Short‐term response of threatened small macropods and their predators to prescribed burns in subtropical Australia

Fire is an important ecological process that shapes vegetation structure and habitat for faunal assemblages globally. Prescribed burns are increasingly being used in conservation and management to restore fire regimes in fire‐suppressed vegetation communities. Small threatened macropods require structurally complex habitat that allows them to evade detection by predators. Given that fire can alter vegetation structure, it can be viewed as a strong ecological force in shifting the dynamics between predator and prey species. Previous studies in temperate Australia have shown that prescribed burns in the presence of European Red Fox (Vulpes vulpes) and feral Cat (Felis catus) can have negative impacts on small macropods and medium‐sized mammals. Post‐fire response of threatened small macropods and their predators has not been experimentally examined in subtropical Australia despite this region providing refugia for the Long‐nosed Potoroo (Potorous tridactylus) and Red‐legged Pademelon (Thylogale stigmatica). We conducted a before‐after‐control‐impact fire experiment at two paired sites after low–moderate intensity burns typical of cool season prescribed burns. We used camera trapping to investigate changes in activity of threatened small macropods and their predators. We also recorded vegetation change. Despite large reductions in ground and shrub cover, activity of small macropods and the Dingo (Canis dingo) did not change in response to fires. Therefore, the threat of dingo predation appears to have remained unchanged following the fires. Although feral cats and foxes were present, they showed negligible activity across our sites. Our study suggests that small‐scale patchy ecological burns may not lead to increased predation of small macropods in our landscape. We attribute this to sufficient post‐fire refugia and very low densities of foxes.     

Discordant patterns of genetic and phenotypic differentiation in five grasshopper species codistributed across a microreserve network

Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several codistributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are codistributed across a network of microreserves but show remarkable differences in dispersal‐related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than codistributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large‐scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation.     

Integrating the Rabinowitz rarity framework with a National Plant Inventory in South Korea

Increasingly large presence‐only survey datasets are becoming available for use in conservation assessments. Potentially, these records could be used to determine spatial patterns of plant species rarity and endemism. We test the integration of a large South Korean species record database with Rabinowitz rarity classes. Rabinowitz proposed seven classes of species rarity using three variables: geographic range, habitat specificity, and local population size. We estimated the range size and local abundance of 2,215 plant species from species occurrence records and habitat specificity as the number of landcover types each species’ records were found in. We classified each species into a rarity class or as common, compared species composition by class to national lists, and mapped the spatial pattern of species richness for each rarity class. Species were classed to narrow or wide geographic ranges using 315 km, the average from a range size index of all species (D_max), based on maximum distance between observations. There were four classes each within the narrow and wide range groups, sorted using cutoffs of local abundance and habitat specificity. Nationally listed endangered species only appeared in the narrow‐range classes, while nationally listed endemic species appeared in almost all classes. Species richness in most rarity classes was high in northeastern South Korea especially for species with narrow ranges. Policy implications. Large presence‐only surveys may be able to estimate some classes of rarity better than others, but modification to include estimates of local abundance and habitat types, could greatly increase their utility. Application of the Rabinowitz rarity framework to such surveys can extend their utility beyond species distribution models and can identify areas that need further surveys and for conservation priority. Future studies should be aware of the subjectivity of the rarity classification and that regional scale implementations of the framework may differ.     

Measuring size and composition of species pools: a comparison of dark diversity estimates

Ecological theory and biodiversity conservation have traditionally relied on the number of species recorded at a site, but it is agreed that site richness represents only a portion of the species that can inhabit particular ecological conditions, that is, the habitat‐specific species pool. Knowledge of the species pool at different sites enables meaningful comparisons of biodiversity and provides insights into processes of biodiversity formation. Empirical studies, however, are limited due to conceptual and methodological difficulties in determining both the size and composition of the absent part of species pools, the so‐called dark diversity. We used >50,000 vegetation plots from 18 types of habitats throughout the Czech Republic, most of which served as a training dataset and 1083 as a subset of test sites. These data were used to compare predicted results from three quantitative methods with those of previously published expert estimates based on species habitat preferences: (1) species co‐occurrence based on Beals' smoothing approach; (2) species ecological requirements, with envelopes around community mean Ellenberg values; and (3) species distribution models, using species environmental niches modeled by Biomod software. Dark diversity estimates were compared at both plot and habitat levels, and each method was applied in different configurations. While there were some differences in the results obtained by different methods, particularly at the plot level, there was a clear convergence, especially at the habitat level. The better convergence at the habitat level reflects less variation in local environmental conditions, whereas variation at the plot level is an effect of each particular method. The co‐occurrence agreed closest the expert estimate, followed by the method based on species ecological requirements. We conclude that several analytical methods can estimate species pools of given habitats. However, the strengths and weaknesses of different methods need attention, especially when dark diversity is estimated at the plot level.     

A meta‐analysis of dispersal in butterflies

Dispersal has recently gained much attention because of its crucial role in the conservation and evolution of species facing major environmental changes such as habitat loss and fragmentation, climate change, and their interactions. Butterflies have long been recognized as ideal model systems for the study of dispersal and a huge amount of data on their ability to disperse has been collected under various conditions. However, no single ‘best’ method seems to exist leading to the co‐occurrence of various approaches to study butterfly mobility, and therefore a high heterogeneity among data on dispersal across this group. Accordingly, we here reviewed the knowledge accumulated on dispersal and mobility in butterflies, to detect general patterns. This meta‐analysis specifically addressed two questions. Firstly, do the various methods provide a congruent picture of how dispersal ability is distributed across species? Secondly, is dispersal species‐specific? Five sources of data were analysed: multisite mark‐recapture experiments, genetic studies, experimental assessments, expert opinions, and transect surveys. We accounted for potential biases due to variation in genetic markers, sample sizes, spatial scales or the level of habitat fragmentation. We showed that the various dispersal estimates generally converged, and that the relative dispersal ability of species could reliably be predicted from their relative vagrancy (records of butterflies outside their normal habitat). Expert opinions gave much less reliable estimates of realized dispersal but instead reflected migration propensity of butterflies. Within‐species comparisons showed that genetic estimates were relatively invariable, while other dispersal estimates were highly variable. This latter point questions dispersal as a species‐specific, invariant trait.     

Utilizing a multifaceted approach to assess the current distribution and conservation status of an uncommon species: the golden mouse (Ochrotomys nuttalli) in Florida

Aim

Our goal was to assess the conservation status of the understudied and naturally uncommon habitat specialist, the golden mouse (Ochrotomys nuttalli), at the edge of its range where its historically fragmented habitat has been subjected to severe loss.

Location

Peninsular Florida, north of approximately 27° latitude, USA.

Methods

We used data gathered from museum collections, regional biologists, geographic information systems (GIS) layers, field surveys and DNA sequencing to determine the habitats that best explain the distribution of the species, examine changes in the geographic extent of both the species and its habitats, and compare genetic differentiation between populations occupying disjunct regions. The results from these multiple analyses were combined to assess the conservation status of the species.

Results

Golden mouse occurrence records align well with the distribution of hardwood habitats in Florida. These habitats occur naturally as ‘islands’, but have become increasingly fragmented by anthropogenic land use. Despite habitat loss, the location of the southern range periphery has remained relatively unchanged in location over the past century. Genetic analysis reveals a history of limited dispersal of females among habitat ‘islands’ that likely predates anthropogenic landscape fragmentation. This pattern suggests that isolated populations that are extirpated will have little to no chance of successful recolonization.

Main conclusions

The combined results from multiple analyses produced a more complete picture of the threats faced by this previously data‐deficient species than any single analysis would have. Although the species' southern range limit cannot be shown to have retracted in the face of human expansion, habitat fragmentation clearly has put the species at increased risk. Conservation and management of hardwood habitats are critical to the persistence of the golden mouse at the edge of its range.     

钱江源国家公园体制试点区功能分区对黑麂保护的有效性评估

功能分区是统一协调国家公园不同保护管理目标的主要措施, 对于国家公园的有效管理有重要意义。钱江源国家公园是我国首批国家公园体制试点区之一, 被分为核心保护区、生态保育区、游憩展示区和传统利用区4个部分, 对应不同的保护管理措施。本研究分析了钱江源国家公园体制试点区现有功能分区与其首要保护对象黑麂(Muntiacus crinifrons)的适宜栖息地之间的空间关系。在红外相机调查获取的94个黑麂分布点的基础上, 结合海拔、地形、植被特征、人为活动干扰等15个环境特征变量, 采用MaxEnt模型预测国家公园内黑麂适宜栖息地的空间分布。结果表明, 黑麂倾向于出现在森林较为原始和道路密度较低的区域, 其适宜栖息地面积42.5 km ², 占国家公园总面积的16.9%。其中, 69.3%的黑麂适宜栖息地位于核心保护区, 30.4%位于生态保育区, 表明国家公园现有功能分区能很好地满足黑麂栖息地保护的需求。此结果也证明黑麂可以作为其分布范围内保存较好的亚热带森林生态系统的指示性物种。通过生境恢复、廊道建设和跨省共建促进黑麂栖息地的完整性保护, 是加强该区域黑麂栖息地保护的关键措施。     

Development and field validation of a regional,management‐scale habitat model: A koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional‐scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently‐collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2‐km spatial filter and by modeling separately two subregions separated by the 500‐m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground‐truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground‐truth sites. Similarly, a site habitat quality index at ground‐truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site‐based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field‐validated models of similar resolution would assist in guiding management of conservation‐dependent species.     

Effects of species' ecology on the accuracy of distribution models

In the face of accelerating biodiversity loss and limited data, species distribution models – which statistically capture and predict species’ occurrences based on environmental correlates – are increasingly used to inform conservation strategies. Additionally, distribution models and their fit provide insights on the broad‐scale environmental niche of species. To investigate whether the performance of such models varies with species’ ecological characteristics, we examined distribution models for 1329 bird species in southern and eastern Africa. The models were constructed at two spatial resolutions with both logistic and autologistic regression. Satellite‐derived environmental indices served as predictors, and model accuracy was assessed with three metrics: sensitivity, specificity and the area under the curve (AUC) of receiver operating characteristics plots. We then determined the relationship between each measure of accuracy and ten ecological species characteristics using generalised linear models. Among the ecological traits tested, species’ range size, migratory status, affinity for wetlands and endemism proved most influential on the performance of distribution models. The number of habitat types frequented (habitat tolerance), trophic rank, body mass, preferred habitat structure and association with sub‐resolution habitats also showed some effect. In contrast, conservation status made no significant impact. These findings did not differ from one spatial resolution to the next. Our analyses thus provide conservation scientists and resource managers with a rule of thumb that helps distinguish, on the basis of ecological traits, between species whose occurrence is reliably or less reliably predicted by distribution models. Reasonably accurate distribution models should, however, be attainable for most species, because the influence ecological traits bore on model performance was only limited. These results suggest that none of the ecological traits tested provides an obvious correlate for environmental niche breadth or intra‐specific niche differentiation.     

Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar

Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location Madagascar. Methods Models were developed and evaluated for 13 species of secretive leaf‐tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km² grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species.     

Predicting habitat distribution and frequency from plant species co-occurrence data

Aim Species frequency data have been widely used in nature conservation to aid management decisions. To determine species frequencies, information on habitat occurrence is important: a species with a low frequency is not necessarily rare if it occupies all suitable habitats. Often, information on habitat distribution is available for small geographic areas only. We aim to predict grid‐based habitat occurrence from grid‐based plant species distribution data in a meso‐scale analysis. Location The study was carried out over two spatial extents: Germany and Bavaria. Methods Two simple models were set up to examine the number of characteristic plant species needed per grid cell to predict the occurrence of four selected habitats (species data from FlorKart, http://www.floraweb.de ). Both models were calibrated in Bavaria using available information on habitat distribution, validated for other federal states, and applied to Germany. First, a spatially explicit regression model (generalized linear model (GLM) with assumed binomial error distribution of response variable) was obtained. Second, a spatially independent optimization model was derived that estimated species numbers without using spatial information on habitat distribution. Finally, an additional uncalibrated model was derived that calculated the frequencies of 24 habitats. It was validated using NATURA2000 habitat maps. Results Using the Bavarian models it was possible to predict habitat distribution and frequency from the co‐occurrence of habitat‐specific species per grid cell. As the model validations for other German federal states were successful, the models were applied to all of Germany, and habitat distribution and frequencies could be retrieved for the national scale on the basis of habitat‐specific species co‐occurrences per grid cell. Using the third, uncalibrated model, which includes species distribution data only, it was possible to predict the frequencies of 24 habitats based on the co‐occurrence of 24% of formation‐specific species per grid cell. Predicted habitat frequencies deduced from this third model were strongly related to frequencies of NATURA2000 habitat maps. Main conclusions It was concluded that it is possible to deduce habitat distributions and frequencies from the co‐occurrence of habitat‐specific species. For areas partly covered by habitat mappings, calibrated models can be developed and extrapolated to larger areas. If information on habitat distribution is completely lacking, uncalibrated models can still be applied, providing coarse information on habitat frequencies. Predicted habitat distributions and frequencies can be used as a tool in nature conservation, for example as correction factors for species frequencies, as long as the species of interest is not included in the model set‐up.     

Occupancy and density of a habitat specialist and a sympatric generalist songbird species in Tasmania

Patterns of distribution and abundance of species are dependent on their particular ecological requirements. Taking specialisation into account is important for interpreting population parameters. Here, we evaluate population parameters of an endangered habitat specialist, the forty‐spotted pardalote (Pardalotus quadragintus; dependent on white gum Eucalyptus viminalis in south‐eastern Tasmania), and a sympatric congeneric habitat generalist, the striated pardalote (Pardalotus striatus). We used occupancy models to estimate occupancy of both species, and distance sampling models to estimate population density and size on North Bruny Island. Within their shared habitat (i.e. white gum forest), we also fitted hierarchical distance sampling models to estimate density in relation to fine‐scale habitat features. We show that forty‐spotted pardalotes only occurred in forests where white gums were present, with a mean density of 2.7 birds per hectare. The density of forty‐spotted pardalotes decreased in areas with abundant small trees and trees with dead crowns, but they increased in areas where larger white gums were abundant. The striated pardalote was widespread, but where white gums were present, they occurred at 2.1 birds per hectare, compared to 0.6 birds per hectare in forests where white gums were absent. Within white gum habitat, the relative abundance of forty‐spotted pardalotes and dead trees had a positive effect on the density of striated pardalotes while small trees had a negative effect. Our study reveals that although widespread, the generalist is most abundant in the limited areas of habitat suitable for the specialist, and this indicates the need of future research to look at whether this pattern of occurrence exacerbates competition in resource depleted habitats.     

The dragonfly delusion: why it is essential to sample exuviae to avoid biased surveys

Odonate populations and species numbers are declining globally. Successful conservation requires sound assessments of both odonate distributions and habitat requirements. Odonates have aquatic (larval) and terrestrial (adult) stages, but most surveys that are used to inform conservation managers are undertaken of the adult stage. This study investigates whether this bias towards adult records in odonate recording is misinterpreting the environmental quality of sites. The habitat focus is farmland ponds, a key feature of agricultural landscapes. We tested whether or not, adult, larval and exuvial surveys lead to similar conclusions on species richness and hence on pond quality. Results showed that pond surveys based upon larvae and exuviae are equally suitable for the reliable assessment of presence/absence of odonates, but that adult surveys are not interchangeable with surveys of larvae/exuviae. Larvae were also found at ponds with no emerging individuals due to changes in habitat quality, therefore presence of exuviae remains the only proof of life-cycle completion at a site. Ovipositing females were recorded at all ponds where exuviae were totally absent hence adult surveys over-estimate pond quality and low-quality ponds are functioning as ecological traps. Highly mobile and generalist species were recorded at more locations than other species. Adult surveys also bias recording towards genera, species and populations with non-territorial mate-location strategies. Odonate biodiversity monitoring would benefit from applying the best survey method (exuviae) to avoid wasting valuable financial resources while providing unbiased data, necessary to achieve conservation objectives.     

The generality of habitat suitability models: A practical test with two insect groups

For the design and declaration of conservation areas as well as for planning habitat management it is important to quantitatively know the habitat preferences of the focal species. To take into account the requirements of as many species as possible, it would be of great advantage if one would either (i) find one or several species whose habitat requirements cover those of a large number of other species or if one could (ii) identify a common set of habitat parameters that is important for the occurrence of many species. Ideally such common habitat parameters should be easy to measure. Only then they may be of practical value in applied conservation biology.In this study, we compared the habitat preferences of different insect species (grasshoppers, bush crickets, butterflies, moths) in the same region by applying identical methods. To identify common explanatory variables that predict the occurrence probability of these species, we first tested the transferability of the specific ‘species models’ to other species within the same insect group. We tested how well the incidence of one species can be predicted by the occurrence probability of another species. The ‘best’ models within each group were then tested for transferability between the different groups. Additionally, we tested the predictive power of the predictor variable ‘habitat type’ as an easy and often available measure for conservation practice.Although in the different ‘species models’ different key factors determine habitat suitability, some models were successfully transferred and were able to reasonably predict the distribution of other species. The habitat preferences of the burnet moth Zygaena carniolica were particularly well suited for the prediction of suitable habitats for all other species. In addition, the predictor variable ‘habitat type’ played a dominant role in all models. Models using this aggregated predictor variable may well predict suitable habitat for all species.     

New evidence of unexpectedly high animal density and diet diversity will benefit the conservation of the Critically Endangered western ringtail possum

A comprehensive and contemporary understanding of habitat and resource requirements has been critical to the conservation of multiple taxa and ecosystems globally. Until recently, much of the ecological knowledge that contributes to conservation priorities and strategies for the Critically Endangered western ringtail possum (Pseudocheirus occidentalis) was largely derived from decades‐old observations in peppermint (Agonis flexuosa) and marri‐jarrah (Corymbia calophylla and Eucalyptus marginanta) woodlands in the northern parts of the species range. These observations do not account for more recent evidence of their flexible use of habitat resources in other regions of its range. This may represent a significant conservation opportunity for the species through the identification of additional habitats that warrant protection. In a region where knowledge of their ecology is scarce, we used scat analysis and quantitative spotlighting to determine the diet and density of western ringtail possums in three vegetation types: peppermint, sheoak (Allocasuarina fraseriana) and marri‐eucalypt (C. calophylla, E. marginanta and Eucalyptus staerii) woodlands. Given the species’ reported dependence on peppermint woodlands and dominant canopy species for food sources, we hypothesised that western ringtail possums would be most abundant in this habitat type and that their diet would comprise the foliage of few (≤2 species) canopy species. We found western ringtail possums consumed a higher diversity of plant species than expected (8–14), exhibited dietary preference for non‐dominant canopy species and were present in all sampled vegetation types at substantially higher densities than previously recorded for the region (as high as 17 possums ha^?1). Our results confirm (i) the western ringtail possum is flexible in its use of habitat resources and (ii) the significant conservation value of sheoak and marri‐eucalypt woodlands in the southernmost portion of its distribution.     

Equilibrium or not? Modelling potential distribution of invasive species in different stages of invasion

Aim The assumption of equilibrium between organisms and their environment is a standard working postulate in species distribution models (SDMs). However, this assumption is typically violated in models of biological invasions where range expansions are highly constrained by dispersal and colonization processes. Here, we examined how stage of invasion affects the extent to which occurrence data represent the ecological niche of organisms and, in turn, influences spatial prediction of species’ potential distributions. Location Six ecoregions in western Oregon, USA. Methods We compiled occurrence data from 697 field plots collected over a 9‐year period (2001–09) of monitoring the spread of invasive forest pathogen Phytophthora ramorum. Using these data, we applied ecological‐niche factor analysis to calibrate models of potential distribution across different years of colonization. We accounted for natural variation and uncertainties in model evaluation by further investigating three hypothetical scenarios of varying equilibrium in a simulated virtual species, for which the ‘true’ potential distribution was known. Results We confirm our hypothesis that SDMs calibrated in early stages of invasion are less accurate than models calibrated under scenarios closer to equilibrium. SDMs that are developed in early stages of invasion tend to underpredict the potential range compared to models that are built in later stages of invasion. Main conclusions A full environmental niche of invasive species cannot be effectively captured with data from a realized distribution that is restricted by processes preventing full occupancy of suitable habitats. If SDMs are to be used effectively in conservation and management, stage of invasion needs to be considered to avoid underestimation of habitats at risk of invasion.     

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long‐term stable habitats. The variability of complex, short‐term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.     

Testing the utility of species distribution modelling using Random Forests for a species in decline

Habitat suitability estimates derived from species distribution models (SDMs) are increasingly used to guide management of threatened species. Poorly estimating species’ ranges can lead to underestimation of threatened status, undervaluing of remaining habitat and misdirection of conservation funding. We aimed to evaluate the utility of a SDM, similar to the models used to inform government regulation of habitat in our study region, in estimating the contemporary distribution of a threatened and declining species. We developed a presence‐only SDM for the endangered New Holland Mouse (Pseudomys novaehollandiae) across Victoria, Australia. We conducted extensive camera trap surveys across model‐predicted and expert‐selected areas to generate an independent data set for use in evaluating the model, determining confidence in absence data from non‐detection sites with occupancy and detectability modelling. We assessed the predictive capacity of the model at thresholds based on (1) sum of sensitivity and specificity (SSS), and (2) the lowest presence threshold (LPT; i.e. the lowest non‐zero model‐predicted habitat suitability value at which we detected the species). We detected P. novaehollandiae at 40 of 472 surveyed sites, with strong support for the species’ probable absence from non‐detection sites. Based on our post hoc optimised SSS threshold of the SDM, 25% of our detection sites were falsely predicted as non‐suitable habitat and 75% of sites predicted as suitable habitat did not contain the species at the time of our survey. One occupied site had a model‐predicted suitability value of zero, and at the LPT, 88% of sites predicted as suitable habitat did not contain the species at the time of our survey. Our findings demonstrate that application of generic SDMs in both regulatory and investment contexts should be tempered by considering their limitations and currency. Further, we recommend engaging species experts in the extrapolation and application of SDM outputs.     

Population genetic structure and demographic history of the lone star tick,Amblyomma americanum (Ixodida: Ixodidae): New evidence supporting old records

Range expansions are a potential outcome of changes in habitat suitability, which commonly result as a consequence of climate change. Hypotheses on such changes in the geographic distribution of a certain species can be evaluated using population genetic structure and demography. In this study we explore the population genetic structure, genetic variability, demographic history of, and habitat suitability for Amblyomma americanum, a North American tick species that is a known vector of several pathogenic microorganisms. We used a double digestion restriction site‐associated DNA sequencing technique (dd‐RAD seq) and discovered 8,181 independent single nucleotide polymorphisms (SNPs) in 189 ticks from across the geographic range of the species. Genetic diversity was low, particularly when considering the broad geographic range of this species. The edge populations were less diverse than populations belonging to the historic range, possibly indicative of a range expansion, but this hypothesis was not statistically supported by a test based on genetic data. Nonetheless, moderate levels of population structure and substructure were detected between geographic regions. For New England, demographic and species distribution models support a scenario where A. americanum was present in more northern locations in the past, underwent a bottleneck, and subsequently recovered. These results are consistent with a hypothesis that this species is re‐establishing in this area, rather than one focused on range expansion from the south. This hypothesis is consistent with old records describing the presence of A. americanum in the northeastern US in the early colonial period.     

Species co-occurrence: the case of congeneric species and a causal approach to patterns of species association

Aim To test whether congeneric species are significantly associated with one another in space, either positively or negatively. Also, to provide a framework for a causal investigation of co‐occurrence patterns by a parallel comparison of interactions in geographical and ecological data matrices. Location For the analysis of congeneric species’ co‐occurrences we used 30 matrices covering a wide range of taxa and geographical areas, while for the causal investigation we used the distribution of 50 terrestrial isopod species on 20 islands and 264 sampling stations in the central Aegean archipelago, as well as a number of ecological variables for each sampling station. Methods We developed a software program (cooc ) that incorporates the species‐by‐species approach to co‐occurrence analysis using EcoSim's output of prior null model analysis of co‐occurrence. We describe this program in detail, and use it to investigate one of the most common assembly rules, namely, the decreased levels of co‐occurrence among congeneric species pairs. For the causal analysis, we proceed likewise, cross‐checking the results from the geographical and the ecological matrices. There is only one possible combination of results that can support claims for direct competition among species. Results We do not get any strong evidence for widespread competition among congeneric species, while most communities investigated do not show significant patterns of species associations. The causal analysis suggests that the principal factors behind terrestrial isopod species associations are of historical nature. Some exceptional cases are also discussed. Main conclusions Presence/absence data for a variety of taxa do not support the assembly rule that congeneric species are under more intense competition compared to less related species. Also, these same data do not suggest strong interactions among species pairs, regardless of taxonomic status. When significant species associations can be seen in such matrices, they mainly reflect the effects of history or of habitat requirements.