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Eric Wajnberg ( INRA, France )
Genetic Algorithms.
What are they, and how can we use them in solving problems in population biology
?Genetic Algorithms are numerical, computer-assisted methods used to find values of parameters that maximize a given criterion. They are inspired by Darwinfs theory of evolution, and are thus simulating an evolutionary process to get to the best (fittest) solutions. These methods were invented in the seventies, and ?since then ?they have been used in a variety of fields, including optimizing military weapons, designing aircrafts, robotics, and even art, to mention just a few. There are now progressively being used to solve problems in ecological science, and especially in behavioral ecology, i.e., to find optimized behaviors animals should adopt to maximize their reproductive output. The seminar will present didactically what Genetic Algorithms are and how they work. Then, a couple of examples showing how we are using them to address problems dealing with the behavioral ecology of parasitoid insects will be presented.
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J. Cohen (The Rockefeller University)
Taylor's power law of fluctuation scaling and abrupt biotic change
??Recent paleoclimatic and paleoecological studies and the 2013 National Academy of Sciences report on Abrupt Impacts of Climate Change: Anticipating Surprises highlight the need to understand better, and develop early warnings of, abrupt changes in the environment and abrupt changes in biota associated with smooth changes in the environment. I will describe recently discovered theoretical examples that predict that smooth changes in the environment can produce abrupt changes (infinite jumps) in a key parameter of Taylor's power law of fluctuation scaling, one of the most widely verified empirical patterns in ecology. A comparable real-world singularity could adversely affect fisheries, forestry, agriculture, conservation, and public health.
R. M. Dorasio (SESC U.S. Geol. Survey )
Accounting for Imperfect Detection and Survey Bias in Statistical Analysis of Presence-only Data
During the past decade ecologists have attempted to estimate the parameters of species distribution models by combining species presence locations observed in opportunistic surveys with spatially referenced covariates of occurrence. Several statistical models have been proposed for the analysis of presence-only data, but these models have largely ignored the effects of imperfect detection and survey bias.?I describe a model-based approach for the analysis of presence-only data that accounts for errors in detection of individuals and for biased selection of survey locations.
?I develop a hierarchical, statistical model that allows presence-only data to be analyzed in conjunction with data acquired independently in planned surveys. One component of the model specifies the spatial distribution of individuals within a bounded, geographic region as a realization of a spatial point process. A second component of the model specifies two kinds of observations, the detections of individuals encountered during opportunistic surveys and the detections of individuals encountered during planned surveys.
?Using mathematical proof and simulation-based comparisons, I demonstrate that biases induced by errors in detection or biased selection of survey locations can be reduced or eliminated by using the hierarchical model to analyze presence-only data in conjunction with counts observed in planned surveys. I show that a relatively small amount of high-quality data (from planned surveys) can be used to leverage the information in presence-only observations, which usually have broad spatial coverage but may not be in- formative of both occurrence and detectability of individuals. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. In addition, since the point-process model is formulated at the level of an individual, it can be extended to account for biological interactions between individuals and temporal changes in their spatial distributions.
M. L. Taper (Montana State University)
?The application of the DC theorem uses well-known and widely used Bayesian computational techniques. With the DC approach, practitioners can use Bayesian phylogenetics software to diagnose non identifiability. Theoreticians and practitioners alike now have a powerful, yet simple tool to detect non identifiability while investigating complex modeling scenarios, where getting closed-form expressions in a probabilistic study is complicated. Furthermore, here we also show how DC can be used as a tool to examine and eliminate the influence of the priors, in particular if the process of prior elicitation is not straightforward. Finally, when applied to phylogenetic inference, DC can be used to study at least two important statistical questions: assessing identifiability of discrete parameters, like the tree topology, and developing efficient sampling methods for computationally expensive posterior densities.
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Chris Elphick (University of Connecticut, USA)
Extinction risk in tidal marsh birds as sea levels rise: changing habitat and demographic processes
?Climate change is predicted to affect many organisms.Specialist species, especially those restricted to habitats that will?diminish under climate change, are presumably most vulnerable. ?High?latitude and high elevation species have received much attention, but?coastal species threatened by sea-level rise are also at risk.?Saltmarsh sparrows Ammodramus caudacutus are tidal marsh endemic?birds, representative of species that use coastal marshes. High tide?flooding is the main cause of nest failure, and nesting habitat is?limited to higher-elevation marshes that flood during spring tides.?Demographic data suggest a high probability of extinction by?mid-century. ?Other tidal-marsh nesting birds likely face similar?fates, albeit not so rapidly. ?Evidence also suggests that?northeastern US marsh habitats are rapidly changing in a manner?consistent with increased tidal flooding and that habitat restoration?is failing to provide suitable conditions for the most vulnerable?species that use these marshes.
Thomas W. Sherry iTulane University, USA)
Effects of nest depredation and weather on reproductive success and population control in a migratory songbird
: Are summer and winter decoupled?
Control of migrant bird populations remains poorlyunderstood. We combined a field experiment (baffles limiting accessto nests by scansorial predators) with modeling long-term nesting?success of American redstarts (Setophaga ruticilla) to assess effects?of multiple variables on nesting success and population dynamics. Theexperiment doubled nesting success, showing importance of scansorial?mammals, primarily red squirrel. Success of unbaffled nests was most?influenced by sciurid nest predator abundance and May temperature, but?also by June rainfall and nest age. Population density had no effect?on nest success in our study, but did in another redstart study?involving different predators. ?Nesting success predicted 66% of the?variation in annual summer population growth (lambda). Our resultsdocument (1) the value of identifying nest predators, (2) multiplefactors affecting reproductive success both directly and indirectly,and (3) ecological decoupling of summer predator-mediated reproductionversus winter food-limited adult survival.
Mauro Fasola (Pavia University, Italy)
Long-term trends of breeding herons and egrets, and their foraging ecology in ricefields of Italy
?Breeding herons and egret were monitored since 1972 in Northwestern Italy, an area of 57,591 km2 with large surfaces of rice cultivation (2,000 km2). The heronries increased from 40 to 130, and the nests peaked in 2000, up to 23 times the initial number for Grey Herons. This spectacular increase was due to lower human-induced mortality, to climatic changes, and to changes in rice cultivation practice. But since 2000, a decreasing trend has become evident. In order to check the influence of rice cultivation practices on population trends, we compared the results obtained in 2013-2014 with those 1977-2000, about the following topics. 1) Changes in chicks diet; some staple prey (amphibians) have diminished, while new prey of recent colonization (the invasive Procambarus clarkii) have increased. 2) Changes in the submerged rice, studied using satellite imagery; compared to 100% submersion until 1990, the submerged surface in 2013 were <50%. 3) Foraging success of the breeders in agricultural versus seminatural foraging habitats. A modeling is under way of the influence of these changes in prey availability, of the climatic changes, and of other factors, on these declining heron populations.
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