Search Results
Archetype analysis in sustainability research: Methodological portfolio and analytical frontiers
2019, Sietz, D., Frey, U., Roggero, M., Gong, Y., Magliocca, N., Tan, R., Janssen, P., Václavík, T.
In sustainability research, archetype analysis reveals patterns of factors and processes that repeatedly shape social-ecological systems. These patterns help improve our understanding of global concerns, including vulnerability, land management, food security, and governance. During the last decade, the portfolio of methods used to investigate archetypes has been growing rapidly. However, these methods differ widely in their epistemological and normative underpinnings, data requirements, and suitability to address particular research purposes. Therefore, guidance is needed for systematically choosing methods in archetype analysis. We synthesize strengths and weaknesses of key methods used to identify archetypes. Demonstrating that there is no “one-size-fits-all” approach, we discuss advantages and shortcomings of a range of methods for archetype analysis in sustainability research along gradients that capture the treatment of causality, normativity, spatial variations, and temporal dynamics. Based on this discussion, we highlight seven analytical frontiers that bear particular potential for tackling methodological limitations. As a milestone in archetype analysis, our synthesis supports researchers in reflecting on methodological implications, including opportunities and limitations related to causality, normativity, space, and time considerations in view of specific purposes and research questions. This enables innovative research designs in future archetype analysis, thereby contributing to the advancement of sustainability research and decision-making.
Is land fragmentation facilitating or obstructing adoption of climate adaptation measures in Ethiopia?
2018, Cholo, T.C., Fleskens, L., Sietz, D., Peerlings, J.
Land fragmentation is high and increasing in the Gamo Highlands of southwest Ethiopia. We postulate that this substantial land fragmentation is obstructing the adoption of sustainable land management practices as climate adaptation measures. To explore this, a mixed method study was conducted with emphasis on a multivariate probit model. The results indicate that farmers adapt to climate change and variability they perceive. According to the probit model, there is no clear answer to the question whether land fragmentation facilitates or obstructs adoption of sustainable land management practices. Yet, a qualitative analysis found that farmers perceive land fragmentation as an obstacle to land improvement as adaptation strategy. Moreover, farmers invest more in land improvement on plots close to their homestead than in remote plots. However, the higher land fragmentation also promoted crop diversification, manure application and terracing. Although exogenous to farmers, we therefore suggest that land fragmentation can be deployed in climate change adaptation planning. This can be done through voluntary assembling of small neighboring plots in clusters of different microclimates to encourage investment in remote fields and to collectively optimize the benefits of fragmentation to adaptation.
Regionalisation of global insights into dryland vulnerability: Better reflecting smallholders' vulnerability in Northeast Brazil
2014, Sietz, D.
Global analyses of vulnerability reveal generic insights into the relation between socio-ecological systems and the stress impacting upon them including climate and market variability. They thus provide a valuable basis for better understanding and comparing the evolution of socio-ecological systems from a broad perspective. However, even when reflecting sub-national differences, global assessments necessarily aggregate regional variations in the underlying conditions of vulnerability. Refinements are therefore necessary to better accommodate context-specific processes and hence facilitate vulnerability reduction. This study presents a novel methodology to refining global insights into vulnerability at a regional scale. It is based on a spatially explicit link between broad patterns of vulnerability and modelled regional smallholder development. Its application in order to better represent the drylands of Northeast Brazil reveals specific facets of smallholders' vulnerability at the municipio level, reflecting non-linear dynamics. The results show that smallholders' vulnerability was widely exacerbated in the most vulnerable areas. One key mechanism causing such a vulnerability increase involved intensifying resource degradation and the related potential for impoverishment as modelled at the regional scale. In addition, by subsequently re-orienting their livelihoods towards off-farm activities, smallholders became more sensitive to fluctuations and competition in the labour market. In contrast to these critical trends, living and environmental conditions improved in only some areas, thus indicating a decrease in vulnerability. Altogether, in differentiating the heterogeneity of resource management and smallholders' livelihoods, the regional refinement presented in this study indicates necessary adjustments to generic strategies for vulnerability reduction gained at the global scale.
One simulation, different conclusions—the baseline period makes the difference!
2020, Liersch, S., Drews, M., Pilz, T., Salack, S., Sietz, D., Aich, V., Larsen, M.A.D, Gädeke, A., Halsnæ s, K., Thiery, W., Huang, S., Lobanova, A., Koch, H., Hattermann, F.F.
The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period.