Agricultural productivity in past societies: toward an empirically informed model for testing cultural evolutionary hypotheses

Agricultural productivity, and its variation in space and time, plays a fundamental role in many theories of human social evolution. However, we often lack systematic information about the productivity of past agricultural systems on a scale large enough to test these theories properly. The effect of climate on crop yields has received a great deal of attention resulting in a range of empirical and process-based models, yet the focus has primarily been on current or future conditions. In this paper, we argue for a “bottom-up” approach that estimates potential productivity based on information about the agricultural practices and technologies used in past societies. Of key theoretical interest is using this information to estimate the carrying high quality historical and archaeological information about past societies in order to infer the temporal and geographic patterns of change in agricultural productivity and potential. We discuss information we need to collect about past agricultural techniques and practices, and introduce a new databank initiative that we have developed for collating the best available historical and archaeological evidence. A key benefit of our approach lies in making explicit the steps in the estimation of past productivities and carrying capacities, and in being able to assess the effects of different modelling assumptions. This is undoubtedly an ambitious task, yet promises to provide important insights into fundamental aspects of past societies, enabling us to test more rigorously key hypotheses about human socio-cultural evolution

Statistical Emulation for Environmental Sustainability Analysis

The potential effects of climate change on the environment and society are many. In order to effectively quantify the uncertainty associated with these effects, highly complex simulation models are run with detailed representations of ecosystem processes. These models are computationally expensive and can involve computer runs of several days for their outputs. Computationally cheaper models can be obtained from large ensembles of simulations using a statistical emulation. The purpose of this thesis is to construct cheaper computational models (emulators) from simulation outputs of Lund-Potsdam-Jena-managed Land (LPJmL) which is a dynamic global vegetation and crop model. This research work is part of a project called ERMITAGE. The project links together several key component models into a common framework to better understand how the management and interaction of land, water and the earth’s climate system could be improved. The thesis focuses specifically on emulation of major outputs from the LPJmL model; carbon fluxes (NPP, carbon loss due to heterotrophic respiration and fire carbon) and potential crop yields (cereal, rice, maize and oil crops). Future decadal changes in carbon fluxes and crop yields are modelled as linear functions of climate change and other relevant variables. The emulators are constructed using a combination of statistical techniques of stepwise least squares regression, principal component analysis, weighted least squares regression, censored regression and Gaussian process regression. Further modelling involves sensitivity analyses to identify the relative contribution of each input variable to the total output variance. This used the Sobol global sensitivity method. The data cover the period 2001-2100 and comprise climate scenarios of several GCMs and RCPs. Under cross validation the percentage of variance explained ranges from 52-96% for carbon fluxes, 60-88% for the rainfed crops and 62-93% for the irrigated crops, averaged over climate scenarios

Cultivating Knowledge: The Production and Adaptation of Knowledge on Organic and GM Cotton Farms in Telangana, India

This dissertation explores the ways in which genetically modified (GM) cotton seeds, rice seeds, and organic cotton seeds in Telangana, India set farmers on diverging economic, environmental, and social trajectories. GM cotton, a cash crop sold under hundreds of different brand names by private corporations, leads farmers to rapidly change to new seeds and copy their neighbors’ choices as they chase high yields that counter their high investments in an input-intensive agriculture. Rice, a subsistence and market crop distributed largely by public breeders, allows farmers to change their seeds more slowly as they carefully evaluate durability and taste alongside overall yield. Organic cotton seeds, often provided free of cost by sponsoring NGOs or ethical fiber companies, show farmers that agricultural cost-benefit analysis can be less important than learning to work in tandem with a sponsoring organization. The solutions to agrarian crisis or underdevelopment are often presented as a series of technological fixes. However, agriculture is a fundamentally social act, hinging on the ways in which farmers learn to manage their fields. Taking individual seeds as a lens, I use ethnographic detail and quantitative analysis to study how farmers learn to navigate confusing seed markets, state programs, ethical supply chains, and the village hierarchies that determine who looks to whom for agricultural advice. This work has implications for international development as well as a broader question of modern life: how do we make technologies sustainable in new contexts

Giving Orders in Rural Southern Rhodesia: Controversies over Africans’ Authority in Development Programs, 1928-1934

This article focuses on the period from 1928 to 1935, Depression years, when Harold Jowitt was director of native development. During these years, debates over the Jeanes teacher program, and specifically over the careers of Matthew Magorimbo and Lysias Mukahleyi, exposed both the needs that drew the administration and missions toward community-based development, and the questions of power, authority, and resources that blocked community development, and more specifically the Jeanes teacher program, from achieving its stated aims

Addressing non-traditional security threats under climate change conditions ; towards a new research agenda on norm diffusion in EU-Asia security relations

While scholarly work and policy speeches have mostly dealt with the EU’s capabilities and performance in traditional security issues like wars and war- like intrastate conflicts, the EU’s source of influence in Asia-Pacific seems rather to lie within its vast amount of expertise and technology concerning those threats that are most imminent in the Asia Pacific region: non- traditional security threats such as water, food, energy (in-)securities and potential conflicts arising over access to scarce, transboundary resources and impacts of growth policies – intensified by the consequences of climate change. Drawing on previous research on diffusion mechanisms in EU security policies towards the Asia- Pacific region, this paper will make the case for enlarging norm diffusion research in EU-Asia relations to non-traditional security threats (NTS) and will demonstrate its theoretical as well as social relevance

Exposing Indigenous Punjab to Modern Technology: An Anthropological Analysis

The current day development models proclaim and promise for self sufficiency and sustainability for the masses especially whenever there is a debate over rural development issue in the third world countries like Pakistan In fact the today s world is fast approaching the sustainable livelihood strategies which unfortunately failed to bring about the results assured Failure of Green Revolution has made the scholars professionals and development practitioners to repondoner the western development model particularly those promising agricultural development The western developmental approaches basically imbedded in the capitalistic ethos resulted for radical changes while increasing the rural dependence on the urban areas and even upon the international multinational corporations These new interventions erased the traditional self reliance of country side and thus became an indirect reason for rural urban migration The current paper is an attempt to throw light on the effects of modern technology upon the cultural life of people of a village Sacha Soda in the district Sheikhupura of the Punjab province The paper evaluates the indigenous people s views on Mechanized Agricultural Methods in terms of Economic Sustainability and Cultural Compatibilit

The Opportunity Not Taken: Institutional and Cognitive Barriers to Entrepreneurial Innovation in Contexts of Resource Scarcity

Entrepreneurship is increasingly heralded as a solution to poverty, and many organizations and governments have begun to pursue market-based approaches to poverty alleviation through programs like microfinance and entrepreneurship training. Despite some exceptions, the results of such efforts have largely generated imitative opportunities, whereby individuals use the money and training they receive to replicate existing businesses within their community, rather than becoming able to recognize a broader range of opportunities for innovation and growth, and would-be entrepreneurs are often little better off than before. Whereas prior work has predominantly explored human/financial capital and formal institutional barriers to innovative entrepreneurship, this dissertation, through a series of three studies, using multiple theoretical lenses and methodologies, aims to identify and understand other potential impediments to innovative entrepreneurship in contexts of poverty, focusing on informal institutional and cognitive barriers. My studies all aim to provide both theoretical and practical insights around the following broad research question: What are the (informal) institutional and cognitive barriers to entrepreneurial innovation in contexts of resource scarcity, and how might they be addressed

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (U.S.) against U.S. Dept. of Agriculture (USDA) time series for about 1,000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. Majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields