Many studies show that punishment, although able to stabilize cooperation at high levels, destroys gains which makes it less efficient than alternatives with no punishment. Standard public goods games (PGGs) in fact show exactly these patterns. However, both evolutionary theory and real world institutions give reason to expect institutions with punishment to be more efficient, particularly in the long run. Long-term cooperative partnerships with punishment threats for non-cooperation should outperform defection prone non-punishing ones. This article demonstrates that fieldwork data from (...) hunter-gatherers, common pool resource management cases and even PGGs support this hypothesis. Although earnings in PGGs with a punishment option may be lower at the beginning, efficiency increases dramatically over time. Most ten-period PGGs cannot capture this change because their time horizon is too short. (shrink)

The influence of many factors on ecological success in common pool resource management is still unclear. This may be due to methodological issues. These include causal complexity, a lack of large-N-studies and nonlinear relationships between factors. We address all three issues with a new methodological approach, artificial neural networks, which is discussed in detail. It allows us to develop a model with comparably high predictive power. In addition, two success factors are analyzed: legal security and institutional fairness. Both factors show (...) a positive impact on success in irrigation and fisheries supporting the view that there are sector-independent success factors. (shrink)

The literature on common pool resource (CPR) governance lists numerous factors that influence whether a given CPR system achieves ecological long-term sustainability. Up to now there is no comprehensive model to integrate these factors or to explain success within or across cases and sectors. Difficulties include the absence of large-N-studies (Poteete 2008), the incomparability of single case studies, and the interdependence of factors (Agrawal and Chhatre 2006). We propose (1) a synthesis of 24 success factors based on the current SES (...) framework and a literature review; (2) the application of neural networks on a database of CPR management case studies in an attempt to test the viability of this synthesis. This method allows us to obtain an implicit quantitative and rather precise model of the interdependencies in CPR systems. Given such a model, every success factor in each case can be manipulated separately, yielding different predictions for success. This could become be a fast and inexpensive way to analyze, predict and optimize performance for communities world-wide facing CPR challenges. Existing theoretical frameworks could be improved as well. (shrink)

The question on how the diverse forms of cooperative behavior in humans and nonhuman animals could have evolved under the pressure of natural selection has been a challenge for evolutionary biology ever since Darwin himself. In this chapter, we briefly review and summarize results from the last 50 years of research on human and nonhuman cooperativeness from a theoretical (biology) and an experimental perspective (experimental economics). The first section presents six concepts from theoretical biology able to explain a variety of (...) forms of cooperativeness which evolved in many different species. These are kin selection, mutualism, reciprocity, green-beard altruism, costly signaling, and cultural group selection. These considerations are complemented by two short examples of evolved cooperative behavior, one from microbiology and one from ethology. The second main section focuses on recent experimental research on human cooperativeness. We present a brief review of factors known to impact individual human decision-making in social dilemmas, most prominently communication, punishment, reputation, and assortment. Our conclusion then draws attention to tasks for further research in this area. (shrink)

Communities, policy actors and conservationists benefit from understanding what institutions and land management regimes promote ecosystem services like carbon sequestration and biodiversity conservation. However, the definition of success depends on local conditions. Forests’ potential carbon stock, biodiversity, and rate of recovery following disturbance are known to vary with a broad suite of factors including temperature, precipitation, seasonality, species’ traits and land use history. Methods like forest changes over time , and comparison with 'pristine' reference forests have been proposed to compare (...) the structure and biodiversity of forests in the face of underlying differences. However, data from previous visits or reference forests may be unavailable or costly to obtain. Here, we introduce a new metric of locally weighted forest inter-comparison to mitigate the above shortcomings. This method is applied to an international database of nearly 300 community forests, and compared with previously published techniques. It is particularly suited to large databases where forests may be compared among one another. Further, it avoids problematic comparisons with old-growth forests which may not resemble the goal of forest management. In most cases, the different methods produce broadly congruent results, suggesting that researchers have the flexibility to compare forest conditions using whatever type of data is available. Forest structure and biodiversity are shown to be independently measurable axes of forest condition, although users’ and foresters’ estimations of seemingly unrelated attributes are highly correlated, perhaps reflecting an underlying sentiment about forest condition. These findings contribute new tools for large-scale analysis of ecosystem condition and natural resource policy assessment. Although applied here to forestry, these techniques have broader applications to classification and evaluation problems using crowdsourced or repurposed data for which baselines or external validations are not available. (shrink)