Monday, September 7, 2015
Ben Pitcher with a cake for Pitcher et al. 2015: Chemical fingerprints reveal clues to identity, heterozygosity, and relatedness.
Here's Ben Pitcher presenting a cake for a new paper in PNAS entitled "Chemical fingerprints reveal clues to identity, heterozygosity, and relatedness", by Benjamin J. Pitcher, Isabelle Charrier, and Robert G. Harcourt.
Olfaction is a key sense for mammals, and as a result chemical signals are an important means of communication for most mammalian species. It has long been established that most mammals make, distribute, and respond to chemosignals in a range of contexts, including reproduction, parent–offspring interactions, and social relationships (1). However, most aquatic mammals are unable to use olfaction when foraging, and evidence for its role in social behavior has been equivocal. Historically, reports in the literature have ranged from describing the semiaquatic pinnipeds as microsmatic (2) to those that have observed the high prevalence of naso-nasal inspection during social interactions (Fig. 1), and so inferred an important role for olfactory recognition (3). It is only recently that we experimentally confirmed in wild Australian sea lions that olfactory cues are a reliable mechanism in offspring recognition even in the absence of other sensory cues (4). Similarly, new experimental evidence in other large, wild mammals indicates the importance of olfactory cues in discrimination of potential mates and competitors as well as kin (5–7). However, perhaps due to both the complexity of working with natural vertebrate populations and the complexity of vertebrate scents, the mechanistic basis of chemical communication has received little study (8). In PNAS, Stoffel et al. (9) provide an important advance in the understanding of chemical communication in wild mammals. They compared genetic similarity and the chemical profiles of Antarctic fur seals in two colonies. In so doing they revealed that individual-specific chemical fingerprints have both inherited and environmental components and seem to encode mother–offspring similarity, heterozygosity, and genetic relatedness. The implications of these findings for chemical communication in wild mammals are profound.
Rob Harcourt with Adriano Zumbo cakes for Hussey et al. 2015, Aquatic animal telemetry: A panoramic window into the underwater world
Rob Harcourt presenting two fantastic Adriano Zumbo cakes in celebration of Hussey, N.E., Kessel, S.T., Aarestrup, K., Cooke, S.J., Cowley, P.D. Fisk, A.T., Harcourt, R.G., Holland, K.N., Iverson, S.J., Kocik, J.F., Mills Flemming, J.E., Whoriskey, F.G. 2015. Aquatic animal telemetry: A panoramic window into the underwater world. Science 1255642 (2015). DOI: 10.1126/science.1255642
A brave new world with a wider view
Researchers have long attempted to follow animals as they move through their environment. Until relatively recently, however, such efforts were limited to short distances and times in species large enough to carry large batteries and transmitters. New technologies have opened up new frontiers in animal tracking remote data collection. Hussey et al. review the unique directions such efforts have taken for marine systems, while Kays et al. review recent advances for terrestrial species. We have entered a new era of animal ecology, where animals act as both subjects and samplers of their environments.
Dan bringing some donuts for a new paper out in Global Change Biology: Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling, by Kumar P Mainali, Dan L Warren, Kunjithapatham Dhileepan, Andrew McConnachie, Lorraine Strathie, Gul Hassan, Debendra Karki, Bharat B Shrestha, and Camille Parmesan.
Here's the abstract:
Modeling the distributions of species, especially of invasive species in non-native ranges,
involves multiple challenges. Here, we developed some novel approaches to species
distribution modeling aimed at reducing the influences of such challenges and improving the
realism of projections. We estimated species-environment relationships with four modeling
methods run with multiple scenarios of (1) sources of occurrences and geographically
isolated background ranges for absences, (2) approaches to drawing background (absence)
points, and (3) alternate sets of predictor variables. We further tested various quantitative
metrics of model evaluation against biological insight. Model projections were very sensitive
to the choice of training dataset. Model accuracy was much improved by using a global
dataset for model training, rather than restricting data input to the species’ native range. AUC
score was a poor metric for model evaluation and, if used alone, was not a useful criterion for
assessing model performance. Projections away from the sampled space (i.e. into areas of
potential future invasion) were very different depending on the modeling methods used,
raising questions about the reliability of ensemble projections. Generalized linear models
gave very unrealistic projections far away from the training region. Models that efficiently fit
the dominant pattern, but exclude highly local patterns in the dataset and capture interactions
as they appear in data (e.g. boosted regression trees), improved generalization of the models.
Biological knowledge of the species and its distribution was important in refining choices
about the best set of projections. A post-hoc test conducted on a new Partenium dataset from
Nepal validated excellent predictive performance of our “best” model. We showed that vast
stretches of currently uninvaded geographic areas on multiple continents harbor highly
suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However,
discrepancies between model predictions and parthenium invasion in Australia indicate
successful management for this globally significant weed.