<Emphasis Type="Italic">Corymbia</Emphasis> phloem phenolics,tannins and terpenoids: interactions with a cerambycid borer

Plant secondary chemistry mediates the ability of herbivores to locate, accept and survive on potential host plants. We examined the relationship between attack by the cerambycid beetle Phoracantha solida and the chemistry of the secondary phloem (inner bark) of two differentially attacked plantation forestry taxa, Corymbia variegata and its hybrid with C. torelliana. We hypothesised that this differential rate of attack may have to do with differences in secondary chemistry between the taxa. We found differences in the bark chemistry of the taxa, both with respect to phenolic compounds and terpenoids. We could detect no difference between bored and non-bored C. variegata trees (the less preferred, but co-evolved host). Hybrid trees were not different in levels of total polyphenols, flavanols or terpenes according to attack status, but acetone extracts were significantly different between bored and non-bored trees. We propose that variations in the bark chemistry explain the differential attack rate between C. variegata and the hybrid hosts.     

An Endangered Longhorn Beetle Associated with Old Oaks and Its Possible Role as an Ecosystem Engineer

Abstract:  For more than 10 years, ecologists have been discussing the concept of ecosystem engineering (i.e., nontrophic interactions of an organism that alters the physical state of its environment and affects other species). In conservation biology, the functional role of species is of interest because persistence of some species may be necessary for maintaining an entire assemblage with many threatened species. The great capricorn ( Cerambyx cerdo ), an endangered beetle listed in the European Union's Habitats Directive, has suffered a dramatic decline in the number of populations and in population sizes in Central Europe over the last century. The damage caused by C. cerdo larvae on sound oak trees has considerable effects on the physiological characteristics of these trees. We investigated the impacts of these effects on the species richness and heterogeneity of the saproxylic beetle assemblage on oaks. We compared the catches made with flight interception traps on 10 oaks colonized and 10 oaks uncolonized by C. cerdo in a study area in Lower Saxony (Germany). Our results revealed a significantly more species-rich assemblage on the trees colonized by C. cerdo . Colonized trees also harbored more red-listed beetle species. Our results suggest that an endangered beetle species can alter its own habitat to create favorable habitat conditions for other threatened beetle species. Efforts to preserve C. cerdo therefore have a positive effect on an entire assemblage of insects, including other highly endangered species. On the basis of the impact C. cerdo seems to have on the saproxylic beetle assemblage, reintroductions might be considered in regions where the species has become extinct.     

Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.     

Nonideal breeding habitat selection: a mismatch between preference and fitness

The selection of breeding sites in heterogeneous habitats should ideally be based on cues closely reflecting habitat quality and thus predicting realized individual fitness. Using long-term population data and data on territory establishment of male Northern Wheatears (Oenanthe oenanthe), we examined whether territory characteristics linked to individual fitness (reproductive performance and survival) also were linked to territory preference. Breeding territories varied in their physical characteristics and their potential effects on reproductive performance, and this variation among territories was correlated from one year to the next. Of all measured territory characteristics (from the focal and the previous year) only territory field layer height predicted individual fitness, i.e., reproductive performance was higher in territories with permanently short rather than growing field layers. Territory preference, instead, was only linked to the size of territory aggregations, i.e., males settled earlier at territory sites sharing borders with several adjacent sites than at those with few or no adjacent sites. This mismatch between territory characteristics linked to fitness and those linked to territory preference was not explained by site fidelity or compensated for by the different fitness components measured. Because the results were not in agreement with an ecological trap scenario, where poor habitats are preferred over high-quality habitats, our results suggest a more general case of nonideal habitat selection. Whereas nonideal selection with respect to territory field layer height may be explained by its poor temporal predictability within the breeding season, the preference for territory aggregations is still open to alternative adaptive explanations. Our study suggests that nonideal habitat selection should be investigated by direct estimates of preferences (e.g., order of territory establishment) and their links to habitat characteristics and fitness components. Furthermore, we suggest that the probability of establishing a territory needs to be included as a factor influencing patterns of habitat selection.     

Density-dependent habitat selection and performance by a large mobile reef fish.

Many exploited reef fish are vulnerable to overfishing because they concentrate over hard-bottom patchy habitats. How mobile reef fish use patchy habitat, and the potential consequences on demographic parameters, must be known for spatially explicit population dynamics modeling, for discriminating essential fish habitat (EFH), and for effectively planning conservation measures (e.g., marine protected areas, stock enhancement, and artificial reefs). Gag, Mycteroperca microlepis, is an ecologically and economically important warm-temperate grouper in the southeastern United States, with behavioral and life history traits conducive to large-scale field experiments. The Suwannee Regional Reef System (SRRS) was built of standard habitat units (SHUs) in 1991-1993 to manipulate and control habitat patchiness and intrinsic habitat quality, and thereby test predictions from habitat selection theory. Colonization of the SRRS by gag over the first six years showed significant interactions of SHU size, spacing, and reef age; with trajectories modeled using a quadratic function for closely spaced SHUs (25 m) and a linear model for widely spaced SHUs (225 m), with larger SHUs (16 standardized cubes) accumulating significantly more gag faster than smaller 4-cube SHUs (mean = 72.5 gag/16-cube SHU at 225-m spacing by year 6, compared to 24.2 gag/4-cube SHU for same spacing and reef age). Residency times (mean = 9.8 mo), indicative of choice and measured by ultrasonic telemetry (1995-1998), showed significant interaction of SHU size and spacing consistent with colonization trajectories. Average relative weight (W(r)) and incremental growth were greater on smaller than larger SHUs (mean W(r) = 104.2 vs. 97.7; incremental growth differed by 15%), contrary to patterns of abundance and residency. Experimental manipulation of shelter on a subset of SRRS sites (2000-2001) confirmed our hypothesis that shelter limits local densities of gag, which, in turn, regulates their growth and condition. Density-dependent habitat selection for shelter and individual growth dynamics were therefore interdependent ecological processes that help to explain how patchy reef habitat sustains gag production. Moreover, gag selected shelter at the expense of maximizing their growth. Thus, mobile reef fishes could experience density-dependent effects on growth, survival, and/or reproduction (i.e., demographic parameters) despite reduced stock sizes as a consequence of fishing.     

Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions

Bioclimatic models are widely used tools for assessing potential responses of species to climate change. One commonly used model is BIOCLIM, which summarises up to 35 climatic parameters throughout a species’ known range, and assesses the climatic suitability of habitat under current and future climate scenarios. A criticism of BIOCLIM is that the use of all 35 parameters may lead to over-fitting of the model, which in turn may result in misrepresentations of species’ potential ranges and to the loss of biological reality. In this study, we investigated how different methods of combining climatic parameters in BIOCLIM influenced predictions of the current distributions of 25 Australian butterflies species. Distributions were modeled using three previously used methods of selecting climatic parameters: (i) the full set of 35 parameters, (ii) a customised selection of the most relevant parameters for individual species based on analysing histograms produced by BIOCLIM, which show the values for each parameter at all of the focal species known locations, and (iii) a subset of 8 parameters that may generally influence the distributions of butterflies. We also modeled distributions based on random selections of parameters. Further, we assessed the extent to which parameter choice influenced predictions of the magnitude and direction of range changes under two climate change scenarios for 2020. We found that the size of predicted distributions was negatively correlated with the number of parameters incorporated in the model, with progressive addition of parameters resulting in progressively narrower potential distributions. There was also redundancy amongst some parameters; distributions produced using all 35 parameters were on average half the size of distributions produced using only 6 parameters. The selection of parameters via histogram analysis was influenced, to an extent, by the number of location records for the focal species. Further, species inhabiting different biogeographical zones may have different sets of climatic parameters limiting their distributions; hence, the appropriateness of applying the same subset of parameters to all species may be reduced under these situations. Under future climates, most species were predicted to suffer range reductions regardless of the scenario used and the method of parameter selection. Although the size of predicted distributions varied considerably depending on the method of selecting parameters, there were no significant differences in the proportional change in range size between the three methods: under the worst-case scenario, species’ distributions decrease by an average of 12.6, 11.4, and 15.7%, using all parameters, the ‘customised set’, and the ‘general set’ of parameters, respectively. However, depending on which method of selecting parameters was used, the direction of change was reversed for two species under the worst-case climate change scenario, and for six species under the best-case scenario (out of a total of 25 species). These results suggest that when averaged over multiple species, the proportional loss or gain of climatically suitable habitat is relatively insensitive to the number of parameters used to predict distributions with BIOCLIM. However, when measuring the response of specific species or the actual size of distributions, the number of parameters is likely to be critical.     

Spatial scale of local breeding habitat quality and adjustment of breeding decisions

Experimental studies provide evidence that, in spatially and temporally heterogeneous environments, individuals track variation in breeding habitat quality to adjust breeding decisions to local conditions. However, most experiments consider environmental variation at one spatial scale only, while the ability to detect the influence of a factor depends on the scale of analysis. We show that different breeding decisions by adults are based on information about habitat quality at different spatial scales. We manipulated (increased or decreased) local breeding habitat quality through food availability and parasite prevalence at a small (territory) and a large (patch) scale simultaneously in a wild population of Great Tits (Parus major). Females laid earlier in high-quality large-scale patches, but laying date did not depend on small-scale territory quality. Conversely, offspring sex ratio was higher (i.e., biased toward males) in high-quality, small-scale territories but did not depend on large-scale patch quality. Clutch size and territory occupancy probability did not depend on our experimental manipulation of habitat quality, but territories located at the edge of patches were more likely to be occupied than central territories. These results suggest that integrating different decisions taken by breeders according to environmental variation at different spatial scales is required to understand patterns of breeding strategy adjustment.     

Eigenanalysis of selection ratios from animal radio-tracking data

The development of methods to analyze habitat selection when resources are defined by several categories (e.g., vegetation types) is a topical issue in radio-tracking studies. The White and Garrott statistic, an extension of the widely used test of Neu et al., can be used to determine whether habitat selection is significant. As well, Manly's selection ratio, a particularly useful measure of resource selectivity by resource users, allows detection of the most strongly selected habitat types. However, when both the number of animals and types of habitat are large, the biologist often has to deal with an excessively large number of measures. In this paper we present a new method, the eigenanalysis of selection ratios, that generalizes these two common methods within the framework of eigenanalyses. This method undertakes an additive linear partitioning of the White and Garrott statistic, so that the difference between habitat use and availability is maximized on the first factorial axes. The eigenanalysis of selection ratios is therefore optimal in habitat selection studies. Although we primarily consider the case where the habitat availability is the same for all animals (design II), we also extend this analysis to the case where the habitat availability varies from one animal to another (design III). An application of this method is provided using radio-tracking data collected on 17 squirrels in five habitat types. The results indicate variability in habitat selection, with two groups of animals displaying two patterns of preference. This difference between the two groups is explained by the patch structure of the study area. Because this method is mainly exploratory, and therefore does not rely on any distributional assumption, we recommend its use in studies of habitat selection.     

Fitness consequences of body-size-dependent host species selection in a generalist ectoparasitoid

In insect parasitoids, offspring fitness is strongly influenced by the adult females choice of host, particularly in ectoparasitoids that attack non-growing host stages. We quantified the fitness consequences of size-dependent host species selection in Dirhinus giffardii, a solitary ectoparasitoid of tephritid fruit fly pupae. We first showed a positive correlation between the size of emerged D. giffardii wasps and the size of their host fruit fly species (in order of decreasing size): Bactrocera latifrons, B. cucurbitae, B. dorsalis or Ceratitis capitata. We then manipulated individual wasps to show that the parasitoid preferred to attack the largest (B. latifrons) to the smallest (C. capitata) host species when provided with a choice, and laid a greater proportion of female eggs in B. latifrons than in C. capitata. There were no differences in developmental time or offspring survival between individuals reared from these two host species. Finally, we compared the foraging efficiency of large versus small wasps (reared from B. latifrons vs C. capitata) under two different laboratory conditions: high versus low host habitat quality, given that realized fecundity in parasitoids may be influenced by either egg-limited or time-limited factors. Under both conditions, large wasps parasitized more hosts than did small ones as a consequence of high searching efficiency in the host-poor habitat, and high capacity for adjusting egg maturation in response to host availability in the host-rich habitat. Considering the flexibility of body growth, the apparent lack of cost of achieving large body size in either development or survival, and the strong dependence of realized reproductive success on a females size, we argue that body size may be a key to understanding evolution of host species selection in ectoparasitoids. We also discuss constraints upon the evolution of size-dependent host species selection in parasitoids.Communicated by D. Gwynne     

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.     

Palatability mapping: a koala's eye view of spatial variation in habitat quality

Ecologists trying to understand the value of habitat to animals must first describe the value of resources contained in the habitat to animals and, second, they must describe spatial variation in resource quality at a resolution relevant to individual animal foraging. We addressed these issues in a study of koalas (Phascolarctos cinereus) in a Eucalyptus woodland. We measured beneficial and deterrent chemical characteristics as well as the palatability of trees using a near-infrared spectroscopic model based on direct feeding experiments. Tree use by koalas was influenced by tree size and foliar quality but was also context-dependent: trees were more likely to be visited if they were surrounded by small, unpalatable trees or by large, palatable trees. Spatial autocorrelation analysis and several mapping approaches demonstrated that foliar quality is spatially structured in the woodland at a scale relevant to foraging decisions by koalas and that the spatial structure is an important component of habitat quality.     

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.     

Who goes first? Condition and danger dependent pioneering in a group-living bark beetle (Dendroctonus ponderosae)

Among group-living organisms, some individuals initiate groups by being the first to attack a prey item or the first to colonize a new settlement site. In the group-living mountain pine beetle (Dendroctonus ponderosae), first attackers (known as pioneers) on live trees suffer higher mortality due to tree defenses than do beetles that join aggregations. This study examined factors that affect an individual’s propensity to initiate an aggregation. When placed on an unoccupied tree, the probability of successfully entering the tree was positively correlated with body condition (residual of mass versus length regression). However, beetles in better condition took longer to initiate tunnel construction than those in poorer condition, suggesting that pioneering is a “desperation” strategy used when low energy reserves preclude further dispersal or when potential trees are rare. These contrasting patterns suggest pioneering is a nonlinear behavioral response, such that beetles with the smallest energy reserves and beetles with the greatest energy reserves both avoid pioneering. We further found that pioneering was more likely when the environment favored success, such as in smaller diameter trees (which may have weaker defenses) and earlier in the season (when the probability of recruiting conspecifics is higher). Our results suggest that pioneers incorporate both internal and external variables in their decision to attack an uncolonized tree.     

Generalized functional responses for species distributions

Researchers employing resource selection functions (RSFs) and other related methods aim to detect correlates of space-use and mitigate against detrimental environmental change. However, an empirical model fit to data from one place or time is unlikely to capture species responses under different conditions because organisms respond nonlinearly to changes in habitat availability. This phenomenon, known as a functional response in resource selection, has been debated extensively in the RSF literature but continues to be ignored by practitioners for lack of a practical treatment. We therefore extend the RSF approach to enable it to estimate generalized functional responses (GFRs) from spatial data. GFRs employ data from several sampling instances characterized by diverse profiles of habitat availability. By modeling the regression coefficients of the underlying RSF as functions of availability, GFRs can account for environmental change and thus predict population distributions in new environments. We formulate the approach as a mixed-effects model so that it is estimable by readily available statistical software. We illustrate its application using (1) simulation and (2) wolf home-range telemetry. Our results indicate that GFRs can offer considerable improvements in estimation speed and predictive ability over existing mixed-effects approaches.     

Nested Subsets and the Distribution of Birds on Isolated Woodlots

Abstract. Distribution of bird species among isolated habitat patches (e.g., woodlots in an agricultural landscape) often appears to be nonrandom; species present in small, species-poor patches also are found in larger patches that support more species. Bird communities form 'nested subsets' (after Patterson & Atmar 1986) if all species found in small faunas also are found in more species-rich assemblages. Occurrence of a nested subset pattern implies an underlying, nonrandom pattern of species distributions. I used computer simulations to analyze the degree of nestedness exhibited by bird communities in east-central Illinois. Results demonstrated that the distribution of bird species breeding in isolated woodlots (1.8 to 600 ha) differed significantly from that predicted by a random distribution model; species assemblages were more "nested" than expected by chance. Most species present in small, species-poor woodlots also were found in larger, species-rich woodlots. As groups, species requiring forest interior habitat for breeding and species wintering in the tropics showed highly nested distributions. In contrast, short-distance migrants and species breeding in forest edge habitat showed more variable distribution patterns, species recorded on smaller woodlots were not always recorded on larger, more species-rich wood-lots. Apparent absences from larger woodlots may have reflected real distribution patterns or insufficient sampling of edge habitats. These results support previous conclusions that small habitat patches are insufficient for preservation of many species.     

Modeling resource selection using polytomous logistic regression and kernel density estimates

Wildlife resource selection studies typically compare used to available resources; selection or avoidance occurs when use is disproportionately greater or less than availability. Comparing used to available resources is problematic because results are often greatly influenced by what is considered available to the animal. Moreover, placing relocation points within resource units is often difficult due to radiotelemetry and mapping errors. Given these problems, we suggest that an animal’s resource use be summarized at the scale of the home range (i.e., the spatial distribution of all point locations of an animal) rather than by individual points that are considered used or available. To account for differences in use-intensity throughout an animal’s home range, we model resource selection using kernel density estimates and polytomous logistic regression. We present a case study of elk (Cervus elaphus) resource selection in South Dakota to illustrate the procedure. There are several advantages of our proposed approach. First, resource availability goes undefined by the investigator, which is a difficult and often arbitrary decision. Instead, the technique compares the intensity of animal use throughout the home range. This technique also avoids problems with classifying locations rigidly as used or unused. Second, location coordinates do not need to be placed within mapped resource units, which is problematic given mapping and telemetry error. Finally, resource use is considered at an appropriate scale for management because most wildlife resource decisions are made at the level of the patch. Despite the advantages of this use-intensity procedure, future research should address spatial autocorrelation and develop spatial models for ordered categorical variables.     

Spatial uncertainty analysis of population models

This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence.     

Integrating habitat-masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments

Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species’ range, but data limitations typically lead to either under- or overestimates (and unnecessarily wide bounds of uncertainty). Fortunately, existing methods in which range maps and land-cover data are used to estimate the area currently holding habitat for a species can be extended to yield an unbiased range of plausible estimates for AOO. Doing so requires estimating the proportion of sites (currently containing habitat) that a species occupies within its range (i.e., prevalence). Multiplying a quantification of habitat area by prevalence yields an estimate of what the species inhabits (i.e., AOO). For species with intense sampling at many sites, presence–absence data sets or occupancy modeling allow calculation of prevalence. For other species, primary biodiversity data (records of a species’ presence at a point in space and time) from citizen-science initiatives and research collections of natural history museums and herbaria could be used. In such cases, estimates of sample prevalence should be corrected by dividing by the species’ detectability. To estimate detectability from these data sources, extensions of inventory-completeness analyses merit development. With investments to increase the quality and availability of online biodiversity data, consideration of prevalence should lead to tighter and more realistic bounds of AOO for many taxonomic groups and geographic regions. By leading to more realistic and representative characterizations of biodiversity, integrating maps of current habitat with estimates of prevalence should empower conservation practitioners and decision makers and thus guide actions and policy worldwide.     

Ecological Correlates of Extinction Proneness in Tropical Butterflies

Abstract:  Widespread and rapid losses of natural habitats and biodiversity have made the identification of extinction-prone species a major challenge in conservation biology. We assessed the relative importance of biologically relevant species traits (e.g., body size, ecological specialization) obtained from published records to determine the extinction probability of butterflies in a highly disturbed tropical landscape (i.e., Singapore). We also developed a taxon-specific model to estimate the extinction proneness of butterflies in Southeast Asia. Logistic regression analyses showed that adult habitat specialization, larval host plant specificity, geographical distribution, sexual dichromatism, and congenor density were significant and independent determinants of butterfly extinctions in Singapore. Among these traits, specificity of larval host plant and adult habitat specialization were the best correlates of extinction risks. We used this phenomenological extinction-regression model to estimate the relative extinction proneness of 416 butterfly species in Southeast Asia. Our results illustrate the utility of available taxon-specific data for a localized area in estimating the extinction proneness of closely related species on a regional scale. When intensive field studies are not forthcoming, especially in regions suffering from rapid biodiversity losses (e.g., Southeast Asia), similar approaches could be used to estimate extinction threats for other taxonomic groups.