Poisson point process models solve the "pseudo-absence problem" for presence-only data in ecology

Presence-only data, point locations where a species has been recorded as being present, are often used in modeling the distribution of a species as a function of a set of explanatory variables---whether to map species occurrence, to understand its association with the environment, or to predict its response to environmental change. Currently, ecologists most commonly analyze presence-only data by adding randomly chosen "pseudo-absences" to the data such that it can be analyzed using logistic regression, an approach which has weaknesses in model specification, in interpretation, and in implementation. To address these issues, we propose Poisson point process modeling of the intensity of presences. We also derive a link between the proposed approach and logistic regression---specifically, we show that as the number of pseudo-absences increases (in a regular or uniform random arrangement), logistic regression slope parameters and their standard errors converge to those of the corresponding Poisson point process model. We discuss the practical implications of these results. In particular, point process modeling offers a framework for choice of the number and location of pseudo-absences, both of which are currently chosen by ad hoc and sometimes ineffective methods in ecology, a point which we illustrate by example.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS331 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Multi-species distribution modeling using penalized mixture of regressions

Multi-species distribution modeling, which relates the occurrence of multiple species to environmental variables, is an important tool used by ecologists for both predicting the distribution of species in a community and identifying the important variables driving species co-occurrences. Recently, Dunstan, Foster and Darnell [Ecol. Model. 222 (2011) 955-963] proposed using finite mixture of regression (FMR) models for multi-species distribution modeling, where species are clustered based on their environmental response to form a small number of "archetypal responses." As an illustrative example, they applied their mixture model approach to a presence-absence data set of 200 marine organisms, collected along the Great Barrier Reef in Australia. Little attention, however, was given to the problem of model selection - since the archetypes (mixture components) may depend on different but likely overlapping sets of covariates, a method is needed for performing variable selection on all components simultaneously. In this article, we consider using penalized likelihood functions for variable selection in FMR models. We propose two penalties which exploit the grouped structure of the covariates, that is, each covariate is represented by a group of coefficients, one for each component. This leads to an attractive form of shrinkage that allows a covariate to be removed from all components simultaneously. Both penalties are shown to possess specific forms of variable selection consistency, with simulations indicating they outperform other methods which do not take into account the grouped structure. When applied to the Great Barrier Reef data set, penalized FMR models offer more insight into the important variables driving species co-occurrence in the marine community (compared to previous results where no model selection was conducted), while offering a computationally stable method of modeling complex species-environment relationships (through regularization).Comment: Published at http://dx.doi.org/10.1214/15-AOAS813 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Model-based control of observer bias for the analysis of presence-only data in ecology

Presence-only data, where information is available concerning species presence but not species absence, are subject to bias due to observers being more likely to visit and record sightings at some locations than others (hereafter "observer bias"). In this paper, we describe and evaluate a model-based approach to accounting for observer bias directly - by modelling presence locations as a function of known observer bias variables (such as accessibility variables) in addition to environmental variables, then conditioning on a common level of bias to make predictions of species occurrence free of such observer bias. We implement this idea using point process models with a LASSO penalty, a new presence-only method related to maximum entropy modelling, that implicitly addresses the "pseudo-absence problem" of where to locate pseudo-absences (and how many). The proposed method of bias-correction is evaluated using systematically collected presence/absence data for 62 plant species endemic to the Blue Mountains near Sydney, Australia. It is shown that modelling and controlling for observer bias significantly improves the accuracy of predictions made using presence-only data, and usually improves predictions as compared to pseudo-absence or "inventory" methods of bias correction based on absences from non-target species. Future research will consider the potential for improving the proposed bias-correction approach by estimating the observer bias simultaneously across multiple species. © 2013 Warton et al

Obesity and the food environment: income and ethnicity differences among people with diabetes: the Diabetes Study of Northern California (DISTANCE).

ObjectiveIt is unknown whether any association between neighborhood food environment and obesity varies according to individual income and/or race/ethnicity. The objectives of this study were to test whether there was an association between food environments and obesity among adults with diabetes and whether this relationship differed according to individual income or race/ethnicity.Research design and methodsSubjects (n = 16,057) were participants in the Diabetes Study of Northern California survey. Kernel density estimation was used to create a food environment score for each individual's residence address that reflected the mix of healthful and unhealthful food vendors nearby. Logistic regression models estimated the association between the modeled food environment and obesity, controlling for confounders, and testing for interactions between food environment and race/ethnicity and income.ResultsThe authors found that more healthful food environments were associated with lower obesity in the highest income groups (incomes 301-600% and >600% of U.S. poverty line) among whites, Latinos, and Asians. The association was negative, but smaller and not statistically significant, among high-income blacks. On the contrary, a more healthful food environment was associated with higher obesity among participants in the lowest-income group (<100% poverty threshold), which was statistically significant for black participants in this income category.ConclusionsThese findings suggest that the availability of healthful food environments may have different health implications when financial resources are severely constrained

Irus and his jovial crew : representations of beggars in Vincent Bourne and other eighteenth-century writers of Latin verse

Alastair Fowler has written, with reference to the time of Milton, of ‘Latin's special role in a bilingual culture’, and this was still true in the early eighteenth century. The education of the elite placed great emphasis on the art of writing Latin verse and modern, as well as ancient, writers of Latin continued to be widely read. Collections of Latin verse, by individual writers such as Vincent Bourne (c. 1694–1747) or by groups such as Westminster schoolboys or bachelors of Christ Church, Oxford, could run into multiple editions, and included poems on a wide range of contemporary topics, as well as reworkings of classical themes. This paper examines a number of eighteenth-century Latin poems dealing with beggars, several of which are here translated for the first time. Particular attention is paid to the way in which the Latin poems recycled well-worn tropes about beggary which were often at variance with the experience of real-life beggars, and to how the specificities of Latin verse might heighten negative representations of beggars in a genre which, as a manifestation of elite culture, appealed to the very class which was politically and legally responsible for controlling them

Disentangling the contributions of dispersal limitation, ecological drift, and ecological filtering to wild bee community assembly

The species composition within communities is highly dependent on the rate of species immigration and whether immigrating species possess the functional traits required by the prevailing environmental conditions. Once established, random fluctuations in birth and death rates may reduce the diversity of ecologically equivalent species if local populations are not replenished by immigrating individuals. Consequently, three key processes drive community assembly: dispersal limitation, ecological filtering, and ecological drift. However, disentangling the relative contribution of these processes remains a challenge in community ecology. We used a binomial generalized linear mixed model to test whether the occurrences of solitary bees within 46 communities in southeast Norway were driven by (1) dispersal limitation, that is, the geographic distance to the nearest site where conspecifics occurred; (2) ecological filtering, that is, if forb species richness selected for non-Ericaceae-affiliated species; and (3) ecological drift, that is, if small, isolated communities were dominated by regionally common species. The regression slopes from the model for each potential driver of community composition were compared with those expected under a null model, in which species were treated as ecologically equivalent. Both dispersal limitation and ecological filtering influenced the probability of species occurring within communities. The occurrence of species decreased with elevation, and this relationship depended on the relative commonness of species and their floral preferences. For non-Ericaceae-affiliated species, the patterns of occurrence mirrored that expected under the null (neutral) model, resulting in the same patterns as would be expected under ecological drift. In contrast, the response of Ericaceae-affiliated species differed from what would be expected from the null model. Our results also indicate that processes leading to neutral dynamics in species compositions drive a large part of the gradient in species richness in Norwegian bee communities. These processes seem related to sampling effects so that large and interconnected communities have a higher probability of including regionally rare species than small, isolated communities. Our results suggest that targeting habitats—where the influence of ecological filtering is expected to be greater than that of neutral dynamics—can increase the success of habitat management plans aimed at promoting rare species

The scaling of postcranial muscles in cats (Felidae) I: forelimb, cervical, and thoracic muscles

The body masses of cats (Mammalia, Carnivora, Felidae) span a ~300‐fold range from the smallest to largest species. Despite this range, felid musculoskeletal anatomy remains remarkably conservative, including the maintenance of a crouched limb posture at unusually large sizes. The forelimbs in felids are important for body support and other aspects of locomotion, as well as climbing and prey capture, with the assistance of the vertebral (and hindlimb) muscles. Here, we examine the scaling of the anterior postcranial musculature across felids to assess scaling patterns between different species spanning the range of felid body sizes. The muscle architecture (lengths and masses of the muscle‐tendon unit components) for the forelimb, cervical and thoracic muscles was quantified to analyse how the muscles scale with body mass. Our results demonstrate that physiological cross‐sectional areas of the forelimb muscles scale positively with increasing body mass (i.e. becoming relatively larger). Many significantly allometric variables pertain to shoulder support, whereas the rest of the limb muscles become relatively weaker in larger felid species. However, when phylogenetic relationships were corrected for, most of these significant relationships disappeared, leaving no significantly allometric muscle metrics. The majority of cervical and thoracic muscle metrics are not significantly allometric, despite there being many allometric skeletal elements in these regions. When forelimb muscle data were considered in isolation or in combination with those of the vertebral muscles in principal components analyses and MANOVAs, there was no significant discrimination among species by either size or locomotory mode. Our results support the inference that larger felid species have relatively weaker anterior postcranial musculature compared with smaller species, due to an absence of significant positive allometry of forelimb or vertebral muscle architecture. This difference in strength is consistent with behavioural changes in larger felids, such as a reduction of maximal speed and other aspects of locomotor abilities