Modeling resilience and sustainability in ancient agricultural systems

The reasons why people adopt unsustainable agricultural practices, and the ultimate environmental implications of those practices, remain incompletely understood in the present world. Archaeology, however, offers unique datasets on coincident cultural and ecological change, and their social and environmental effects. This article applies concepts derived from ecological resilience thinking to assess the sustainability of agricultural practices as a result of long-term interactions between political, economic, and environmental systems. Using the urban center of Gordion, in central Turkey, as a case study, it is possible to identify mismatched social and ecological processes on temporal, spatial, and organizational scales, which help to resolve thresholds of resilience. Results of this analysis implicate temporal and spatial mismatches as a cause for local environmental degradation, and increasing extralocal economic pressures as an ultimate cause for the adoption of unsustainable land-use practices. This analysis suggests that a research approach that integrates environmental archaeology with a resilience perspective has considerable potential for explicating regional patterns of agricultural change and environmental degradation in the past

Detecting spatial regimes in ecosystems

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change

Perceived stressors of climate vulnerability across scales in the Savannah zone of Ghana: a participatory approach

Smallholder farmers in sub-Saharan Africa are confronted with climatic and non-climatic stressors. Research attention has focused on climatic stressors, such as rainfall variability, with few empirical studies exploring non-climatic stressors and how these interact with climatic stressors at multiple scales to affect food security and livelihoods. This focus on climatic factors restricts understanding of the combinations of stressors that exacerbate the vulnerability of farming households and hampers the development of holistic climate change adaptation policies. This study addresses this particular research gap by adopting a multi-scale approach to understand how climatic and non-climatic stressors vary, and interact, across three spatial scales (household, community and district levels) to influence livelihood vulnerability of smallholder farming households in the Savannah zone of northern Ghana. This study across three case study villages utilises a series of participatory tools including semi-structured interviews, key informant interviews and focus group discussions. The incidence, importance, severity and overall risk indices for stressors are calculated at the household, community, and district levels. Results show that climatic and non-climatic stressors were perceived differently; yet, there were a number of common stressors including lack of money, high cost of farm inputs, erratic rainfall, cattle destruction of crops, limited access to markets and lack of agricultural equipment that crossed all scales. Results indicate that the gender of respondents influenced the perception and severity assessment of stressors on rural livelihoods at the community level. Findings suggest a mismatch between local and district level priorities that have implications for policy and development of agricultural and related livelihoods in rural communities. Ghana’s climate change adaptation policies need to take a more holistic approach that integrates both climatic and non-climatic factors to ensure policy coherence between national climate adaptation plans and District development plans

Early predictors of impaired social functioning in male rhesus macaques (Macaca mulatta)

Autism spectrum disorder (ASD) is characterized by social cognition impairments but its basic disease mechanisms remain poorly understood. Progress has been impeded by the absence of animal models that manifest behavioral phenotypes relevant to ASD. Rhesus monkeys are an ideal model organism to address this barrier to progress. Like humans, rhesus monkeys are highly social, possess complex social cognition abilities, and exhibit pronounced individual differences in social functioning. Moreover, we have previously shown that Low-Social (LS) vs. High-Social (HS) adult male monkeys exhibit lower social motivation and poorer social skills. It is not known, however, when these social deficits first emerge. The goals of this study were to test whether juvenile LS and HS monkeys differed as infants in their ability to process social information, and whether infant social abilities predicted later social classification (i.e., LS vs. HS), in order to facilitate earlier identification of monkeys at risk for poor social outcomes. Social classification was determined for N = 25 LS and N = 25 HS male monkeys that were 1–4 years of age. As part of a colony-wide assessment, these monkeys had previously undergone, as infants, tests of face recognition memory and the ability to respond appropriately to conspecific social signals. Monkeys later identified as LS vs. HS showed impairments in recognizing familiar vs. novel faces and in the species-typical adaptive ability to gaze avert to scenes of conspecific aggression. Additionally, multivariate logistic regression using infant social ability measures perfectly predicted later social classification of all N = 50 monkeys. These findings suggest that an early capacity to process important social information may account for differences in rhesus monkeys’ motivation and competence to establish and maintain social relationships later in life. Further development of this model will facilitate identification of novel biological targets for intervention to improve social outcomes in at-risk young monkeys