The line transect method for estimating densities of large mammals in a tropical deciduous forest: An evaluation of models and field experiments

We have evaluated techniques of estimating animal density through direct counts using line transects during 1988-92 in the tropical deciduous forests of Mudumalai Sanctuary in southern India for four species of large herbivorous mammals, namely, chital (Axis axis), sambar (Cervus unicolor), Asian elephant (Elephas maximus) and gaur (Bos gauras). Density estimates derived from the Fourier Series and the Half-Normal models consistently had the lowest coefficient of variation. These two models also generated similar mean density estimates. For the Fourier Series estimator, appropriate cut-off widths for analysing line transect data for the four species are suggested. Grouping data into various distance classes did not produce any appreciable differences in estimates of mean density or their variances, although model fit is generally better when data are placed in fewer groups. The sampling effort needed to achieve a desired precision (coefficient of variation) in the density estimate is derived. A sampling effort of 800 km of transects returned a 10% coefficient of variation on estimate for chital; for the other species a higher effort was needed to achieve this level of precision. There was no statistically significant relationship between detectability of a group and the size of the group for any species. Density estimates along roads were generally significantly different from those in the interior af the forest, indicating that road-side counts may not be appropriate for most species.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.

Cultural innovation and transmission of tool use in wild chimpanzees:evidence from field experiments

Animal Cognition, V.6, pp. 213-223

Field experiments for marine casualty detection with autonomous surface vehicles

In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

Bearded capuchin monkeys` and a human`s efficiency at cracking palm nuts with stone tools: field experiments

Wild bearded capuchins, Cebus libidinosus, in Fazenda Boa Vista, Brazil crack tough palm nuts using hammer stones. We analysed the contribution of intrinsic factors (body weight, behaviour), size of the nuts and the anvil surface (flat or pit) to the efficiency of cracking. We provided capuchins with local palm nuts and a single hammer stone at an anvil. From video we scored the capuchins` position and actions with the nut prior to each strike, and outcomes of each strike. The most efficient capuchin opened 15 nuts per 100 strikes (6.6 strikes per nut). The least efficient capuchin that succeeded in opening a nut opened 1.32 nuts per 100 strikes (more than 75 strikes per nut). Body weight and diameter of the nut best predicted whether a capuchin would crack a nut on a given strike. All the capuchins consistently placed nuts into pits. To provide an independent analysis of the effect of placing the nut into a pit, we filmed an adult human cracking nuts on the same anvil using the same stone. The human displaced the nut on proportionally fewer strikes when he placed it into a pit rather than on a flat surface. Thus the capuchins placed the nut in a more effective location on the anvil to crack it. Nut cracking as practised by bearded capuchins is a striking example of a plastic behaviour where costs and benefits vary enormously across individuals, and where efficiency requires years to attain. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Recoupled separated-local-field experiments and applications to study intermediate-regime molecular motions

A specific separated-local-field NMR experiment, dubbed Dipolar-Chemical-Shift Correlation (DIPSHIFT) is frequently used to study molecular motions by probing reorientations through the changes in XH dipolar coupling and T-2. In systems where the coupling is weak or the reorientation angle is small, a recoupled variant of the DIPSHIFT experiment is applied, where the effective dipolar coupling is amplified by a REDOR-like pi-pulse train. However, a previously described constant-time variant of this experiment is not sensitive to the motion-induced T-2 effect, which precludes the observation of motions over a large range of rates ranging from hundreds of Hz to around a MHz. We present a DIPSHIFT implementation which amplifies the dipolar couplings and is still sensitive to T-2 effects. Spin dynamics simulations, analytical calculations and experiments demonstrate the sensitivity of the technique to molecular motions, and suggest the best experimental conditions to avoid imperfections. Furthermore, an in-depth theoretical analysis of the interplay of REDOR-like recoupling and proton decoupling based on Average-Hamiltonian Theory was performed, which allowed explaining the origin of many artifacts found in literature data. (C) 2012 Elsevier Inc. All rights reserved.

Is Group Lending A Good Enforcement Scheme for Achieving High Repayment Rates?: Evidence from Field Experiments in Vietnam

Microfinance institutions employ various kinds of incentive schemes but estimating the effect of each scheme is not easy due to endogeneity bias. We conducted field experiments in Vietnam to capture the role of joint liability, monitoring, cross-reporting, social sanctions, communication and group formation in borrowers’ repayment behavior. We find that joint liability contracts cause serious free-riding problems, inducing strategic default and lowering repayment rates. When group members observe each others’ investment returns, participants are more likely to choose strategic default. Even after introducing a cross-reporting system and/or penalties among borrowers, the default rates and the ratios of participants who chose strategic default under joint liability are still higher than those under individual lending. We also find that joint liability lending often failed to induce mutual insurance among borrowers. Those who had been helped or who had repaid a little in the previous round were more likely to default strategically and repay a little again in the current round and those who paid large amounts were always the same individuals.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Dynamics in the governance of collective irrigation systems: Evidence from field experiments in Nicaragua.

In this paper, we investigate the real demand for climate protection when the purely individual perspective of existing revealed preference studies is relaxed. This is achieved in two treatments; first, we determine the information subjects receive about the demand revealed by other subjects in a similar decision making situation, second, collective action is implemented whereby all subjects are required to purchase the group?s median quantity at a given price. Participants in the experiment were offered the opportunity to contribute to climate protection by purchasing European Union Allowances. Allowances purchased were withdrawn from the European Emissions Trading Scheme. In our experiment, information about other subjects? behaviour has no treatment effect on the demand for climate protection. Under collective action however, the probability of purchasing allowances is higher compared to the reference treatment situation, an individual contribution mechanism. Furthermore, we observe a strong correlation between subjects? demand and their expectations about other participants? behaviour. When collective action is not available, subjects? e xpectations are consistent with free rider behaviour.

Dynamics in the governance of collective irrigation systems: Evidence from field experiments in Nicaragua.

The objective of this study is to analyze the common pool resource appropriation and public good provisiondecisions in a dynamic setting, testing the differences in behavior and performance between lab and field subjects. We performeda total of 45 games in Nicaragua, including 88 villagers in rural communities and 92 undergraduate students. In order to analyze sequential decision making, we introduce a dynamic and asymmetric irrigation game that combines the typical social dilemmas associated to irrigation systems management.In addition, in 9 out of 22 villagers’ groups, we implemented a treatment that included the disclosure of subjects’ appropriation of the common pool resource. The results reveal that the provision of individuals’ appropriation level results in higher appropriation in subsequent rounds. In addition, the results show that non-treated villagers provide more public good than treated villagers but if compared with students the differences are not significant. The results also suggest that appropriation levels are below the Nash prediction of full appropriation, but above the social efficient level. This results in an efficiency loss in the game that can be explained to a large extent by individual decisions on appropriation and public good contribution and by group appropriation behavior.

Nitrous oxide emissions from European agriculture - an analysis of variability and drivers of emissions from field experiments

Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logarden in Sweden, Maulde in Belgium CE1, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Godollo in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha−1yr−1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important deter- minant of emissions, accounting for 15 % of the variance (using linear regression) in the data from the arable sites (p<0.0001), and 77 % in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission fac- tors. Variability of N2O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation