Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

Aim Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location California, USA. Methods We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching.     

Animal models of diabetic retinopathy: doors to investigate pathogenesis and potential therapeutics

Effective and validated animal models are valuable to investigate the pathogenesis and potential therapeutics for human diseases. There is much concern for diabetic retinopathy (DR) in that it affects substantial number of working population all around the world, resulting in visual deterioration and social deprivation. In this review, we discuss animal models of DR based on different species of animals from zebrafish to monkeys and prerequisites for animal models. Despite criticisms on imprudent use of laboratory animals, we hope that animal models of DR will be appropriately utilized to deepen our understanding on the pathogenesis of DR and to support our struggle to find novel therapeutics against catastrophic visual loss from DR.     

Development of a human three-dimensional organotypic skin-melanoma spheroid model for in vitro drug testing

Despite remarkable efforts, metastatic melanoma (MM) still presents with significant mortality. Recently, mono-chemotherapies are increasingly replenished by more cancer-specific combination therapies involving death ligands and drugs interfering with cell signaling. Still, MM remains a fatal disease because tumors rapidly develop resistance to novel therapies thereby regaining tumorigenic capacity. Although genetically engineered mouse models for MM have been developed, at present no model is available that reliably mimics the human disease and is suitable for studying mechanisms of therapeutic obstacles including cell death resistance. To improve the increasing requests on new therapeutic alternatives, reliable human screening models are demanded that translate the findings from basic cellular research into clinical applications. By developing an organotypic full skin equivalent, harboring melanoma tumor spheroids of defined sizes we have invented a cell-based model that recapitulates both the 3D organization and multicellular complexity of an organ/tumor in vivo but at the same time accommodates systematic experimental intervention. By extending our previous findings on melanoma cell sensitization toward TRAIL (tumor necrosis factor-related apoptosis-inducing ligand) by co-application of sublethal doses of ultraviolet-B radiation (UVB) or cisplatin, we show significant differences in the therapeutical outcome to exist between regular two-dimensional (2D) and complex in vivo-like 3D models. Of note, while both treatment combinations killed the same cancer cell lines in 2D culture, skin equivalent-embedded melanoma spheroids are potently killed by TRAIL+cisplatin treatment but remain almost unaffected by the TRAIL+UVB combination. Consequently, we have established an organotypic human skin-melanoma model that will facilitate efforts to improve therapeutic outcomes for malignant melanoma by providing a platform for the investigation of cytotoxic treatments and tailored therapies in a more physiological setting.     

Effects of ambient temperature on avian incubation behavior

Ambient temperature is commonly thought to influence avian incubation behavior. However, results of empirical studies examining correlationsbetween ambient temperature and bout duration are equivocal.We propose that these equivocal results can be partly explainedby developing a conceptual understanding of how we should expecttemperature to influence incubation. We demonstrate why linearcorrelation analyses across a wide range of temperatures canbe inappropriate based on development of an incubation model for small birds that incorporates how ambient temperature influencesboth embryonic development and adult metabolism. We found supportfor predictions of the model using incubation data from orange-crownedwarblers (Vermivora celata) in Arizona. Both off- and on-boutduration were positively correlated with ambient temperaturebetween 9° and 26°C, but unrelated to ambient temperature<9° and 26-40°C. Bout durations declined as ambienttemperature approached or exceeded 40°C. Incubating orange-crowned warblers appeared to avoid bouts off the nest <7 min andbouts on the nest <20 min. Time of day, duration of theprevious bout, and variation among nests all explained variationin both on- and off-bout duration. Although we found supportfor the general shape of the incubation model, temperature still explained only a small portion of the overall variation in on-and off-bout duration. Results of previous studies were generallyconsistent with the model for off-bout duration; most studiesin colder environments reported positive correlations withtemperature, and the one negative correlation reported was from a hot environment. However, the relationships between on-boutduration and temperature reported in previous studies wereless consistent with our model and our data. Although somediscrepancies could be explained by considering our model,some studies reported negative correlations in cold environments.The effect of ambient temperature on duration of on-bouts probablydiffers among species based on the amount of fat reserves females typically carry during incubation and the extent of male incubationfeeding. Additional studies of the effects of temperature onavian incubation will help improve the general model and ultimatelyaid our understanding of energetic and ecological constraintson avian incubation.     

Co-evolution with lytic phage selects for the mucoid phenotype of Pseudomonas fluorescens SBW25

The effects of co-evolution with lytic phage on bacterial virulence-related traits are largely unknown. In this study we investigate the incidence of the mucoid phenotype of the bacterium Pseudomonas fluorescens SBW25 in response to co-evolution with the lytic phage phi2 (φ2). The mucoid phenotype of Pseudomonas spp. is due to overproduction of alginate and is a considerable virulence factor contributing to the intractability of infections most notably in cystic fibrosis (CF) lung, but also in pathogenic infections of plants. Our data show that this phenotype can evolve as an adaptive response to phage predation and is favoured under specific abiotic conditions, in particular a homogenous spatial structure and a high rate of nutrient replacement. The mucoid phenotype remains partially sensitive to phage infection, which facilitates ‘apparent competition'' with phage-sensitive competitors, partially offsetting the costs of alginate production. Although P. fluorescens SBW25 is not a pathogen, several key characteristics typical of Pseudomonas aeruginosa clinical isolates from CF lung were noted, including loss of motility on mucoid conversion and a high rate of spontaneous reversion to the wild-type phenotype. Although the genetic mechanisms of this phenotype remain unknown, they do not include mutations at many of the commonly reported loci implicated in mucoid conversion, including mucA and algU. These data not only further our understanding of the potential role phage have in the ecology and evolution of bacteria virulence in both natural and clinical settings, but also highlight the need to consider both biotic and abiotic variables if bacteriophages are to be used therapeutically.     

Spectral imaging for precise surgical intervention in Hirschsprung's Disease

We used advanced spectral imaging for intrasurgical decision making in a preclinical study, on a mouse model of Hirschsprung's Disease. Our imaging device sampled areas from normal and abnormal (aganglionic) colon in these animals. Spectral segmentation and classification of the resulting images showed a clear distinction between the normal and aganglionic regions, as confirmed by pathological analysis and use of mutant mice. We developed a simple algorithm that could distinguish normal from aganglionic colon with high spatial resolution and reproducibility, and the following statistics: sensitivity = 97%, specificity = 94%, positive predictive value = 92%, negative predictive value = 98%. These studies showed translational proof of concept that spectral imaging could be used during operations, in real time, to help surgeons precisely distinguish normal from abnormal tissue without requiring traditional biopsy. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modelling biological invasions over homogeneous and inhomogeneous landscapes using level set methods

The establishment, spread and subsequent degradation of existing environments by invasive species is a worldwide problem affecting native and agricultural ecosystems. The phenomenal cost to governments as a result of research and eradication or control drives the need to understand invasion characteristics. In this paper we develop a method for modelling the boundary of an invasion over time with model inputs being the initial distribution of the invasion and the speed at which the invasion front moves over time. This speed function can depend on the topography of the ground cover and we consider examples of homogeneous and inhomogeneous spread. The possibility of a long-distance dispersal event occurring is also considered. In particular, examples of the spread of emergent weeds and weeds which favour creeks and river beds in New Zealand are presented.     

Consumer pressure, seed versus safe-site limitation, and plant population dynamics

Plants often suffer reductions in fecundity due to insect herbivory. Whether this loss of seeds has population-level consequences is much debated and often unknown. For many plants, particularly those with long-lived seedbanks, it is frequently asserted that herbivores have minimal impacts on plant abundance because safe-site availability rather than absolute seed number determines the magnitude of future plant recruitment and hence population abundance. However, empirical tests of this assertion are generally lacking and the interplay between herbivory, spatio-temporal variability in seed- or safe-site-limited recruitment, and seedbank dynamics is likely to be complex. Here we use a stochastic simulation model to explore how changes in the spatial and temporal frequency of seed-limited recruitment, the strength of density-dependent seedling survival, and longevity of seeds in the soil influence the population response to herbivory. Model output reveals several surprising results. First, given a seedbank, herbivores can have substantial effects on mean population abundance even if recruitment is primarily safe-site-limited in either time or space. Second, increasing seedbank longevity increases the population effects of herbivory, because annual reductions in seed input due to herbivory are accumulated in the seedbank. Third, population impacts of herbivory are robust even in the face of moderately strong density-dependent seedling mortality. These results imply that the conditions under which herbivores influence plant population dynamics may be more widespread than heretofore expected. Experiments are now needed to test these predictions. Received: 3 November 1999 / Accepted: 15 February 2000