Does the interpolation accuracy of species distribution models come at the expense of transferability?

Model transferability (extrapolative accuracy) is one important feature in species distribution models, required in several ecological and conservation biological applications. This study uses 10 modelling techniques and nationwide data on both (1) species distribution of birds, butterflies, and plants and (2) climate and land cover in Finland to investigate whether good interpolative prediction accuracy for models comes at the expense of transferability – i.e. markedly worse performance in new areas. Models’ interpolation and extrapolation performance was primarily assessed using AUC (the area under the curve of a receiver characteristic plot) and Kappa statistics, with supplementary comparisons examining model sensitivity and specificity values. Our AUC and Kappa results show that extrapolation to new areas is a greater challenge for all included modelling techniques than simple filling of gaps in a well‐sampled area, but there are also differences among the techniques in the degree of transferability. Among the machine‐learning modelling techniques, MAXENT, generalized boosting methods (GBM), and artificial neural networks (ANN) showed good transferability while the performance of GARP and random forest (RF) decreased notably in extrapolation. Among the regression‐based methods, generalized additive models (GAM) and generalized linear models (GLM) showed good transferability. A desirable combination of good prediction accuracy and good transferability was evident for three modelling techniques: MAXENT, GBM, and GAM. However, examination of model sensitivity and specificity revealed that model types may differ in their tendencies to either increased over‐prediction of presences or absences in extrapolation, and some of the methods show contrasting changes in sensitivity vs specificity (e.g. ANN and GARP). Among the three species groups, the best transferability was seen with birds, followed closely by butterflies, whereas reliable extrapolation for plant species distribution models appears to be a major challenge at least at this scale. Overall, detailed knowledge of the behaviour of different techniques in various study settings and with different species groups is of utmost importance in predictive modelling.     

Iron and iron/manganese ratio in forage from Icelandic sheep farms: relation to scrapie

This study was undertaken in order to examine whether any connection existed between the amounts of iron in forage and the sporadic occurrence of scrapie observed in certain parts of Iceland. As iron and manganese are considered antagonistic in plants, calculation of the Fe/Mn ratios was also included by using results from Mn determination earlier performed in the same samples. Forage samples (n = 170) from the summer harvests of 2001–2003, were collected from 47 farms for iron and manganese analysis. The farms were divided into four categories: 1. Scrapie-free farms in scrapie-free areas (n = 9); 2. Scrapie-free farms in scrapie-afflicted areas (n = 17); 3. Scrapie-prone farms (earlier scrapie-afflicted, restocked farms) (n = 12); 4. Scrapie-afflicted farms (n = 9). Farms in categories 1 and 2 are collectively referred to as scrapie-free farms. The mean iron concentration in forage samples from scrapie-afflicted farms was significantly higher than in forage samples from farms in the other scrapie categories (P = 0.001). The mean Fe/Mn ratio in forage from scrapie-afflicted farms was significantly higher than in forage from scrapie-free and scrapie-prone farms (P < 0.001). The results indicated relative dominance of iron over manganese in forage from scrapie-afflicted farms as compared to farms in the other categories. Thus thorough knowledge of iron, along with manganese, in soil and vegetation on sheep farms could be a pivot in studies on sporadic scrapie.     

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km² to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.     

Biotic interactions improve prediction of boreal bird distributions at macro-scales

Aim The role of biotic interactions in influencing species distributions at macro‐scales remains poorly understood. Here we test whether predictions of distributions for four boreal owl species at two macro‐scales (10 × 10 km and 40 × 40 km grid resolutions) are improved by incorporating interactions with woodpeckers into climate envelope models. Location Finland, northern Europe. Methods Distribution data for four owl and six woodpecker species, along with data for six land cover and three climatic variables, were collated from 2861 10 × 10 km grid cells. Generalized additive models were calibrated using a 50% random sample of the species data from western Finland, and by repeating this procedure 20 times for each of the four owl species. Models were fitted using three sets of explanatory variables: (1) climate only; (2) climate and land cover; and (3) climate, land cover and two woodpecker interaction variables. Models were evaluated using three approaches: (1) examination of explained deviance; (2) four‐fold cross‐validation using the model calibration data; and (3) comparison of predicted and observed values for independent grid cells in eastern Finland. The model accuracy for approaches (2) and (3) was measured using the area under the curve of a receiver operating characteristic plot. Results At 10‐km resolution, inclusion of the distribution of woodpeckers as a predictor variable significantly improved the explanatory power, cross‐validation statistics and the predictive accuracy of the models. Inclusion of land cover led to similar improvements at 10‐km resolution, although these improvements were less apparent at 40‐km resolution for both land cover and biotic interactions. Main conclusions Predictions of species distributions at macro‐scales may be significantly improved by incorporating biotic interactions and land cover variables into models. Our results are important for models used to predict the impacts of climate change, and emphasize the need for comprehensive evaluation of the reliability of species–climate impact models.     

Biologic, morphologic, and molecular characterisation of Neospora caninum isolates from littermate dogs

Isolation and biologic and molecular attributes of Neospora caninum from three littermate dogs are described. Tissue cysts were confined to the brain and striated muscles. N. caninum was isolated (isolates NC-6, NC-7, and NC-8) in rodents and cell culture that had been inoculated with brain tissue from the dogs. Schizont-like stages reactive with N. caninum antibodies were seen in cell cultures seeded with bradyzoites released from Percoll-isolated N. caninum tissue cysts from the brain of one dog. Tissue cysts were infective orally to mice and gerbils, but not to cats and dogs. The isolates were also identified as N. caninum by PCR and sequence analysis.     

The major histocompatibility complex in monotremes: an analysis of the evolution of <Emphasis Type="Italic">Mhc</Emphasis> class I genes across all three mammalian subclasses

We report the isolation and characterization of cDNA clones of expressed, functional major histocompatibility complex class-I ( Mhc-I) genes from two species of monotremes: the duck-billed platypus and the short-beaked echidna. The cDNA clones were isolated from libraries constructed from spleen RNA, clearly establishing their expression in at least this one peripheral lymphoid organ. From the presence of conserved amino acid residues, it appears the expressed sequences encode molecules that likely function as classical Mhc-I. These clones were isolated using monotreme Mhc-I processed pseudogenes as probes. These processed pseudogenes were isolated from genomic DNA and, based on their structure, are likely independently derived in the platypus and echidna. When all the monotreme sequences were included in phylogenetic analyses, we found no apparent orthologous relationships between the platypus and echidna Mhc-I. Analyses that included a large number of Mhc-I sequences from other taxa support a separate monotreme Mhc-I clade, basal to a therian Mhc-I clade that is comprised of sequences from marsupial and placental mammals. The phylogenies also support the hypothesis that Mhc-I genes of placental mammals, marsupials, and monotremes are derived from three separate lineages of Mhc-I genes, best explained by two rounds of duplications and deletions. The first round would have occurred prior to the divergence of monotremes and therians, and the second prior to the divergence of marsupials and placental mammals. The sequences described here represent the first reported functional monotreme Mhc-I, as well as the first processed pseudogenes of any type from monotremes.     

Scanning electron microscopy and gramicidin patch clamp recordings of microvillous receptor neurons dissociated from the rat vomeronasal organ

Vomeronasal organs from female rats were dissociated and isolated microvillous receptor neurons were studied. The isolated receptor neurons kept the typical bipolar shape which they have in situ as observed by scanning electron microscopy. We applied the perforated patch-clamp technique using the cation-selective ionophore gramicidin on freshly isolated and well differentiated receptor neurons. The mean resting potential was -58+/-14 mV (n=39). The contribution of the sodium pump current to the resting potential was demonstrated by lowering the K+ concentration in the bath or by application of 100 microM dihydro-ouabain. The input resistance was in the range of 1-6 GOmega and depolarizing current pulses of a few pA were sufficient to trigger overshooting action potentials. In voltage clamp conditions a fast transient sodium inward current and a sustained outward potassium current were activated by membrane depolarization. These observations indicate that freshly isolated vomeronasal receptor neurons of rats can be recorded, using gramicidin, with little modification of the intracellular content. Their electrophysiological properties are very similar to those observed in situ. Four out of eight female vomeronasal receptor cells were depolarized by diluted rat male urine.