cumulative regional impacts of these factors on land use adoption decisions by farmers are neither well accounted for nor reflected in agricultural land use planning. We present an innovative spatially explicit agent-based modelling approach (Crop GIS-ABM) that accounts for factors involved in farmer decision making on new irrigation adoption to enable land-use predictions and exploration. The model was designed using a participatory approach, capturing stakeholder insights in a conceptual model of farmer decisions. We demonstrate a case study of the factors influencing the uptake of new irrigation infrastructure and land use in Tasmania, Australia. The model demonstrates how irrigated land-use expansion promotes the diffusion of alternative crops in the region, as well as how coupled social, biophysical and environmental conditions play an important role in crop selection. Our study shows that agricultural land use reflected the evolution of multiple simultaneous interacting biophysical and socio-economic drivers, including soil and climate type, crop and commodity prices, and the accumulated effects of interactive decisions of farmers.

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Identification of erosion-prone areas using morphometric parameters, land use land cover and multi-criteria decision-making method: geo-informatics approach

Environment Development and Sustainability ◽

10.1007/s10668-021-01452-7 ◽

2021 ◽

Author(s):

Paolenmang Haokip ◽

Md. Abdullah Khan ◽

Pandurang Choudhari ◽

Luc Cimusa Kulimushi ◽

Ibodullo Qaraev

Keyword(s):

Decision Making ◽

Land Use ◽

Land Cover ◽

Morphometric Parameters ◽

Multi Criteria Decision Making ◽

Land Use Land Cover

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Methodology of Analyzing Maize Density Loss in Smallholder’s Fields and Potential Optimize Approach

Agriculture ◽

10.3390/agriculture11060480 ◽

2021 ◽

Vol 11 (6) ◽

pp. 480

Author(s):

Zhichao An ◽

Chong Wang ◽

Xiaoqiang Jiao ◽

Zhongliang Kong ◽

Wei Jiang ◽

...

Keyword(s):

Decision Making ◽

Food Security ◽

Zea Mays L ◽

Plant Density ◽

Density Difference ◽

Yield Gap ◽

Farmer Decision Making ◽

Yield Gaps ◽

Farmer Survey ◽

Experimental Plots

Increasing plant density is a key measure to close the maize (Zea mays L.) yield gap and ensure food security. However, there is a large plant density difference in the fields sown by agronomists and smallholders. The primary cause of this phenomenon is the lack of an effective methodology to systematically analyze the density loss. To identify the plant density loss processes from experimental plots to smallholder fields, a research methodology was developed in this study involving a farmer survey and measurements in a smallholder field. The results showed that the sowing density difference caused by farmer decision-making and plant density losses caused by mechanical and agronomic factors explained 15.5%, 5.5% and 6.8% of the plant density difference, respectively. Changing smallholder attitudes toward the value of increasing the plant density could help reduce this density loss and increase farm yields by 12.3%. Therefore, this methodology was effective for analyzing the plant density loss, and to clarify the primary causes of sowing density differences and plant density loss. Additionally, it was beneficial to identify the priorities and stakeholders who share responsibility for reducing the density loss. The methodology has wide applicability to address the sowing density differences and plant density loss in other areas to narrow crop yield gaps and ensure food security.

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Changing Land Use and Population Density Are Degrading Water Quality in the Lower Mekong Basin

Water ◽

10.3390/w13141948 ◽

2021 ◽

Vol 13 (14) ◽

pp. 1948

Author(s):

Flavia Tromboni ◽

Thomas E. Dilts ◽

Sarah E. Null ◽

Sapana Lohani ◽

Peng Bun Ngor ◽

...

Keyword(s):

Water Quality ◽

Land Use ◽

Population Density ◽

Local Population ◽

Reference Conditions ◽

Mekong River ◽

Land Use Impacts ◽

Wet Season ◽

Mekong Basin ◽

Lower Mekong Basin

Establishing reference conditions in rivers is important to understand environmental change and protect ecosystem integrity. Ranked third globally for fish biodiversity, the Mekong River has the world’s largest inland fishery providing livelihoods, food security, and protein to the local population. It is therefore of paramount importance to maintain the water quality and biotic integrity of this ecosystem. We analyzed land use impacts on water quality constituents (TSS, TN, TP, DO, NO3−, NH4+, PO43−) in the Lower Mekong Basin. We then used a best-model regression approach with anthropogenic land-use as independent variables and water quality parameters as the dependent variables, to define reference conditions in the absence of human activities (corresponding to the intercept value). From 2000–2017, the population and the percentage of crop, rice, and plantation land cover increased, while there was a decrease in upland forest and flooded forest. Agriculture, urbanization, and population density were associated with decreasing water quality health in the Lower Mekong Basin. In several sites, Thailand and Laos had higher TN, NO3−, and NH4+ concentrations compared to reference conditions, while Cambodia had higher TP values than reference conditions, showing water quality degradation. TSS was higher than reference conditions in the dry season in Cambodia, but was lower than reference values in the wet season in Thailand and Laos. This study shows how deforestation from agriculture conversion and increasing urbanization pressure causes water quality decline in the Lower Mekong Basin, and provides a first characterization of reference water quality conditions for the Lower Mekong River and its tributaries.

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Monetary Valuation of Flood Protection Ecosystem Service Based on Hydrological Modelling and Avoided Damage Costs. An Example from the Čierny Hron River Basin, Slovakia

Water ◽

10.3390/w13020198 ◽

2021 ◽

Vol 13 (2) ◽

pp. 198

Author(s):

Igor Gallay ◽

Branislav Olah ◽

Zuzana Gallayová ◽

Tomáš Lepeška

Keyword(s):

Decision Making ◽

Land Use ◽

Ecosystem Service ◽

Hydrological Modelling ◽

Flood Protection ◽

Medium Size ◽

Land Uses ◽

Monetary Valuation ◽

Monetary Value ◽

Damage Costs

Flood protection is considered one of the crucial regulating ecosystem services due to climate change and extreme weather events. As an ecosystem service, it combines the results of hydrological and ecosystem research and their implementation into land management and/or planning processes including several formally separated economic sectors. As managerial and economic interests often diverge, successful decision-making requires a common denominator in form of monetary valuation of competing trade-offs. In this paper, a methodical approach based on the monetary value of the ecosystem service provided by the ecosystem corresponding to its actual share in flood regulating processes and the value of the property protected by this service was developed and demonstrated based on an example of a medium size mountain basin (290 ha). Hydrological modelling methods (SWAT, HEC-RAS) were applied for assessing the extent of floods with different rainfalls and land uses. The rainfall threshold value that would cause flooding with the current land use but that would be safely drained if the basin was covered completely by forest was estimated. The cost of the flood protection ecosystem service was assessed by the method of non-market monetary value for estimating avoided damage costs of endangered infrastructure and calculated both for the current and hypothetical land use. The results identify areas that are crucial for water retention and that deserve greater attention in management. In addition, the monetary valuation of flood protection provided by the current but also by hypothetical land uses enables competent and well-formulated decision-making processes.

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