|Gella Patria L. Abella||Central Luzon State University, Bantug, Science City of Muñoz, Nueva Ecija 3120, Philippines|
|Felino Lansigan||University of the Philippines Los Baños, Los Baños, Laguna 4031, Philippines|
|Jerrold Tubay||University of the Philippines Los Baños, Los Baños, Laguna 4031, Philippines|
A model-based systems approach in optimizing agricultural land use spatial allocation integrating climate change adaptation was developed in this study. A land use planning and analysis system framework was modified and adopted under current conditions and anticipated scenarios for 2035. Climatic scenarios were reflected in land suitability ratings by conducting a land evaluation. All agricultural inputs and outputs were estimated and analyzed by multiple goal linear programming using Gurobi software. The results demonstrated that under current conditions, the city can meet its crop production, increase total farmers’ net income, maximize agricultural labor, and provide a suitable residential area by optimally allocating grids to suitable uses. Under the 2035 scenario, the city can still achieve its development goals despite the change in land suitability and increase in population.
Climate change adaptation; Land suitability; Land use allocation; Systems approach
The growing global human population, coupled with intensifying climate change is putting intense pressure on land. Nations are challenged to strike a balance among different land uses to meet the needs of the people while safeguarding ecosystems (Brown et al., 2008). Land use as an imperative process must evolve to meet the demands and changing climate. The use of land dictates human development since it is the platform of social and economic activities (Corpuz, 2013). However, some development goals are conflicting regarding land, such as residential and commercial land uses encroaching into agricultural land or agricultural and timber production competing with protected areas (Kaim et al., 2018).
Agriculture is among the economic activities greatly affected by competing land use and aggravated by climate change, hence threatening food security. Climate change would put 5–170 million people at risk of hunger by 2080 (Abd-Elmabod et al., 2020). Agricultural productivity is predicted to decrease because of changes in land suitability and water availability brought about by the changing climate.
Climate influences plant growth rate, and any change in climatic parameters brings new opportunities or poses risks to agricultural land use. Exploration of climate change impacts on land suitability can identify areas where a range of options may be expected to change in the future (Brown et al., 2008).
The formulation of a land use plan mainstreaming climate change is being mandated to local government units (LGUs) of the Philippines. However, the process does not entail specifying what crops to grow on specific land based on suitability or where to allocate residential areas such that economic gains from the agricultural sector would not be compromised. The country’s growing population necessitates more food supply, but farmland expansion options have shrunk significantly. A systems approach is required to determine the allocation of land for residential and agriculture. This would help the decision-makers in selecting the best course of action regarding land use allocation by providing a better understanding of the interrelatedness of different components of the system, broadening the scientific information base, and facilitating the prediction of the consequences of the options (Armenakis, 2008). Agricultural land use allocation involves several actors, such as farmers, farmer’s associations, environmental agencies, land planners, and economists (Kaim et al., 2018), representing their respective concerns. Linear programming is an important tool that can be used to explore land use allocations that optimize agricultural, economic, or environmental objectives translated as objective functions (Makowski et al., 2000). Decision variables are areas assigned to production activities of land utilization type, and constraints may include resource availability and supply of and demand for crops.
In this study, a methodological framework was developed in formulating a land use plan integrating land evaluation under current and 2035 climate scenarios in San Jose City, Philippines. A systems approach was utilized to optimally allocate agricultural land use, considering the land suitability of major crops under current and projected climate scenarios, farmers’ yield and income, agricultural employment, and the disaster risk of San Jose City residents. Various development scenarios and land use options are presented to provide a decision-support system for LGUs.
The science-based methodology is doable and can be transferred to any LGU so that they can comply with the Hyogo Framework of Action and Climate Change Act of 2009.
The integration of climate change adaptation into the comprehensive land use plan should be done using a systems approach to provide decision-makers quantified parameters as the basis. Decisions on the use of the finite land are vital in the pursuit of economic, social, and environmental development goals.
Since the framework functioned in San Jose City, it can be adopted by other LGUs. One way of adapting to climate change in the agricultural sector is through a modification of the cropping system. For one, farmers may be planting crops based on what used to be planted and not on crop suitability. Farmlands may meet the land and climatic requirements of crops or varieties other than what farmers used to plant. Crops or varieties may be more resilient to the changing climate and thus can contribute more to economic development.
The result of the optimization runs is a sound basis for decision-making because a better understanding of the system (San Jose City) was provided and the prediction of consequences was facilitated. Optimal land use allocation is a tool for climate change adaptation toward the resiliency of the community.
This study offers the following recommendations: (1) crops planted in different distinct seasons may be included in the MGLP to identify more specifically the use of the land by making it as another type of crop; (2) minimizing disaster risk specific to agriculture may be customized by considering only drought and/or flood as hazards; (3) constraint regarding the assignment of grids for residential use with specific risk scores may be added; (4) in the disaster risk assessment, the coping capacity may be considered another element in the vulnerability equation, including but not limited to a good governance index, material insurance, and hospital services; and (5) in vulnerability assessment, the weights of the factors considered in exposure, susceptibility, and a lack of adaptive capacity must be validated in the Philippine setting.
The authors would like to express their humble gratitude to: (1) the Commission on Higher Education for the research grant, Faculty Development Program Phase II 2012-08-0006, awarded to the corresponding author; (2) employees of the city government of San Jose for providing the necessary information and documents; and (3) farmer respondents for allowing their farms to be part of the study.
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