Modelos poblacionales del gran ánsar nival: comparación entre distintos enfoques empleados para evaluar los impactos potenciales de la cosecha

Demographic models, which are a natural extension of capture–recapture (CR) methodology, are a powerful tool to guide decisions when managing wildlife populations. We compare three different modelling approaches to evaluate the effect of increased harvest on the population growth of Greater Snow Geese (Chen caerulescens atlantica). Our first approach is a traditional matrix model where survival was reduced to simulate increased harvest. We included environmental stochasticity in the matrix projection model by simulating good, average, and bad years to account for the large inter–annual variation in fecundity and first–year survival, a common feature of birds nesting in the Arctic. Our second approach is based on the elasticity (or relative sensitivity) of population growth rate (lambda) to changes in survival as simple functions of generation time. Generation time was obtained from the mean transition matrix based on the observed proportion of good, average and bad years between 1985 and 1998. If we assume that hunting mortality is additive to natural mortality, then a simple formula predicts changes in lambda as a function of changes in harvest rate. This second approach can be viewed as a simplification of the matrix model because it uses formal sensitivity results derived from population projection. Our third, and potentially more powerful approach, uses the Kalman Filter to combine information on demographic parameters, i.e. the population mechanisms summarized in a transition matrix model, and the census information (i.e. annual survey) within an overall Gaussian likelihood. The advantage of this approach is that it minimizes process and measured uncertainties associated with both the census and demographic parameters based on the variance of each estimate. This third approach, in contrast to the second, can be viewed as an extension of the matrix model, by combining its results with the independent census information.Los modelos demográficos, que son una ampliación natural de la metodología de captura–recaptura (CR), constituyen un excelente instrumento orientativo a la hora de decidir cómo gestionar las poblaciones de flora y fauna. Comparamos tres enfoques de modelos distintos para evaluar los efectos de una mayor cosecha en el crecimiento poblacional del ánsar nival (Chen caerulescens atlantica). Nuestro primer enfoque consiste en un modelo de matrices tradicional en el que se redujo la supervivencia a efectos de simular una mayor cosecha. Incluimos estocasticidad medioambiental en el modelo de proyección matricial simulando años buenos, medios y malos a efectos justificar la significativa variación interanual en la fecundidad y en la supervivencia durante el primer año, dado que constituyen una característica común de las aves que nidifican en el Ártico. Nuestro segundo enfoque se basa en la elasticidad (o sensibilidad relativa) de la tasa de crecimiento poblacional (lambda) con respecto a los cambios en la supervivencia como funciones simples del tiempo generacional. El tiempo generacional se obtuvo a partir de la matriz de transición media basada en la proporción observada de años buenos, medios y malos entre 1985 y 1998. Si suponemos que la mortalidad por caza se suma a la mortalidad natural, una fórmula simple predice cambios en la lambda como una función de cambios en la tasa de cosechas. El segundo enfoque puede considerarse como una simplificación del modelo de matrices, puesto que emplea resultados de sensibilidad formal derivados de la proyección poblacional. Nuestro tercer enfoque, de mayor alcance potencial, utiliza el filtro de Kalman para combinar información sobre parámetros demográficos; es decir, los mecanismos poblacionales resumidos en un modelo de matrices de transición, y la información censal (es decir, la inspección anual) en una probabilidad gaussiana general. La ventaja de este enfoque es que minimiza los procesos y las incertidumbres medidas que se asocian, tanto con el censo como con los parámetros demográficos basados en la varianza de cada estimación. El tercer enfoque, a diferencia del segundo, puede considerarse como una ampliación del modelo de matrices, combinando sus resultados con la información censal independiente

Methodological advances

The study of population dynamics has long depended on methodological progress. Among many striking examples, continuous time models for populations structured in age (Sharpe & Lotka, 1911) were made possible by progress in the mathematics of integral equations. Therefore the relationship between population ecology and mathematical and statistical modelling in the broad sense raises a challenge in interdisciplinary research. After the impetus given in particular by Seber (1982), the regular biennial EURING conferences became a major vehicle to achieve this goal. It is thus not surprising that EURING 2003 included a session entitled "Methodological advances". Even if at risk of heterogeneity in the topics covered and of overlap with other sessions, such a session was a logical way of ensuring that recent and exciting new developments were made available for discussion, further development by biometricians and use by population biologists. The topics covered included several to which full sessions were devoted at EURING 2000 (Anderson, 2001) such as: individual covariates, Bayesian methods, and multi–state models. Some other topics (heterogeneity models, exploited populations and integrated modelling) had been addressed by contributed talks or posters. Their presence among "methodological advances", as well as in other sessions of EURING 2003, was intended as a response to their rapid development and potential relevance to biological questions. We briefly review all talks here, including those not published in the proceedings. In the plenary talk, Pradel et al. (in prep.) developed GOF tests for multi–state models. Until recently, the only goodness–of–fit procedures for multistate models were ad hoc, and non optimal, involving use of standard tests for single state models (Lebreton & Pradel, 2002). Pradel et al. (2003) proposed a general approach based in particular on mixtures of multinomial distributions. Pradel et al. (in prep.) showed how to decompose tests into interpretable components as proposed by Pollock et al. (1985) for the Cormack–Jolly–Seber model Pledger et al. (in prep.) went on in their thorough exploration of models with heterogeneity of capture (Pledger & Schwarz, 2002; Pledger et al., 2003), by considering the use of finite mixture models for the robust design. Given the level of details in demographic traits presently addressed by capture–recapture, the problem of heterogeneity, once apparently settled by fairly reassuring messages (Carothers, 1973, 1979), is becoming again a central issue, with potential disastrous consequences if improperly handled. Heterogeneity models, that bear also a relationship to "multi–event models" (Pradel, in press), will thus certainly be increasingly useful. Pollock, Norris, and Pledger (in prep.) reviewed the capture–recapture models as applied to community data (Boulinier et al., 1998) and developed general removal and capture–recapture models when multiple species are sampled to estimate community parameters. Because of unequal delectability between species, these approaches bear a clear relationship to heterogeneity models, which will be more and more a reference for comparative studies of communities and "macroecology" (Gaston & Blackburn, 2000). Bonner & Schwarz (2004) proposed a capture–recapture model with continuous individual covariates changing over time more fully developed in Bonner & Schwarz (2004). The difficulty here is to set up a sub–model predicting the covariate value when an individual is not captured. While multi–state models permit an ad hoc treatment by categorizing the covariate, Bonner and Schwarz bring a sound answer by considering the covariate obeys a Markov chain with continuous state–space. Otis & White (2004) presented a thorough, simulation–based, investigation of two approaches used to test the contrasting hypotheses of additive and compensatory hunting mortality based on band recovery data. The two approaches are the usual ultra–structural model and a new one based on a random effects model. This paper can be viewed as part of a revival of studies of the dynamics of exploited populations, in the broad sense, including the study of man–induced mortality in the framework of conservation biology (Lebreton, in press). This revival is a direct consequence of the increasing impact of man on the biosphere and of continuing methodological progress (Ferson & Burgman, 2000). The use of random effects models (see also Schaub & Lebreton, 2004) directly builds upon the seminal work by Anderson and Burnham (1976). Stauffer presented a Winbugs implementation of the Cormack–Jolly–Seber model that complemented other presentations in the conference and the short course. Finally, Morgan, Besbeas, Thomas, Buckland, Harwood, Duck and Pomery, proposed a thorough and timely review of integrated modelling, i.e., in our context, of models considering simultaneously capture–recapture demographic information and census information. These methods were covered in other sessions, in relation to Bayesian methodology. Integrated modelling appears indeed to be the logical way of combining all pieces of information arising from integrated monitoring, and as one of the great methodological challenges for our community in the years to come (Besbeas et al., 2002). Methodological progress in population dynamics is apparently still on an upward trajectory and we look forward to many exciting contributions at future EURING conferences

Estudio comparativo entre la hipótesis de la mortalidad aditiva y la hipótesis de la mortalidad compensatoria mediante el empleo de un modelo de efectos aleatorios basado en datos de recuperación de anillas

The interaction of an additional source of mortality with the underlying "natural" one strongly affects population dynamics. We propose an alternative way to test between two forms of interaction, total additivity and compensation. In contrast to existing approaches, only ring–recovery data where the cause of death of each recovered individual is known are needed. Cause–specific mortality proportions are estimated based on a multistate capture–recapture model. The hypotheses are tested by inspecting the correlation between the cause–specific mortality proportions. A variance decomposition is performed to obtain a proper estimate of the true process correlation. The estimation of the cause–specific mortality proportions is the most critical part of the approach. It works well if at least one of the two mortality rates varies across time and the two recovery rates are constant across time. We illustrate this methodology by a case study of White Storks Ciconia ciconia where we tested whether mortality induced by power line collision is additive to other forms of mortality.La interacción de una fuente adicional de mortalidad con la fuente subyacente "natural" incide de forma considerable en la dinámica poblacional. Proponemos un método alternativo para comprobar los dos tipos de interacción: la aditividad total y la compensación. A diferencia de lo que sucede con los modelos empleados actualmente, en este caso sólo se precisan datos de recuperación de anillas de cada uno de los individuos recuperados cuando se conoce la causa que ha provocado su muerte. Los porcentajes de mortalidad inducida por una causa específica se estiman a partir de un modelo de captura–recaptura multiestado. Las hipótesis se comprueban examinando la correlación existente entre los porcentajes de mortalidad inducida por una causa específica. Posteriormente, se efectúa una descomposición de varianza a fin de obtener una estimación apropiada de la verdadera correlación del proceso. La estimación de los porcentajes de mortalidad provocada por una causa específica representa el punto más crítico de este planteamiento. Funciona adecuadamente si por lo menos una de las dos tasas de mortalidad varía con el tiempo y las dos tasas de recuperación se mantienen constantes en el tiempo. Para ilustrar esta metodología, presentamos un estudio de la cigüeña blanca Ciconia ciconia, en el que verificamos si la mortalidad inducida por colisiones con los tendidos eléctricos se suma a otras formas de mortalidad

Principios e interés de los test Bondad de Ajuste (GOF) para los modelos de captura–recaptura multiestado

Optimal goodness–of–fit procedures for multistate models are new. Drawing a parallel with the corresponding single–state procedures, we present their singularities and show how the overall test can be decomposed into interpretable components. All theoretical developments are illustrated with an application to the now classical study of movements of Canada geese between wintering sites. Through this application, we exemplify how the interpretable components give insight into the data, leading eventually to the choice of an appropriate general model but also sometimes to the invalidation of the multistate models as a whole. The method for computing a corrective overdispersion factor is then mentioned. We also take the opportunity to try to demystify some statistical notions like that of Minimal Sufficient Statistics by introducing them intuitively. We conclude that these tests should be considered an important part of the analysis itself, contributing in ways that the parametric modelling cannot always do to the understanding of the data.Los procedimientos óptimos de bondad de ajuste, aplicados a los modelos multiestado, son nuevos. Trazando un paralelismo con los correspondientes procesos de uniestado, presentamos sus articularidades y mostramos como el test general puede descomponerse en componentes susceptibles de ser interpretados. Todos los desarrollos teóricos están ilustrados con una aplicación del ya clásico estudio de los desplazamientos de la barnacla canadiense entre sus lugares de invernada. Mediante esta aplicación, presentamos un ejemplo de cómo los componentes susceptibles de ser interpretados nos proporcionan una idea de los datos que nos pueden llevar a la elección de un modelo general apropiado, pero también a veces a la invalidación de los modelos de multiestados en su conjunto. Se menciona entonces el método para calcular un factor de corrección de la sobredispersión. Aprovechamos esta ocasión para intentar también desmitificar algunas nociones estadísticas, como las Estadísticas Suficientes Mínimas, introduciéndolas intuitivamente. La conclusión es que estas pruebas deberían considerarse una parte importante del propio análisis, contribuyendo a la comprensión de los datos, de un modo que el modelaje paramétrico no siempre consigue

Measurement of the electron drift velocity for directional dark matter detectors

Three-dimensional track reconstruction is a key issue for directional Dark Matter detection. It requires a precise knowledge of the electron drift velocity. Magboltz simulations are known to give a good evaluation of this parameter. However, large TPC operated underground on long time scale may be characterized by an effective electron drift velocity that may differ from the value evaluated by simulation. In situ measurement of this key parameter is hence a way to avoid bias in the 3D track reconstruction. We present a dedicated method for the measurement of the electron drift velocity with the MIMAC detector. It is tested on two gas mixtures : $\rm CF_4$ and $\rm CF_4+CHF_3$. We also show that adding $\rm CHF_3$ allows us to lower the electron drift velocity while keeping almost the same Fluorine content of the gas mixture.Comment: Proceedings of the 4th international conference on Directional Detection of Dark Matter (CYGNUS 2013), 10-12 June 2013, Toyama, Japa

In situ measurement of the electron drift velocity for upcoming directional Dark Matter detectors

Three-dimensional track reconstruction is a key issue for directional Dark Matter detection and it requires a precise knowledge of the electron drift velocity. Magboltz simulations are known to give a good evaluation of this parameter. However, large TPC operated underground on long time scale may be characterized by an effective electron drift velocity that may differ from the value evaluated by simulation. In situ measurement of this key parameter is hence needed as it is a way to avoid bias in the 3D track reconstruction. We present a dedicated method for the measurement of the electron drift velocity with the MIMAC detector. It is tested on two gas mixtures: CF4 and CF4 + CHF3. The latter has been chosen for the MIMAC detector as we expect that adding CHF3 to pure CF4 will lower the electron drift velocity. This is a key point for directional Dark Matter as the track sampling along the drift field will be improved while keeping almost the same Fluorine content of the gas mixture. We show that the drift velocity at 50 mbar is reduced by a factor of about 5 when adding 30% of CHF3.Comment: 19 pages, 14 figures. Minor corrections, matches published version in JINS

The origin and prevention of pandemics.

Despite the fact that most emerging diseases stem from the transmission of pathogenic agents from animals to humans, the factors that mediate this process are still ill defined. What is known, however, is that the interface between humans and animals is of paramount importance in the process. This review will discuss the importance of the human-animal interface to the disease emergence process. We also provide an overview of factors that are believed to contribute to the origin and global spread of emerging infectious diseases and offer suggestions that may serve as future prevention strategies, such as social mobilization, public health education, behavioral change, and communication strategies. Because there exists no comprehensive global surveillance system to monitor zoonotic disease emergence, the intervention measures discussed herein may prove effective temporary alternatives