Investigating species–environment relationships at multiple scales: Differentiating between intrinsic scale and the modifiable areal unit problem

In ecology, multi-scale analyses are commonly performed to identify the scale at which a species interacts with its environment (intrinsic scale). This is typically carried out using multi-scale species–environment models that compare the relationship between ecological attributes (e.g., species diversity) measured with point data to environmental data (e.g. vegetation cover) for the surrounding area within buffers of multiple sizes. The intrinsic scale is identified as the buffer size at which the highest correlation between environmental and ecological variables occurs. We present the first investigation of how the spatial resolution of remote sensing environmental data can influence the identification of the intrinsic scale using multi-scale species–environment models. Using the virtual ecologist approach we tested this influence using vegetation cover spatial data and a simulated species–environment relationship derived from the same spatial data. By using a simulation model there was a known truth to use as a benchmark to measure accuracy. Our findings indicate that by varying the spatial resolution of the environmental data, the intrinsic scale may be incorrectly identified. In some cases, the errors in the intrinsic scale identified were close to the maximum value possible that could be measured by this experiment. Consequently, multi-scale ecological analyses may not be suitable for distinguishing scale patterns caused by the relationship between an organism and its environment from scale patterns caused by the effect of changing spatial resolution: a phenomenon referred to as the modifiable areal unit problem (MAUP). Thus, observed scale-dependent ecological patterns may be an artefact of the observation of ecological data, not the ecological phenomenon. This study concludes with some suggestions for future work to quantify the effect of the MAUP on multi-scale studies and develop generalisations that can be used to assess when multi-scale analyses have the potential to produce spurious results.     

The study of nest-site preferences in Eleonora’s falcon Falco eleonorae through digital terrain models on a western Mediterranean island

This study addresses nesting-site preferences in Eleonora’s falcon Falco eleonorae by means of geographic information systems and high-quality high-resolution digital terrain models (DTMs). A small western Mediterranean archipelago (Columbretes Islands) with a colony of 34 pairs was chosen as a case study. Overall, 21 grid variables obtained from DTM were considered of which 12 showed a significant effect. Four of them were topographic (i.e. elevation, X-axis aspect, slope and curvature), four climatic (i.e. wind exposure, solar insolation, solar radiation and radiation index), three anthropogne (visibility of lighthouse beam, visibility of antropic zones and distance to antropic zones) and one biotic (vegetation cover). Falcon nests were placed on pixel cells with lower average insolation and radiation than cells without nests, but had higher values of wind exposure. Nests were built on concave sites mainly with an easterly facing aspect and steep slopes. Falcons were shown to respond to human presence as all antropic variables considered had a significant effect. The results have a number of management and conservation implications, because the knowledge of nesting preferences of the species allows the proper design of sanctuaries and an appropriate human use of these areas.     

Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution

Patch context is a way to describe the effect that the surroundings exert on a landscape patch. Despite anthropogenic context alteration may affect species distributions by reducing the accessibility to suitable patches, species distribution modelling have rarely accounted for its effects explicitly. We propose a general framework to statistically detect the occurrence and the extent of such a factor, by combining presence-only data, spatial distribution models and information-theoretic model selection procedures. After having established the spatial resolution of the analysis on the basis of the species characteristics, a measure of anthropogenic alteration that can be quantified at increasing distance from each patch has to be defined. Then the distribution of the species is modelled under competing hypotheses: H₀, assumes that the distribution is uninfluenced by the anthropogenic variables; H₁, assumes the effect of alteration at the species scale (resolution); and H₂, H₃ … H_n add the effect of context alteration at increasing radii. Models are compared using the Akaike Information Criterion to establish the best hypothesis, and consequently the occurrence (if any) and the spatial scale of the anthropogenic effect. As a study case we analysed the distribution data of two insular lizards (one endemic and one naturalised) using four alternative hypotheses: no alteration (H₀), alteration at the species scale (H₁), alteration at two context scales (H₂ and H₃). H₂ and H₃ performed better than H₀ and H₁, highlighting the importance of context alteration. H₂ performed better than H₃, setting the spatial scale of the context at 1 km. The two species respond differently to context alteration, the introduced lizard being more tolerant than the endemic one. The proposed approach supplies reliably and interpretable results, uses easily available data on species distribution, and allows the assessing of the spatial scale at which human disturbance produces the heaviest effects.     

Assessing 3D vs. 2D habitat metrics in a Mediterranean ecosystem for a wiser wildlife management

Although many ecological studies recognize the importance of the three-dimensional complexity of the landscape, only a small number of investigations incorporate it into their methods. Through an empirical study we assess the extent to which habitat metric patterns vary measured by 3D versus 2D methods, and whether it is possible that variations are associated with scale, topographic complexity or specific animal behavior. We analyze areas and potential animals where the use of 3D approaches is most influential for reliable results in ecological studies. This study was carried out in southern Spain, focusing on game estates covering an area of about 2.241 km². The topographical features of the areas were obtained from a digital terrain model (DTM) and a scalable terrain model (STM) generated from Lidar data. The estates were categorized according to a preliminary 3D vs. 2D surface increment index (SI index). Then an experimental repeated measures design was carried out to compare three nested scales from 1 to 4 km square plots. The influence of plot topography on the SI index was analyzed statistically. Plots were also compared pair-wise through a post hoc comparison analysis. In order to establish how 3D affects the metrics of the trajectories travelled by different animal species, we simulated movements of Oryctolagus cunniculus, Cervus elaphus, Canis lupus and Lynx pardinus, which move and behave differently in the study area. We simulated 15 replicate paths per specie, assuming 24 fixes per path. Variations in animal trajectories were analyzed by fitting general linear models (GLMs), which also provide a basic method for estimating the potential errors produced by a simple 2D analysis. We obtained significant differences between the projected and geometric surface areas, with an increase of up to 11.15% and an increase in animal paths length up to 5% using 3D approaches. Landscape complexity, rather than species type, is related to animal path metrics differences. However, in species such as deer and lynx the 3D spatial component is basic for an accurate estimate of path length, especially in heterogeneous landscapes. Altitude and slope range are determining factors for considering the 3D approaches as advisable. Our results confirm that ecological studies ignoring three-dimensional (3D) components run the risk of misinterpretation due to the fact that the bi-dimensional (2D) approach underestimates distances and landscape area. The use of 3D methods provides more accurate results than with 2D approaches, with far-reaching implications for a wiser wildlife management and conservation in Mediterranean ecosystems.     

Assessing climate change associated sea‐level rise impacts on sea turtle nesting beaches using drones,photogrammetry and a novel GPS system

Climate change associated sea‐level rise (SLR) is expected to have profound impacts on coastal areas, affecting many species, including sea turtles which depend on these habitats for egg incubation. Being able to accurately model beach topography using digital terrain models (DTMs) is therefore crucial to project SLR impacts and develop effective conservation strategies. Traditional survey methods are typically low‐cost with low accuracy or high‐cost with high accuracy. We present a novel combination of drone‐based photogrammetry and a low‐cost and portable real‐time kinematic (RTK) GPS to create DTMs which are highly accurate (<10 cm error) and visually realistic. This methodology is ideal for surveying coastal sites, can be broadly applied to other species and habitats, and is a relevant tool in supporting the development of Specially Protected Areas. Here, we applied this method as a case‐study to project three SLR scenarios (0.48, 0.63 and 1.20 m) and assess the future vulnerability and viability of a key nesting habitat for sympatric loggerhead (Caretta caretta) and green turtle (Chelonia mydas) at a key rookery in the Mediterranean. We combined the DTM with 5 years of nest survey data describing location and clutch depth, to identify (a) regions with highest nest densities, (b) nest elevation by species and beach, and (c) estimated proportion of nests inundated under each SLR scenario. On average, green turtles nested at higher elevations than loggerheads (1.8 m vs. 1.32 m, respectively). However, because green turtles dig deeper nests than loggerheads (0.76 m vs. 0.50 m, respectively), these were at similar risk of inundation. For a SLR of 1.2 m, we estimated a loss of 67.3% for loggerhead turtle nests and 59.1% for green turtle nests. Existing natural and artificial barriers may affect the ability of these nesting habitats to remain suitable for nesting through beach migration.     

An Ecological Classification of British Butterflies: Ecological Attributes and Biotope Occupancy

We classify British butterflies using 136 non-biotope associated binary state ecological attributes describing all stages of butterfly life-cycles. Using cluster analysis we identify two groups of woodland species, a group occurring in tall open grassland, another group associated with short sward herb-rich grassland, and a ruderal group. Principal Component and Factor analyses (4 factor solution) are used to identify ecological attributes that determine species groupings. No single attribute or attribute type is responsible for the groupings, which are also insensitive to hostplant type. We use presence/absence data from Butterfly Monitoring Scheme transects in southern Britain to test our classification. On the basis of adult occurrences, similarities within two of the four groups identified from PCA are greater than between groups. Exclusivity between species pairs is also more frequent between groups than within groups. Species' ranges, distributions, biotope range, dispersal ability and recent decline in abundances differ between groups identified by their factor loadings. Ruderal species have large ranges, abundances, extensive mobilities and show little recent decline. The group associated with short sward grassland have the lowest mobilities, and the smallest distributions within their geographic ranges. True woodland species have the smallest biotope range, and the species associated with open areas have the second smallest decline in their distributions. Our ecological classification identifies characteristics of species that determine their habitat requirements and could serve to predict the response of species groups to environmental change on the basis of their ecological attributes. Our method may be of use in identifying the relative importance of ecological attributes of less-well studied taxa and be applicable in less well known geographic regions.     

Which species to conserve: evaluating children’s species-based conservation priorities

We currently have a meager understanding of the species attributes viewed as important for conservation by children, despite the fact that arguments for biodiversity conservation often hinge on the bequest value of species. We conducted a study of children between the ages of 4 and 14 (N = 183) on Andros Island, The Bahamas to determine how they prioritized wildlife species for conservation based on five attributes: endemism, use for hunting and fishing, rapid decline in population size, visibility around their home, and ecological significance. Children tended to rank ecological significance as the most important attribute for prioritizing wildlife for protection, followed closely by endemism, with other attributes being less important and not significantly different from one another. However, participants in a local environmental education program (N = 67) placed greater prioritization to species experiencing rapid population declines. We also found that boys prioritized use for hunting and fishing as more important for conservation than girls, older children placed greater importance on species with declining numbers and less importance on visibility of animals around their house, and children who had previously fished placed greater importance on endemism. These findings help elucidate how children value biodiversity, and suggest children’s conservation priorities may align relatively well with those of conservation biologists, especially after exposure to environmental education. We suggest that better understanding how children prioritize wildlife attributes for conservation can lead to more informed biodiversity conservation decisions and more effective policy implementation, as the perspectives of children can help bridge the gap between public opinion and scientific opinion.     

Understanding the Underlying Mechanism of HA-Subtyping in the Level of Physic-Chemical Characteristics of Protein

The evolution of the influenza A virus to increase its host range is a major concern worldwide. Molecular mechanisms of increasing host range are largely unknown. Influenza surface proteins play determining roles in reorganization of host-sialic acid receptors and host range. In an attempt to uncover the physic-chemical attributes which govern HA subtyping, we performed a large scale functional analysis of over 7000 sequences of 16 different HA subtypes. Large number (896) of physic-chemical protein characteristics were calculated for each HA sequence. Then, 10 different attribute weighting algorithms were used to find the key characteristics distinguishing HA subtypes. Furthermore, to discover machine leaning models which can predict HA subtypes, various Decision Tree, Support Vector Machine, Naïve Bayes, and Neural Network models were trained on calculated protein characteristics dataset as well as 10 trimmed datasets generated by attribute weighting algorithms. The prediction accuracies of the machine learning methods were evaluated by 10-fold cross validation. The results highlighted the frequency of Gln (selected by 80% of attribute weighting algorithms), percentage/frequency of Tyr, percentage of Cys, and frequencies of Try and Glu (selected by 70% of attribute weighting algorithms) as the key features that are associated with HA subtyping. Random Forest tree induction algorithm and RBF kernel function of SVM (scaled by grid search) showed high accuracy of 98% in clustering and predicting HA subtypes based on protein attributes. Decision tree models were successful in monitoring the short mutation/reassortment paths by which influenza virus can gain the key protein structure of another HA subtype and increase its host range in a short period of time with less energy consumption. Extracting and mining a large number of amino acid attributes of HA subtypes of influenza A virus through supervised algorithms represent a new avenue for understanding and predicting possible future structure of influenza pandemics.     

Spatial scale,topography and thermoregulatory behaviour interact when modelling species’ thermal niches

The spatial scale at which climate and species’ occupancy data are gathered, and the resolution at which ecological models are run, can strongly influence predictions of species performance and distributions. Running model simulations at coarse rather than fine spatial resolutions, for example, can determine if a model accurately predicts the distribution of a species. The impacts of spatial scale on a model's accuracy are particularly pronounced across mountainous terrain. Understanding how these discrepancies arise requires a modelling approach in which the underlying processes that determine a species’ distribution are explicitly described. Here we use a process‐based model to explore how spatial resolution, topography and behaviour alter predictions of a species thermal niche, which in turn constrains its survival and geographic distribution. The model incorporates biophysical equations to predict the operative temperature (T_e), thermal‐dependent performance and survival of a typical insect, with a complex life‐cycle, in its microclimate. We run this model with geographic data from a mountainous terrain in South Africa using climate data at three spatial resolutions. We also explore how behavioural thermoregulation affects predictions of a species performance and survival by allowing the animal to select the optimum thermal location within each coarse‐grid cell. At the regional level, coarse‐resolution models predicted lower T_e at low elevations and higher T_e at high elevations than models run at fine‐resolutions. These differences were more prominent on steep, north‐facing slopes. The discrepancies in T_e in turn affected estimates of the species thermal niche. The modelling framework revealed how spatial resolution and topography influence predictions of species distribution models, including the potential impacts of climate change. These systematic biases must be accounted for when interpreting the outputs of future modelling studies, particularly when species distributions are predicted to shift from uniform to topographically heterogeneous landscapes.     

Comparison of pasture types in the tropical Andes: Species composition,distribution, nutritive value and responses to environmental change

Pastoralism is the main land use in the humid tropical Andes of South America. Wide areas of mountain rainforest have been cleared for gaining pastureland. Due to the lack of indigenous useful grasses in the pristine forests, mainly exotic grass species have been used for establishing the pastures. In the Ecuadorian Andes, Axonopus compressus, Melinis minutiflora, Pennisetum clandestinum and Holcus lanatus are common pasture grass species. Their preference for certain microsites resulted in a mosaic of different pasture types, which reflect the differing ecological conditions on the undulating terrain of the mountain slopes. During the last decades, however, another exotic grass species, Setaria sphacelata has widely been introduced which, because of its fast growth on some of the sites could successfully suppress the formerly dominant plant species. With respect to the changing microclimate and cattle stocking rates the present study explored, whether planting Setaria is the best option for the common low-input type of pasture farming in these tropical mountains. In a study over twenty years, the development of four main pasture types, dominated by the above-mentioned grass species was investigated in areas with and without Setaria, and their topographical occurrence on the sloping terrain was analyzed. On forty-eight plots a pairwise (with or without Setaria) comparison of species composition and diversity, biomass production, forage quality and soil properties was performed. Although Setaria grows faster than the other grass species, its productivity was only higher on flat terrain. The nutritive value of the Setaria plots was at best equivalent to that of the former pastures, while species richness was consistently lower. Our results suggest the maintenance of a terrain-adapted diversification of the pastures and in particular the use of Setaria only on flat terrain.     

Modelling deep water habitats to develop a spatially explicit, fine scale understanding of the distribution of the western rock lobster, Panulirus cygnus

Background

The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site.

Methods and Findings

Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables) were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand) and dominant biota (kelp, sessile invertebrates and macroalgae) within a 40 km² area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D² of 64 and an 80% correct classification.

Conclusions

Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical lobster habitats.     

Micro-topography driven vegetation patterns in open mosaic landscapes

Elevation models based on remotely sensed data, especially high-resolution Digital Terrain Models (DTMs) generated using airborne laser scanner (ALS) data, are increasingly being used for the analysis of plant diversity patterns in open landscapes. The vegetation pattern of alkali landscapes shows a high correlation with the position of water table and salt accumulation, which are strongly correlated with topographic variations occurring at a small spatial scale of a few decimetres (micro-topography). In this study we classified eight grassland associations in an alkali landscape based on a DTM generated from ALS data at a pixel size of 0.25 m, and 30 variables derived from the DTM, using an ensemble learning method (Random Forest). Our aim was to identify the micro-topographic variables which could be indicators of vegetation pattern in alkali landscapes. The associations range from Cynodon pastures (short dry grasslands on soil with low salt content) occupying the highest elevations to Beckmannia meadows (wet grasslands on soils with moderate salt content composed of tall grass species) at the lowest elevations, with an elevation difference of approximately 1.2 m between the two. Apart from slope, aspect and curvature, we used Topographic Wetness Index (TWI), and Topographic Position Indices (TPI) at various kernel sizes ranging from 50 cm to 500 m for the classification. The eight associations were also grouped into four aggregated categories — loess grasslands, alkali steppes, open alkali swards and alkali meadows — for further analysis. Vegetation of the studied alkali landscape could be classified into the eight associations with an accuracy of κ: 0.56, and into the four aggregated categories with an accuracy of κ: 0.77 using all the variables. Sequential backward and forward selections of variables were implemented to reduce the number of variables while maximising the accuracies, resulting in increased accuracies of κ: 0.72 and κ: 0.83 for the associations and aggregated categories using six and three variables respectively. TPI at different kernel sizes, previously used to explain vegetation distribution in mountainous areas, was found to be a better indicator of vegetation types than absolute elevations in lowlands where the elevation differences are more subtle. Two characteristic features of the study area — erosional channels and alkali steps — could also be delineated using micro-topographic variables. The results point to the possibility of large-area mapping and monitoring of grasslands where micro-topography is an indicator of vegetation, using only the elevation data from ALS.     

Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data

Despite a growing appreciation of the need to protect sensitive deep sea ecosystems such as cold-water corals, efforts to map the extent of their distribution are limited by their remoteness. Here we develop ecological niche models to predict the likely distributions of cold-water corals based on occurrence records and data describing environmental parameters (e.g. seafloor terrain attributes and oceanographic conditions). This study has used bathymetric data derived from ship-borne multibeam swath systems, species occurrence data from remotely operated vehicle video surveys and oceanographic parameters from hydrodynamic models to predict coral locations in regions where there is a paucity of direct observations. Predictions of the locations of the scleractinian coral, Lophelia pertusa are based primarily upon ecological niche modelling using a genetic algorithm. Its accuracy has been quantified at local (~ 25 km²) and regional scales (~ 4000 km²) along the Irish continental slope using a variety of error assessment techniques and a comparison with another ecological niche modelling technique. With appropriate choices of parameters and scales of analyses, ecological niche modelling has been effective in predicting the distributions of species at local and regional scales. Refinements of this approach have the potential to be particularly useful for ocean management given the need to manage areas of sensitive habitat where survey data are often limited.     

Capybara (Hydrochoerus hydrochaeris) distribution in agroecosystems: a cross-scale habitat analysis

Aim The aim of this study was to understand the spatial distribution of capybara (Hydrochoerus hydrochaeris) according to habitat attributes, using a multiscale approach based on fine‐ and broad‐scale variables in agroecosystems. Location Piracicaba river basin, south‐eastern Brazil (22°00′–23°30′ S; 45°45′–48°30′ W). Methods Potential habitats for capybara were selected in order to evaluate species presence/absence from October 2001 to December 2002. In each site, habitat attributes were sampled in the field (fine scale) and from GIS maps (broad scale) in terms of their presence or absence close to water. The variability of land cover between study sites was described by principal components analysis. Chi‐square tests were calculated for capybara presence/absence and the presence of each habitat attribute. A linear discriminant function analysis was used to describe to what extent the species’ presence could be explained by habitat attributes. Results The species presence was predominantly related to flat open areas (slope ranging from 0% to 6%) (χ² = 37.054, d.f. = 4, P < 0.001), covered by sugar cane or cultivated pasture (χ² = 84.814, d.f. = 9, P < 0.001). Terrain curvature, water meadows, aquatic vegetation, forest cover and open areas resulted in the best combination of variables, explaining 69.7% of capybara occurrence in the study sites in this river basin. Main conclusions Capybaras are widespread in the Piracicaba river basin, except in elevated areas. The spatial distribution of capybara was associated with the main types of land cover in the river basin – sugar cane plantations or pasture – both key food sources for capybara. This probably explains the species’ recent abundance in the region, since an intensive process of landscape alteration has taken place in this region owing to the expansion of agriculture in recent decades. These results may be useful in understanding the relationship between recent landscape modifications and the species’ population expansion in agroecosystems.     

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments.     

Characterizing soil seed banks and relationships to plant communities

Estimates of soil seed banks are important to many ecological investigations and plant conservation, yet seed banks are among the most difficult plant community attributes to accurately quantify. To compare extraction and emergence seed bank characterization methods, we collected 0- to 5-cm soil seed bank samples and measured plant community composition in six microsite types (below different perennial plant species and interspaces) at 10 field sites in the Mojave Desert, USA. Extraction detected five times more species sample^?1 and orders of magnitude greater seed density than emergence, though evaluating viability of extracted seed was not straightforward. Only 13 % of 847 tested seeds from extraction emerged in follow-up assays. Considering all sites, species detection was more similar between methods: 21 taxa for emergence and 28 for extraction. Results suggest that: (i) capturing microsite variation is critical for efficiently estimating site-level desert seed banks; (ii) method comparisons hinged on the scale of analysis for species richness, as differences in species detection between methods diminished when increasing resolution from the sample to the regional scale; (iii) combining data from all seed bank methods provided the strongest correlation with vegetation; and (iv) improving knowledge of seed germinability is important for advancing both seed bank methods, including for extraction to evaluate the proportion of extracted seeds that are viable. Multifactor approaches that balance several effectiveness measures (e.g., both seed density and species detection at multiple scales) and procedural challenges are most likely to accurately represent complexity in tradeoffs for choosing methods to quantify soil seed banks.     

New approach for evaluating habitat stability using scarce records for both historical and contemporary specimens: a case study using Carabidae specimen records

Natural history collections, such as specimen records, are crucial resources for conservation and habitat management. However, these data are usually scarce compared to physical environmental data (e.g., digital terrain maps) that we often have little species data and a lot of physical environmental data with which to evaluate habitats. In this paper, we propose a method for evaluating habitat stability using scarce natural history records and abundant physical environmental data. We used both historical and contemporary specimen records of carabid beetles (areas in which records of the same species were recorded during both periods) and evaluated the attributes of these areas using terrain characteristics. We found two common terrain characteristics among the occupied areas: large total river length and low variation in elevation. These terrain characteristics suggest that habitats of carabid species have been conserved in disturbed and wet environments for a long time. These results are consistent with the ecological characteristics of carabid beetles. Our study shows that scarce natural history collections, combined with ingenuity, can be useful for evaluating habitats.     

Geographic patterns of species richness of diurnal raptors in Venezuela

Knowledge of a species’ geographic distribution is crucial to assessing its vulnerability. It is also important to know if protected areas provide effective protection for raptor species. Here, we examine the species richness (S) patterns, factors predicting S and the effectiveness of protected areas (EPA) in the conservation of diurnal raptors in Venezuela. We modeled geographic distributions (SDM) of 64 raptor species using ecological niche models. Nine climatic and seven landscape metrics were used as environmental predictors. SDM were stacked to examine S and predictors of S were investigated using regression models. This study evaluated S patterns in the 13 bioregions defined for Venezuela. A gap analysis was performed to evaluate the EPA in the conservation of raptor diversity. Forty species showed a continuous distribution, whereas as disjunct distributions were observed in 24 species. Species richness differed among bioregions; six pairwise compared bioregions did not show differences. Guyana Massif and the mountains of northern Venezuela had the highest species richness. Landscape features, specifically canopy height, land cover and terrain slope explained most of the species richness. Environmental heterogeneity affected the distribution of S and is therefore important in conservation planning for Neotropical raptors. Responses from environmental variables used to predict S were scale dependent; it is necessary to standardize methods/experimental design to study the biogeography of raptors. Priority-setting for the conservation of raptors in Venezuela must consider restricted range species, even if they are not threatened. A new territorial ordering is urgent to improve the protection of this group of birds.     

Host range of Cybocephalus flavocapitis and Cybocephalus nipponicus,two potential biological control agents for the cycad aulacaspis scale,Aulacaspis yasumatsui

Host-range and host-specificity tests were performed with Cybocephalus flavocapitis T. R. Smith (Coleoptera: Cybocephalidae) and Cybocephalus nipponicus Endrödy-Younga (Coleoptera: Cybocephalidae), two biological control candidates against the invasive cycad aulacaspis scale, Aulacaspis yasumatsui Takagi (Hemiptera: Diaspididae). Seventeen native scale species plus the invasive A. yasumatsui scale were tested in growth chambers using no-choice tests and hosts suitable for each of the two predatory beetles. The results revealed that the two Cybocephalus beetles, one imported species from Thailand and one native species, both fed on relatively similar scale prey species. Additionally, the adult beetles of these two species oviposited only on Diaspididae scales. The results showed that both Cybocephalus beetles may share a similar host niche in Taiwan.