Using geographic profiling to locate elusive nocturnal animals: A case study with spectral tarsiers

© 2015 The Zoological Society of London. Estimates of biodiversity, population size, population density and habitat use have important implications for management of both species and habitats, yet are based on census data that can be extremely difficult to collect. Traditional assessment techniques are often limited by time and money and by the difficulties of working in certain habitats, and species become more difficult to find as population size decreases. Particular difficulties arise when studying elusive species with cryptic behaviours. Here, we show how geographic profiling (GP) - a statistical tool originally developed in criminology to prioritize large lists of suspects in cases of serial crime - can be used to address these problems. We ask whether GP can be used to locate sleeping sites of spectral tarsiers Tarsius tarsier in Sulawesi, Southeast Asia, using as input the positions at which tarsier vocalizations were recorded in the field. This novel application of GP is potentially of value as tarsiers are cryptic and nocturnal and can easily be overlooked in habitat assessments (e.g. in dense rainforest). Our results show that GP provides a useful tool for locating sleeping sites of this species, and indeed analysis of a preliminary dataset during field work strongly suggested the presence of a sleeping tree at a previously unknown location; two sleeping trees were subsequently found within 5m of the predicted site. We believe that GP can be successfully applied to locating the nests, dens or roosts of elusive animals such as tarsiers, potentially improving estimates of population size with important implications for management of both species and habitats.We thank Operation Wallacea for supporting S.C.F. in thisproject and for providing logistical support for the fieldwork,and Aidan Kelsey for invaluable assistance in the field. Wethank the Indonesian Institute of Sciences (LIPI) andKementerian Riset dan Teknologi Republik Indonesia(RISTEK) for providing permission to undertake the work(RISTEK permit no. 211/SIP/FRP/SM/VI/2013, and BalaiKonservasi Sumber Daya Alam (BKSDA) for theirassistance

Lógicas acerca de lo que no engaña

El interés de Lacan por la lógica y la matemática, lejos de consentir el ideal de la ciencia, forma par te de su esfuerzo en la posibilidad de formaliza ción y matematización del psicoanálisis para su trasmisión. En su “Seminario, libro 10”, cuando se detenga a analizar la angustia, a saber: el afecto que no en gaña, se sostendrá de los rudimentos de la lógica para dar consistencia a sus postulados. Si el autor coloca a la angustia en relación al de seo del Otro, ubicando al objeto a como causa, es porque este juega un papel bisagra en la articulación deseo-goce según aparezca o no velado por el falo. Destaca de este modo que el tiempo de la angustia siempre se sitúa previo a los momentos de cesión, antecediendo así la constitución subjetiva. En esta tarea de darle un sustento lógico a su elaboración sobre la angustia, Lacan relee la letra freudiana recurriendo a la lógica modal para ubicar la cuestión de la causa y a la lógica  matemática para dar cuenta del falo (-φ) y del objeto a. De este modo, el falo se revela como consustancial con la proporción áurea o número de oro y el objeto con la angustia y los números inconmensurables.&nbsp

Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning

Reinforcement learning can effectively learn amortised design policies for designing sequences of experiments. However, current methods rely on contrastive estimators of expected information gain, which require an exponential number of contrastive samples to achieve an unbiased estimation. We propose an alternative lower bound estimator, based on the cross-entropy of the joint model distribution and a flexible proposal distribution. This proposal distribution approximates the true posterior of the model parameters given the experimental history and the design policy. Our estimator requires no contrastive samples, can achieve more accurate estimates of high information gains, allows learning of superior design policies, and is compatible with implicit probabilistic models. We assess our algorithm's performance in various tasks, including continuous and discrete designs and explicit and implicit likelihoods

Cogum : um conto roteiro como simulacro de morte

Monografia (graduação)—Universidade de Brasília, Faculdade de Comunicação, Departamento de Publicidade e Audiovisual, 2013.Cogum é um conto-roteiro. Trata-se de um conto literário e de um roteiro de longametragem inspirados pelo mesmo argumento. A adaptação da literatura para o cinema não é, exatamente, o campo problemático em que Cogum se insere, nem o contrário: conto e roteiro compõem uma obra híbrida, dentro da qual não há hierarquia. O projeto pode ser compreendido em sua multiplicidade temática por meio dos seguintes núcleos: teorias sobre contatos entre cinema e literatura, teorias sobre realismo fantástico e teorias sobre rituais de morte. _________________________________________________________________________ ABSTRACTCogum is a story-script. It’s a short story and a script for a feature-length film inspired by the same argument. The adaptation of literature to the cinema is not exactly the problematic field in which Cogum is fitted into, nor the opposite: here, short story and script are just one and they slide between both textual genres. The project has a thematic complexity that divides into: theories about the contacts between cinema and literature, theories about fantastic realism and theories about death rituals

The Value of Resolving Uncertainty in Social-Ecological Systems

Conservation is increasingly framed or analyzed as a coupled social-ecological problem. However, considering the broader links between social and ecological systems reveals additional and increasing dimensions of uncertainty for conservation management. Reducing uncertainty is expected to lead to improved management decisions, however collecting more data or lengthening project time frames to reduce uncertainty is not without cost. In this study we analyze where conservation managers should invest resources to improve management outcomes by decreasing uncertainty in a coupled social-ecological system. We consider five system components: social and ecological nodes and links, and social-ecological links. We find that the expected value of improving information for any one component is always highest for the component which is most directly acted upon by managers. Our results can help guide conservation investment to reduce uncertainty where improved knowledge of a social-ecological system will provide the greatest improvement in management outcomes

When do we need more data? A primer on calculating the value of information for applied ecologists

1. Applied ecologists continually advocate further research, under the assumption that obtainingmore information will lead to better decisions. Value of information (VoI) analysis can be used to quantify how additional informationmay improve management outcomes: despite its potential, this method is still underused in environmental decision-making. We provide a primer on how to calculate the VoI and assess whether reducing uncertainty will change a decision. Our aim is to facilitate the application of VoI by managers who are not familiar with decision-analytic principles and notation, by increasing the technical accessibility of the tool. 2. Calculating the VoI requires explicit formulation ofmanagement objectives and actions.Uncertainty must be clearly structured and its effects on management outcomes evaluated. We present two measures of the VoI. The expected value of perfect information is a calculation of the expected improvement inmanagement outcomes that would result fromaccess to perfect knowledge. The expected value of sample information calculates the improvement in outcomes expected by collecting a given sample of new data. 3. We guide readers through the calculation of VoI using two case studies: (i) testing for disease when managing a frog species and (ii) learning about demographic rates for the reintroduction of an endangered turtle.We illustrate the use of Bayesian updating to incorporate new information. 4. The VoI depends on our current knowledge, the quality of the information collected and the expected outcomes of the available management actions. Collecting information can require significant investments of resources;VoI analysis assistsmanagers in deciding whether these investments are justified

Fast-tracking stationary MOMDPs for adaptive management problems

Adaptive management is applied in conservation and natural resource management, and consists of making sequential decisions when the transition matrix is uncertain. Informally described as ’learning by doing’, this approach aims to trade off between decisions that help achieve the objective and decisions that will yield a better knowledge of the true transition matrix. When the true transition matrix is assumed to be an element of a finite set of possible matrices, solving a mixed observability Markov decision process (MOMDP) leads to an optimal trade-off but is very computationally demanding. Under the assumption (common in adaptive management) that the true transition matrix is stationary, we propose a polynomial-time algorithm to find a lower bound of the value function. In the corners of the domain of the value function (belief space), this lower bound is provably equal to the optimal value function. We also show that under further assumptions, it is a linear approximation of the optimal value function in a neighborhood around the corners. We evaluate the benefits of our approach by using it to initialize the solvers MO-SARSOP and Perseus on a novel computational sustainability problem and a recent adaptive management data challenge. Our approach leads to an improved initial value function and translates into significant computational gains for both solvers

Fermentation of mannitol extracts from brown macro algae by Thermophilic Clostridia

Publisher's version (útgefin grein)Mannitol-containing macro algae biomass, such as Ascophyllum nodosum and Laminaria digitata, are a potential feedstock for the production of biofuels such as bioethanol. The purpose of this work was to evaluate the ability of thermophilic anaerobes within Class Clostridia to ferment mannitol and mannitol-containing algal extracts. Screening of the type strains of six genera, Caldanaerobius, Caldanaerobacter, Caldicellulosiruptor, Thermoanaerobacter, Thermobrachium, and Thermoanaerobacterium) was conducted on 20 mM mannitol and revealed that 11 of 41 strains could utilize mannitol with ethanol being the dominant end-product. Mannitol utilization seems to be most common within the genus of Thermoanaerobacter (7 of 16 strains) with yields up to 88% of the theoretical yield in the case of Thermoanaerobacter pseudoethanolicus. Six selected mannitol-degrading strains (all Thermoanaerobacter species) were grown on mannitol extracts prepared from A. nodosum and L. digitata. Five of the strains produced similar amounts of ethanol as compared with ethanol yields from mannitol only. Finally, T. pseudoethanolicus was kinetically monitored using mannitol and mannitol extracts made from two macro algae species, A. nodosum and L. digitata for end-product formation.AVS research fund, grant R15065-15.Peer reviewe

Academic conferences urgently need environmental policies

For nearly a decade, environmental scientists have deplored the paradox of needing to fly to conferences1–3 and have increasingly called for sustainable conferencing4,5. Have conferences responded by reducing their environmental impact?No Full Tex