Molecules, wing pattern and distribution: an approach to species delimitation in the "loxurina group" (Lepidoptera: Lycaenidae: Penaincisalia)

The wide range of morphological variations in the “loxurina group” makes taxa identification difficult, and despite several reviews, serious taxonomical confusion remains. We make use of DNA data in conjunction with morphological appearance and available information on species distribution to delimit the boundaries of the “loxurina” group species previously established based on morphology. A fragment of 635 base pairs within the mtDNA gene cytochrome oxidase I (COI) was analysed for seven species of the “loxurina group”. Phylogenetic relationships among the included taxa were inferred using maximum parsimony and maximum likelihood methods. Penaincisalia sigsiga (Bálint et al), P. cillutincarae (Draudt), P. atymna (Hewitson) and P. loxurina (C. Felder & R. Felder) were easily delimited as the morphological, geographic and molecular data were congruent. Penaincisalia ludovica (Bálint & Wojtusiak) and P. loxurina astillero (Johnson) represent the same entity and constitute a sub-species of P. loxurina. However, incongruence among morphological, genetic, and geographic data is shown in P. chachapoya (Bálint & Wojtusiak) and P. tegulina (Bálint et al). Our results highlight that an integrative approach is needed to clarify the taxonomy of these neotropical taxa, but more genetic and geographical studies are still required.

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.

Using niche modelling of indicator species to predict the distribution of xerophitic shrub dune communities in South-Western Portugal

Inland sand dune systems are amongst the most threatened habitat types of Europe. Affected by severe conditions, these habitats present distinct community compositions, which makes them excellent for studying possible interactions among their integrating species and the environment. We focus on understanding the distribution and cooccurrence of the species from dune plant assemblages as a key step for the adequate protection of these habitats. Using data from an extensive survey we identified the shrub species that could be considered indicators of the different xerophytic scrub dune communities in South West Portugal. Then, we modelled the responses of these species to the environmental conditions using Ecological Niche Factor Analysis. We present some preliminary results elucidating whether using species distribution models of indicator species at a regional scale is a valid approach to predict the distribution of the different types of communities inhabiting these endangered habitats.

Can we use niche models of indicator species to predict the distribution of endangered communities?

European-wide conservation policies are based on the identification of priority habitats. However, research on conservation biogeography often relies on the results and projections of species distribution models to assess species' vulnerability to global change. We assess whether the distribution and structure of threatened communities can be predicted by the suitability of the environmental conditions for their indicator species. We present some preliminary results elucidating if using species distribution models of indicator species at a regional scale is a valid approach to predict these endangered communities. Dune plant assemblages, affected by severe conditions, are excellent models for studying possible interactions among their integrating species and the environment. We use data from an extensive survey of xerophytic inland sand dune scrub communities from Portugal, one of the most threatened habitat types of Europe. We identify indicator shrub species of different types of communities, model their geographical response to the environment, and evaluate whether the output of these niche models are able to predict the distribution of each type of community in a different region.

Defining the spatiotemporal surveillance space for alien species’ invasions using approximate Bayesian computation

The spatiotemporal dynamics of an alien species invasion across a real landscape are typically complex. While surveillance is an essential part of a management response, planning surveillance in space and time present a difficult challenge due to this complexity. We show here a method for determining the highest probability sites for occupancy across a landscape at an arbitrary point in the future, based on occupancy data from a single slice in time. We apply to the method to the invasion of Giant Hogweed, a serious weed in the Czech republic and throughout Europe.

Extinction risk in cloud forest fragments under climate change and habitat loss

Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

Optimizing search strategies for invasive pests: Learn before you leap

Strategic searching for invasive pests presents a formidable challenge for conservation managers. Limited funding can necessitate choosing between surveying many sites cursorily, or focussing intensively on fewer sites. While existing knowledge may help to target more likely sites, e.g. with species distribution models (maps), this knowledge is not flawless and improving it also requires management investment. 2.In a rare example of trading-off action against knowledge gain, we combine search coverage and accuracy, and its future improvement, within a single optimisation framework. More specifically we examine under which circumstances managers should adopt one of two search-and-control strategies (cursory or focussed), and when they should divert funding to improving knowledge, making better predictive maps that benefit future searches. 3.We use a family of Receiver Operating Characteristic curves to reflect the quality of maps that direct search efforts. We demonstrate our framework by linking these to a logistic model of invasive spread such as that for the red imported fire ant Solenopsis invicta in south-east Queensland, Australia. 4.Cursory widespread searching is only optimal if the pest is already widespread or knowledge is poor, otherwise focussed searching exploiting the map is preferable. For longer management timeframes, eradication is more likely if funds are initially devoted to improving knowledge, even if this results in a short-term explosion of the pest population. 5.Synthesis and applications. By combining trade-offs between knowledge acquisition and utilization, managers can better focus - and justify - their spending to achieve optimal results in invasive control efforts. This framework can improve the efficiency of any ecological management that relies on predicting occurrence. © 2010 The Authors. Journal of Applied Ecology © 2010 British Ecological Society.

New species of Onthophagus Latreille (Coleoptera : Scarabaeidae) from Australia

Twenty new Australian species of the scarabaeine genus Onthophagus Latreille are described: O. arkoola, O. beelarong, O. bindaree, O. binyana, O. bundara, O. cooloola, O. dinjerra, O. godarra, O. gurburra, O. kakadu, O. mije, O. mongana, O. pinaroo, O. trawalla, O. weringerong, O. williamsi, O. worooa, O. yackatoon, O. yaran, O. yourula. Notes and scanning electron micrographs are given to assist in the separation of each from previously described Australian species. Distribution maps are provided for each species

Distribution and abundance of white grubs (Coleoptera: Scarabaeidae) on groundnut in southern India

Scarab species associated with groundnuts were surveyed in Andhra Pradesh, Karnataka and Tamil Nadu, southern India, between 1995 and 2001. Scarab adults were collected from trees on which they were feeding and/or mating, and larvae (white grubs) from groundnut fields. Holotrichia species, especially H. reynaudi and H. serrata were the major species associated with groundnut. H. reynaudi predominated in the central Deccan area, while H. serrata was most abundant in areas to the south and west. A new, undescribed, Holotrichia species near H. consanguinea was collected south and south-west of Hyderabad in mixed populations with H. reynaudi. However, the full extent of this new species’ distribution remains uncertain. H. rufoflava was rarely associated with groundnut, but was common as an adult at some locations. Other genera encountered during surveys were Anomala, Adoretus, Schizonycha, Autoserica. In survey data, densities of Holotrichia larvae and ‘all other white grubs’ were both very highly correlated with % of damaged groundnut plants. These correlations in combination with concurrent observations of plant damage establish a causal link between white grubs and plant damage and death in southern Indian groundnut. Ranking of preferred host trees for adults were developed from field observations for four Holotrichia species and Schizonycha spp. and will assist grower-initiated surveys of pest occurrence. In combination with insecticide efficacy data published elsewhere, the survey provides the basis for an environmentally friendly and economically viable pest-management system for white grubs on groundnut in southern India.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

The Distribution of Henipaviruses in Southeast Asia and Australasia: Is Wallace's Line a Barrier to Nipah Virus?

Nipah virus (NiV) (Genus Henipavirus) is a recently emerged zoonotic virus that causes severe disease in humans and has been found in bats of the genus Pteropus. Whilst NiV has not been detected in Australia, evidence for NiV-infection has been found in pteropid bats in some of Australia's closest neighbours. The aim of this study was to determine the occurrence of henipaviruses in fruit bat (Family Pteropodidae) populations to the north of Australia. In particular we tested the hypothesis that Nipah virus is restricted to west of Wallace's Line. Fruit bats from Australia, Papua New Guinea, East Timor and Indonesia were tested for the presence of antibodies to Hendra virus (HeV) and Nipah virus, and tested for the presence of HeV, NiV or henipavirus RNA by PCR. Evidence was found for the presence of Nipah virus in both Pteropus vampyrus and Rousettus amplexicaudatus populations from East Timor. Serology and PCR also suggested the presence of a henipavirus that was neither HeV nor NiV in Pteropus alecto and Acerodon celebensis. The results demonstrate the presence of NiV in the fruit bat populations on the eastern side of Wallace's Line and within 500 km of Australia. They indicate the presence of non-NiV, non-HeV henipaviruses in fruit bat populations of Sulawesi and Sumba and possibly in Papua New Guinea. It appears that NiV is present where P. vampyrus occurs, such as in the fruit bat populations of Timor, but where this bat species is absent other henipaviruses may be present, as on Sulawesi and Sumba. Evidence was obtained for the presence henipaviruses in the non-Pteropid species R. amplexicaudatus and in A. celebensis. The findings of this work fill some gaps in knowledge in geographical and species distribution of henipaviruses in Australasia which will contribute to planning of risk management and surveillance activities.

Effect of Electromagnetic Stirring on Macrosegregation during Solidification of a Binary Alloy

The effect of electromagnetic stirring of melt on the final macrosegregation in the continuous casting of an aluminium alloy billet is studied numerically. A continuum mixture model for solidification in presence of electromagnetic stirring is presented. As a case study, simulations are performed for direct chill (DC) casting of an Al-Cu alloy and the effect of electromagnetic stirring on macrosegregation is analysed. The model predicts the temperature, velocity, and species distribution in the mold. As a special case, we have also studied the case in which dendritic particles are fragmented at the interface due to vigorous electromagnetic stirring. For this case, an additional conservation equation for the transport of solid fraction is solved. For modeling the resistance offered by moving solid crystals, a switching function in the momentum equations is used for variation of viscosity. The fragmentation and transport of dendritic particles has a profound effect on the final macrosegregation and microstructure of the solidified billet. It is found that the application of electromagnetic stirring in continuous casting of billets results in better temperature uniformity and macrosegregation pattern.

Lineage delimitation and description of nine new species of bush frogs (Anura: Raorchestes, Rhacophoridae) from the Western Ghats Escarpment

Bush frogs of the genus Raorchestes are distributed mainly in the Western Ghats Escarpment of Peninsular India. The inventory of species in this genus is incomplete and there is ambiguity in the systematic status of species recognized by morphological criteria. To address the dual problem of taxon sampling and systematic uncertainty in bush frogs, we used a large-scale spatial sampling design, explicitly incorporating the geographic and ecological heterogeneity of the Western Ghats. We then used a hierarchical multi-criteria approach by combining mitochondrial phylogeny, genetic distance, geographic range, morphology and advertisement call to delimit bush frog lineages. Our analyses revealed the existence of a large number of new lineages with varying levels of genetic divergence. Here, we provide diagnoses and descriptions for nine lineages that exhibit divergence across multiple axes. The discovery of new lineages that exhibit high divergence across wide ranges of elevation and across the major massifs highlights the large gaps in historical sampling. These discoveries underscore the significance of addressing inadequate knowledge of species distribution, namely the ``Wallacean shortfall'', in addressing the problem of taxon sampling and unknown diversity in tropical hotspots. A biogeographically informed sampling and analytical approach was critical in detecting and delineating lineages in a consistent manner across the genus. Through increased taxon sampling, we were also able to discern a number of well-supported sub-clades that were either unresolved or absent in earlier phylogenetic reconstructions and identify a number of shallow divergent lineages which require further examination for assessment of their taxonomic status.

Habitat availability and heterogeneity and the Indo-Pacific warm pool as predictors of marine species richness in the tropical Indo-Pacific

Range overlap patterns were observed in a dataset of 10,446 expert-derived marine species distribution maps, including 8,295 coastal fishes, 1,212 invertebrates (crustaceans and molluscs), 820 reef-building corals, 50 seagrasses and 69 mangroves. Distributions of tropical Indo-Pacific shore fishes revealed a concentration of species richness in the northern apex and central region of the Coral Triangle epicenter of marine biodiversity. This pattern was supported by distributions of invertebrates and habitat-forming primary producers. Habitat availability, heterogeneity and sea surface temperatures were highly correlated with species richness across spatial grains ranging from 23,000 to 5,100,000 km2 with and without correction for autocorrelation. The consistent retention of habitat variables in our predictive models supports the area of refuge hypothesis which posits reduced extinction rates in the Coral Triangle. This does not preclude support for a center of origin hypothesis that suggests increased speciation in the region may contribute to species richness. In addition, consistent retention of sea surface temperatures in models suggests that available kinetic energy may also be an important factor in shaping patterns of marine species richness. Kinetic energy may hasten rates of both extinction and speciation. The position of the Indo-Pacific Warm Pool to the east of the Coral Triangle in central Oceania and a pattern of increasing species richness from this region into the central and northern parts of the Coral Triangle suggests peripheral speciation with enhanced survival in the cooler parts of the Coral Triangle that also have highly concentrated available habitat. These results indicate that conservation of habitat availability and heterogeneity is important to reduce extinction and that changes in sea surface temperatures may influence the evolutionary potential of the region.