Dataset Information

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system.

ABSTRACT: Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-based-model applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

SUBMITTER: Eitzel MV

PROVIDER: S-EPMC7442250 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system.

Eitzel M V MV Solera Jon J Wilson K B KB Neves Kleber K Fisher Aaron C AC Veski André A Omoju Oluwasola E OE Mawere Ndlovu Abraham A Mhike Hove Emmanuel E

PloS one 20200821 8

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this stud ...[more]

PMID: 32822357

Similar Datasets

Project description:BackgroundInfectious disease surveillance is difficult in many low- and middle-income countries. Information market (IM)-based participatory surveillance is a crowdsourcing method that encourages individuals to actively report health symptoms and observed trends by trading web-based virtual "stocks" with payoffs tied to a future event.ObjectiveThis study aims to assess the feasibility and acceptability of a tailored IM surveillance system to monitor population-level COVID-19 outcomes in Accra, Ghana.MethodsWe designed and evaluated a prediction markets IM system from October to December 2021 using a mixed methods study approach. Health care workers and community volunteers aged ≥18 years living in Accra participated in the pilot trading. Participants received 10,000 virtual credits to trade on 12 questions on COVID-19-related outcomes. Payoffs were tied to the cost estimation of new and cumulative cases in the region (Greater Accra) and nationwide (Ghana) at specified future time points. Questions included the number of new COVID-19 cases, the number of people likely to get the COVID-19 vaccination, and the total number of COVID-19 cases in Ghana by the end of the year. Phone credits were awarded based on the tally of virtual credits left and the participant's percentile ranking. Data collected included age, occupation, and trading frequency. In-depth interviews explored the reasons and factors associated with participants' user journey experience, barriers to system use, and willingness to use IM systems in the future. Trading frequency was assessed using trend analysis, and ordinary least squares regression analysis was conducted to determine the factors associated with trading at least once.ResultsOf the 105 eligible participants invited, 21 (84%) traded at least once on the platform. Questions estimating the national-level number of COVID-19 cases received 13 to 19 trades, and obtaining COVID-19-related information mainly from television and radio was associated with less likelihood of trading (marginal effect: -0.184). Individuals aged <30 years traded 7.5 times more and earned GH ¢134.1 (US $11.7) more in rewards than those aged >30 years (marginal effect: 0.0135). Implementing the IM surveillance was feasible; all 21 participants who traded found using IM for COVID-19 surveillance acceptable. Active trading by friends with communal discussion and a strong onboarding process facilitated participation. The lack of bidirectional communication on social media and technical difficulties were key barriers.ConclusionsUsing an IM system for disease surveillance is feasible and acceptable in Ghana. This approach shows promise as a cost-effective source of information on disease trends in low- and middle-income countries where surveillance is underdeveloped, but further studies are needed to optimize its use.

Project description:Being subject to climate change and human intervention, the land-use pattern in the agro-pastoral ecotone of Northern China has undergone complex changes over the past few decades, which may jeopardize the provision of ecosystem services. Thus, for sustainable land management, ecosystem services should be evaluated and monitored. In this study, based on Landsat TM/ETM data, we quantitatively evaluated the losses of ecosystem service values (ESV) in three sections of the agro-pastoral ecotone from 1980-2015. The results were as follows: (1) the main characteristic of the land conversions was that a large area of grassland was converted into cultivated land in the agro-pastoral ecotone; (2) on the spatial scale, the ESV losses of the agro-pastoral ecotone can be called an "inclined surface" in the direction of the northeast to southwest, and the northeastern section of the agro-pastoral ecotone lost more ESV than the middle and northwest sections (p < 0.05), on the temporal scale, the order of losses was 1990-2000 > 1980-1990 > 2000-2015; (3) the agro-pastoral ecotone lost more ESV, which was mainly due to four kinds of land conversion, which were grassland that was transformed into cultivated land, grassland transformed into unused land, grassland transformed into built-up areas, and cultivated land transformed into built-up areas; (4) although these land conversions were curbed after the implementation of protection policies at the end of the 1990s, due to reduced precipitation and increasing temperatures, the agro-pastoral ecotone will face a more severe situation in the future; and, (5) during the period of 1990-2015, the overall dynamic processes of increasing population gradually expanded to the sparsely populated pastoral area. Therefore, we believe that human interventions are the main cause of ecological deterioration in the agro-pastoral ecotone. This study provides references for fully understanding the regional differences in the ecological and environmental effects of land use change and it helps to objectively evaluate ecological civilization construction in the agro-pastoral ecotone of Northern China.

Dataset Information

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system.

Publications

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets