Can the Tragedy of the Commons be Avoided in Common-Pool Forage Resource Systems? An Application to Small-Holder Herding in the Semi-Arid Grazing Lands of Nigeria

Abstract

There exist common-pool resource systems where it is difficult to prevent prospective beneficiaries from receiving profits from the use or harvest of shared resources, and they are often subject to continual utilization, leading to resource degradation and economic erosion (a behavior known as the ‘tragedy of the commons’). Nigerian nomadic grazing systems currently undergoing the tragedy of the commons pose a great challenge to agrarian communities, herders and political stability throughout the country due to violent conflicts and property destruction as herders migrate in search of forage resources for livestock. We modeled these dynamics in order to better understand the Nigerian grazing lands, with the objective of identifying potential leverage points capable of reversing overgrazing-induced forage degradation, in order to ensure a sustainable livestock production sector. Model what-if experiments (crop restrictions, crop marketing and increased labor costs) were run, resulting in partial solutions that were effective only in the short-term or limited in geographic-scope. A sustainable solution should include a combination of strategies, as the impact of one strategy alone cannot effectively resolve these Nigerian grazing issues (e.g., collaboration between farmers, herdsmen and government stakeholders to increase market integration via crop market expansion while simultaneously providing forage regeneration time for grazing lands). The resulting model could be used by Nigerian policy-makers to evaluate the long-term effects of decisions which were previously unexplored.

Assessing soil erosion and farmers’ decision of reducing erosion for sustainable soil and water conservation in Burji woreda, southern Ethiopia

“…In Wacho sub-watershed, 80% of the users and almost all non-users benefit from grazing on communal lands. Even though this could reduce trampling and residue grabbing on cultivated lands, it would result in overgrazing and land degradation due to little conservation effort to common resources 36 .…”

ASAS–NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production

“…In agriculture, models are extensively used to capture pathways, test hypotheses, and identify high-leverage solutions, circumventing high risk, time constraints, or financial costs ( Sterman, 2000 ; Turner et al, 2016 ; Tedeschi and Fox, 2020 ; Turner, 2020 ). Models have been applied to optimize diet formulation, livestock grazing dynamics, animal and plant performance/production, environmental impacts, and economic outcomes ( Thornley and France, 2007 ; Turner et al, 2013 ; NASEM, 2016 ; Park et al, 2017 ; Tedeschi et al, 2019 ; Tinsley et al, 2019 ; Aderinto et al, 2020 ; Tedeschi and Fox, 2020 ; Taylor et al, 2022 ). Other examples include the Integrated Farm Systems model to conduct a life cycle assessment ( Webb et al, 2020 ), the Ruminant Nutrition System that simulates nutrition and growth dynamics for different ruminant animal classes and production phases (e.g., steer feedlot finishing diet formulation) as well as economic-cost optimization based on feedstuff costs ( Tedeschi and Fox, 2020 ), and the Ruminant Farm Systems whole-farm dairy system model that accounts for animal, manure, soil and crop, feed storage, and dairy environmental impacts (e.g., GHG; Kebreab et al, 2019 ; Hansen et al, 2021 ).…”

Exploring Wild Horse Population Dynamics on US Public Rangelands Using a Simple Systems Simulation Model

“…To achieve this, a model, grounded in systems thinking methodology (i.e., closed-form endogenous feedback processes), was constructed linking the wild horse population dynamics to varying management control flows, namely harvest, drylotting, adoption, and fertility control. Similar dynamic models have been used to explore pressing rangeland problems, such as tragedy of the commons in Mongolia (Oniki et al 2018) or Nigeria (Aderinto et al 2020), stocking rate and ranch-level processes and economics (Teague et al 2008; Diaz-Solis et al 2009; Teague et al 2009; Teague et al 2015), or wildlife population dynamics (DeMaso et al 2013; Eversole et al 2018). The remainder of this paper proceeds with an overview of the modeling process, documenting the resulting mathematical model, followed by the design of our calibration and management intervention experiments.…”