The impact of urban development on butterflies within a city region

The effect of urban development on butterfly species' richness and species' incidence is tested for the Greater Manchester conurbation and two sample areas, mapped at finer scales, within the southern part of the conurbation. The tests include measures of bias for recording effort (number of visits). Species' richness is found to increase with percentage urban cover for Greater Manchester (tetrad scale) and decrease with urban cover for the two sample areas in South West Manchester (1 km scale) and the Mersey Valley (100 m scale). For Greater Manchester, the increase in species' richness with increased urban cover is largely explained by lower species' richness at higher altitude in the Pennines bounding the conurbation. For the two sample areas, decreasing species' richness associated with increasing urban cover corresponds with reductions in the areas of a number of semi-natural habitats, hostplants and nectar sources. Despite these statistically significant correlations, the impact of urban cover on species' richness is weak. The maximum loss rate identified anywhere within the region is 0.81 species per 10% change in urban cover for South West Manchester. This finding may reflect on the generally low species diversity of the region. However, these results could be influenced by recording and sampling artefacts, particularly the failure of mapping programmes to distinguish vagrant individuals from breeding populations and a bias of records to vagrants. This is supported by the higher correlations between species' incidence and nectar sources than between species' incidence and their hostplants. Adult butterflies are opportunistic nectar users and nectar sources are more widely spread and thus less influenced by urban development than are specific butterfly hostplants. The finding may also reflect on the capacity of most of the butterfly species to breed successfully on tiny areas of hostplant existing within extensively built-up areas. Moreover, the capacity of butterfly species to persist by using small fragments of hostplants would be enhanced by vagrancy. If this is indeed the case, it is a finding that would support the value of small patches in butterfly metapopulations, albeit ones comprising incomplete complements of resources required during the life cycle. The incidence of most species decreases with increase in urban cover. Multivariate analyses indicate that this is owing to corresponding declines in hostplant-habitats and nectar sources. Five species increase with urban cover, but none attain formal significance. Associations among hostplants and habitat variables in a principal components analysis suggest that, in three cases (Pieris brassicae, P. rapae, Celastrina argiolus), this is owing to increasing areas of their hostplants within urban environments.     

Bias in Butterfly Distribution Maps: The Effects of Sampling Effort

Data from the Greater Manchester Butterfly Atlas (UK) reveal a highly significant and substantial impact of visits on both species' richness and species' incidence in squares. This effect has been demonstrated for three different zones mapped at different scales. The significant impact of number of visits persists when data are amalgamated for coarser scales. The findings demonstrate that it is essential for distribution mapping projects to record data on recording effort as well as on the target organisms. Suggestions are made as to how distribution mapping may be improved, including a geographically and environmentally representative structure of permanently monitored squares and closer links between distribution mapping and the Butterfly Monitoring Scheme (BMS), which primarily monitors changes in butterfly populations. The benefit to conservation will be data that can be better used to analyse the reasons for changes in ranges and distributions, fundamental for determining priorities and policy decisions.     

Progressive bias in species status is symptomatic of fine-grained mapping units subject to repeated sampling

Atlas maps of butterflies invariably fail to distinguish the status of records, that is, whether they are observations of breeding populations or vagrant individuals. Yet, for conservation purposes, it is clearly important to know whether records relate to breeding populations in suitable habitats or not. The high mobility of butterfly adults carries two expectations. First, vagrants will frequently be recorded within grid squares, particularly when mapping is fine grained. Second, the frequency of vagrants is likely to be higher in mapping units comprising biotopes with few butterfly habitats, than in those rich in butterfly habitats, if only because there is a greater regional pool of potential vagrants for biotopes depleted in butterfly habitats. It follows that with repeated sampling of squares or biotopes differences in species breeding status will be cumulative between those rich and poor in butterfly habitats. In this paper, these predictions have been tested using data from 30, 1 ha grid squares on Alderley Edge Site of Special Scientific Interest (SSSI) (UK), half of which are in woodland (few butterfly habitats) and half with open habitats (non-woodland; rich in butterfly habitats). Butterflies have been recorded during 38 visits over 4 years. Within squares, vagrants have been distinguished from breeding species on the basis of the presence of larval hostplants and other suitable resources for seasonal maintenance. Owing to the occurrence of vagrants, number of breeding species was found to be significantly fewer than total species in mapping units. Vagrants were found to be significantly more abundant in woodland squares, which contain few species larval hostplants, than in squares dominated by open biotopes with many species larval hostplants. Repeated sampling resulted in a cumulative increase in the frequency of vagrant species. Furthermore, the relative frequency of vagrants increased at a greater rate in woodland squares compared to non-woodland squares. Suggestions are made as to how recording for atlases may be improved.     

Recording effort biases the species richness cited in plant distribution atlases

This paper explores potential biases due to recording effort in the species richness (number of vascular plant species) recorded in grid-mapping projects. In this study, we review 80 regional and national grid Central European Basic Area (CEBA) mapping projects on the vascular plant flora of Central Europe. The measures of recording effort used were the duration of the mapping project, resolution of the mapping grid and number of botanists involved. Furthermore, several environmental and geographic factors associated with the variation in species richness were used as covariables: the number of phytosociological units in the Map of Potential Natural Vegetation of Europe, altitudinal range, annual precipitation, mean January and June temperatures and geographical location of the study areas. The effects of individual factors on species richness were compared by multiple regression and hierarchical partitioning. Both methods indicated a bias in observed species richness due to recording effort. Multiple regression indicated a significant role of duration of study, and hierarchical partitioning revealed significant effects of duration, number of botanists and used resolution. Of the variation in the total number of species recorded, 8% was attributed to the duration of mapping, 9% to the used resolution, and 7% to the number of botanists involved in mapping. However, this bias was scale-dependent. Although the sampling effect can be neglected on a broad scale, on a finer scale a significant amount of the variation in plant species richness can be ascribed to recording effort. This indicates the need for a standard approach in mapping and analysing patterns of species richness.     

Bias in Butterfly Distribution Maps: The Influence of Hot Spots and Recorder's Home Range

We use data from the Mersey Valley zone (3×2km area; N = 600Iha squares) of the Greater Manchester butterfly atlas to investigate whether recorder visits are biased by access (viz. distance from recorder's home base) and by the locations of potential hot spots. In a multiple regression analysis, visits were found to correlate significantly both with distance from home base of the recorder and with the mean and maximum number of species found in squares. Sites close to the home base of the recorder were visited more frequently than those further afield and squares with more species were visited more frequently than those squares with fewer species. Visits were also made significantly more frequently to squares with greater numbers of butterfly resources (e.g. hostplants, nectar). Furthermore, recording is biased to and away from distinct land uses, which vary significantly in species richness. Reasons are given why these biases are to be expected at all scales. The message is that future distribution mapping should be based on rigorous sampling approaches.     

是否低估了本地热带蝴蝶区系成分的丰富度?样带观察结果的剖析

作者利用在菲律宾吕宋岛Calumpang Lejos (Indang, Cavite) 地区以样带法收集的蝴蝶种数记录, 检验了类群记录是否低估了当地种数丰富度和多样性。在两年间长达340 h的457个样带调查中, 没有出现种数积累曲线突破情况。折叠估计、有偏纪录、丰富度的地区变化以及与群落生境有关的相对多度均支持当地蝴蝶区系丰富度被低估的观点。在样带调查中, 多样性及体色类型记录具有误差。这些误差反映在发现日期以及同种的科学命名日期, 并且涉及到菲律宾吕宋岛发现的所有物种, 且与蝴蝶的体型大小有关。数量较少、体型较小和不显眼的种类发现得较晚。在分类上亦有误差, 弄蝶科和灰蝶科比粉蝶科和蝶科稀少、体小且不显眼, 发现和命名较晚。翅型特征不明显的种类具有体型较小的趋势, 使所做的形态特征记录产生错误。我们发现菲律宾吕宋岛Calumpang Lejos (Indang, Cavite) 地区的稀有种类体型明显较小和特征较不明显。由于区域性样带调查偏差包括了灰蝶科但未包括弄蝶科, 因此偏差源于对树冠型蝴蝶种类的记录偏低。本文讨论了在其它生物区系以及热带蝴蝶保育上的应用, 认为今后需要使用误差小的新技术进行动物区系中物种丰富度的可靠估计。     

Water–energy balance and the geographic pattern of species richness of western Palearctic butterflies

Abstract. 1. Using two sources of data to estimate butterfly species richness, the potential influences of 11 environmental variables on the richness gradient of butterflies in western/central Europe and northern Africa were examined with multiple regression and spatial autocorrelation analysis. A measure of water–energy balance, actual evapotranspiration, explained 79% of the variance in butterfly species richness using data derived from range maps, and 72% of the variance using data derived from grid‐based distribution maps. All other variables explained less than 4% of the variance in the regression models and differed depending on the data source. 2. The spatial analysis indicated that actual evapotranspiration successfully removed most of the spatial autocorrelation in both richness data sets at all spatial scales, confirming the ability of the model to account for the spatial pattern in butterfly richness. 3. Plant species richness, a rarely tested variable hypothesised to be an important determinant of herbivore diversity, was weakly associated with butterfly richness, suggesting that it has little or no direct influence on butterfly richness. 4. A historical variable, the length of time that areas have been exposed for recolonisation after the retreat of the ice sheet following the last ice age, was also not associated with richness patterns, indicating that butterfly richness is in equilibrium with contemporary climate. 5. It was not possible to confirm a result reported for Canadian butterflies that land cover diversity is a strong predictor of butterfly richness, possibly because of methodological differences in the studies, differences in the range of climates found in Canada and the western Palearctic, or because of the highly modified landscape characteristic of Europe. 6. Water–energy balance offers a parsimonious explanation for the butterfly richness gradient in this region, operating partially indirectly via effects on plant productivity and partially directly via physiological effects on butterflies, and this conclusion is robust to differences in the types of distribution maps used to estimate richness patterns.     

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 × 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike’s Information Criterion corrected for small sample size (AIC_c), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions.     

Human impacts on environment–diversity relationships: evidence for biotic homogenization from butterfly species richness patterns

Aim Broad‐scale spatial variation in species richness relates to climate and physical heterogeneity but human activities may be changing these patterns. We test whether climate and heterogeneity predict butterfly species richness regionally and across Canada and whether these relationships change in areas of human activity. Location Canada. Methods We modelled the ranges of 102 butterfly species using genetic algorithms for rule‐set production (GARP). We then measured butterfly species richness and potentially important aspects of human activity and the natural environment. These were included in a series of statistical models to determine which factors are likely to affect butterfly species richness in Canada. We considered patterns across Canada, within predominantly natural areas, human‐dominated areas and particular ecozones. We examined independent observations of butterfly species currently listed under Canada's endangered species legislation to test whether these were consistent with findings from statistical models. Results Growing season temperature is the main determinant of butterfly species richness across Canada, with substantial contributions from habitat heterogeneity (measured using elevation). Only in the driest areas does precipitation emerge as a leading predictor of richness. The slope of relationships between all of these variables and butterfly species richness becomes shallower in human‐dominated areas, but butterfly richness is still highest there. Insecticide applications, habitat loss and road networks reduce butterfly richness in human‐dominated areas, but these effects are relatively small. All of Canada's at‐risk butterfly species are located in these human‐dominated areas. Main conclusions Temperature affects butterfly species richness to a greater extent than habitat heterogeneity at fine spatial scales and is generally far more important than precipitation, supporting both the species richness–energy and habitat heterogeneity hypotheses. Human activities, especially in southern Canada, appear to cause surprisingly consistent trends in biotic homogenization across this region, perhaps through range expansion of common species and loss of range‐restricted species.     

Trends in butterfly species richness in response to the peninsular effect in South Korea

Aim The Korean peninsula is elongated in shape and is connected to the Asian continent on the north. The peninsular effect – a decline in species density or richness as a function of distance from the mainland base (towards the distal tip) of a peninsula – was evaluated for plants and animals in different peninsulas. The aims of the present study were to describe the pattern of butterfly species diversity and to determine what factors may be responsible for this pattern along the Korean peninsula. The distribution pattern of butterfly species in South Korea before and after the Korean War was also investigated. Location South Korea (34–38° N, 126–129° E). Methods Forty‐three quadrats, each 1/2° latitude by 1/2° longitude, and three data sets – butterfly distribution data from 1938 to 1950, butterfly distribution data from 1976 to 1999, and the combined data – were analysed. The influence of four variables – latitude, longitude, area and maximum altitude – on each quadrat was investigated using multiple regression analysis. Results and conclusion The analyses revealed a marked peninsular effect: there was a significant positive correlation between butterfly species richness and latitude. Additionally, habitat diversity, expressed as maximum altitude, was significantly correlated with butterfly species richness. I conclude that both the geographical orientation and habitat diversity contribute to butterfly species diversity across South Korea. Comparison of ranges between the older and recent data sets suggests that geographical distributions of several species are dramatically reduced in size. These species may be used for future conservation activities in South Korea.     

Climate-based models of spatial patterns of species richness in Egypt's butterfly and mammal fauna

Aim  Identifying areas of high species richness is an important goal of conservation biogeography. In this study we compared alternative methods for generating climate-based estimates of spatial patterns of butterfly and mammal species richness.
Location  Egypt.
Methods  Data on the occurrence of butterflies and mammals in Egypt were taken from an electronic database compiled from museum records and the literature. Using M axent , species distribution models were built with these data and with variables describing climate and habitat. Species richness predictions were made by summing distribution models for individual species and by modelling observed species richness directly using the same environmental variables.
Results  Estimates of species richness from both methods correlated positively with each other and with observed species richness. Protected areas had higher species richness (both predicted and actual) than unprotected areas.
Main conclusions  Our results suggest that climate-based models of species richness could provide a rapid method for selecting potential areas for protection and thus have important implications for biodiversity conservation.     

Influences of interpolation of species ranges on elevational species richness gradients

Interpolation of species ranges has been a common approach to compensate for the unevenness or incompleteness in sampling effort in studies of geographic species richness gradients. However, potential biases introduced by this estimation method remain unclear. Here, we presented an explicit examination of the influences of one‐dimensional interpolation on elevational species richness gradients, and discussed potential causes and processes of these influences. We conducted intensive surveys of birds along the elevational gradients of the Ailao Mountains, southwestern China, and compared richness patterns based on interpolation with raw data as well as estimated data from rarefaction and Chao1 non‐parametric estimator; we also compared results of multiple linear regressions and hierarchical partitioning analyses explaining these four measures of richness. Actual evapotranspiration (AET) and the mid‐domain effect (MDE) were highly correlated and separately provided a good potential explanation for the unimodal richness pattern in the Ailao Mountains, with modifying and suppressive effects of other variables such as area. Interpolation consistently and significantly increased the effects of AET/MDE, while it reduced contributions of area and human disturbance. Our results demonstrated that while compensating for biases in sampling effort, interpolation may also spuriously fill genuine distribution gaps, and tend to underestimate the effects of the non‐monotonic or discontinuous influencing factors that are responsible for these gaps, and overestimate the effects of other factors actually suppressed by these factors. These influences were most strong for species with relatively medium elevational ranges. We conclude that at the regional scale, interpolation method is a potential source of bias in identifying and explaining species richness gradients and should be used with careful consideration. It may be advantageous to adopt other robust estimation methods besides interpolation to gain a more accurate assessment of species richness and a more objective understanding of their underlying mechanisms.     

Butterfly species richness in the north-west Mediterranean Basin: the role of natural and human-induced factors

Aim We developed a model enabling us to evaluate the contribution of both natural and human‐related factors to butterfly species richness in Catalonia, a Mediterranean area that harbours one of the most diverse butterfly faunas in Europe. Location The study was carried out in Catalonia (north‐east Iberian Peninsula), a region of 31,930 km² lying between the Pyrenees, the Ebro depression and the Mediterranean sea. Methods Data from the Catalan Butterfly Monitoring Scheme were used to assess butterfly species richness from 55 transects spread all over the region. Three groups of environmental variables likely to affect the presence of butterfly species were calculated, above all from geographic information system data: (1) climatology and topography, (2) vegetation structure and (3) human disturbance. Because climatic and topographic variables are expected to be strongly correlated, we first performed a principal component analysis (PCA) to create a summarizing factor that would account for most of the variance within this set of variables. Subsequently, a backward stepwise multiple regression was performed in order to assess the effects of environmental factors on butterfly species richness. Results A total of 131 species were detected in the monitoring transects, representing 75.7% of the butterfly fauna known from Catalonia. Mean species richness per transect and per year was 41.4, although values varied greatly among sites (range: 14–76.8). The final regression model explained more than 80% of the total variance, which indicated a strong association between butterfly species richness and the studied environmental factors. The model revealed the very important contribution of climatic and topographic variables, which were combined into a single factor in the PCA. In contrast to what has been found in other, more northerly countries, species richness was negatively correlated with temperature and positively correlated with rainfall, except for extreme cold and wet conditions. This may be a consequence of the predictably adverse effects of the Mediterranean summer drought on herbivorous insects, and the fact that the limits of distribution of many butterflies correlate well with climatic variables. Human disturbance (defined as the proportion of urban and agricultural landscape cover in buffer areas of 5 km around the transect sites) was the second most important predictor for species richness. We found that a significant decrease in species numbers was associated with an increase in human pressure, a finding that indicates that not only building development, but also modern‐day agricultural practices are detrimental to the conservation of Mediterranean butterflies. Surprisingly, vegetation variables had an almost negligible effect on butterfly species richness. Main conclusions Our findings strongly indicate that the current motors of global change will have a negative effect on Mediterranean butterfly assemblages. First, changes in land‐use are transforming and fragmenting the landscape into an inhospitable and less permeable matrix for butterflies. Secondly, the negative correlation between species richness and temperature will lead to a predictable loss of diversity over the coming years, as predicted in the most plausible scenarios of climate change. Considering the high butterfly richness characterizing the Mediterranean Basin, this future trend will pose a serious threat to biodiversity.     

Finessing atlas data for species distribution models

Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This study outlines the incorporation of existing knowledge into a conventional approach to predict the distribution of Bonelli’s eagle (Aquila fasciata) at a resolution 100 times finer than available atlas data. Location Malaga province, Andalusia, southern Spain. Methods A Bayesian expert system was proposed to utilize the knowledge from distribution models to yield the probability of a species being recorded at a finer resolution (1 × 1 km) than the original atlas data (10 × 10 km). The recorded probability was then used as a weight vector to generate a sampling scheme from the species atlas to enhance the accuracy of the modelling procedure. The maximum entropy for species distribution modelling (MaxEnt) was used as the species distribution model. A comparison was made between the results of the MaxEnt using the enhanced and, the random sampling scheme, based on four groups of environmental variables: topographic, climatic, biological and anthropogenic. Results The models with the sampling scheme enhanced by an expert system had a higher discriminative capacity than the baseline models. The downscaled (i.e. finer scale) species distribution maps using a hybrid MaxEnt/expert system approach were more specific to the nest locations and were more contrasted than those of the baseline model. Main conclusions The proposed method is a feasible substitute for comprehensive field work. The approach developed in this study is applicable for predicting the distribution of Bonelli’s eagle at a local scale from a national‐level occurrence data set; however, the usefulness of this approach may be limited to well‐known species.     

Elevational species richness patterns for vascular plants on Mount Kinabalu, Borneo

Aim  We quantify the elevational patterns of species richness for all vascular plants and some functional and taxonomic groups on a regional scale on a tropical mountain and discuss some possible causes for the observed patterns.
Location  Mount Kinabalu, Sabah, Borneo.
Methods  A data base containing elevational information on more than 28,000 specimens was analysed for vascular plant distribution, taking into account sampling effort. The total species richness pattern was estimated per 300-m elevational interval by rarefaction analyses. The same methods were also applied to quantify species richness patterns of trees, epiphytes, and ferns.
Results  Total species richness has a humped relationship with elevation, and a maximum species richness in the interval between 900 and 1200 m. For ferns and epiphytes the maximum species richness is found at slightly higher elevations, whereas tree species did not have a statistically significant peak in richness above the lowest interval analysed.
Main conclusions  For the first time a rigorous estimate of an elevational pattern in species richness of the whole vascular plant flora of a tropical mountain has been quantified. The pattern observed depends on the group studied. We discuss the differences between the groups and compare the results with previous studies of elevational patterns of species richness from other tropical areas. We also discuss the methods used to quantify the richness pattern and conclude that rarefaction gives an appropriate estimate of the species richness pattern.     

Moths count: recording moths for conservation in the UK

Insects are under-represented in current assessments of biodiversity loss at global and national scales. Butterflies, and a few other insect taxa, have been used as indicators of biodiversity change and as flagships for conservation, especially in temperate zones, but these groups are typically species-poor and may not be representative of insects as a whole. Macro-moths, on the other hand, are an important component of UK biodiversity, in terms of both species richness and ecosystem function. Moth abundance has decreased significantly in the UK and there is rapidly growing interest in the surveillance and monitoring of macro-moths among amateur and professional scientists. The Moths Count project was instigated to raise awareness of moths, increase moth recording and set up a long-term National Moth Recording Scheme for c.900 species of macro-moth in the UK. Since 2006, Moths Count has promoted moths to millions of people, trained and engaged thousands in recording and collated over eight million species distribution records into the National Moth Recording Scheme. These data, though incomplete at present, are already contributing to assessments of biodiversity loss and to conservation initiatives. We present initial results which show that substantial changes are already evident for macro-moths in the UK. The northern range margins of a sample of 12 species have shifted northwards by 194.8 km on average between 1982 and 2009 (7.8 km year^?1 over the 25 years between survey mid-points). Provisional distribution trends (not corrected for variation in recording effort) were calculated for 43 species and the results corroborated both positive and negative population-level changes assessed previously.     

区域变动尺度上不同生境类型及环境因子对西双版纳蝴蝶多样性的影响

【目的】生境类型和环境因子对物种分布和维持具有重要的影响。本研究通过分析不同生境类型对蝴蝶群落多样性及其群落结构影响的差异,以及环境因子对蝴蝶物种丰富度和多度的影响,为区域变动尺度蝴蝶多样性维持机制的研究奠定基础。【方法】于2019年8月和10月,在西双版纳地区采用样线法,调查了天然林、次生林、复合生境、人工林和农田5种生境中蝴蝶的物种,分析了蝴蝶群落多样性、群落结构相似性及物种丰富度和多度与环境因子的关系。【结果】2019年从西双版纳共采集蝴蝶2 226头,隶属于11科98属175种,在西双版纳州级尺度上蝴蝶物种丰富度高于县域尺度。在西双版纳州级尺度上,蝴蝶的物种丰富度和多度在5种生境间存在显著差异,而在县域尺度上,物种丰富度、多度和Chao 1物种丰富度估计值没有一致性规律。群落结构相似性结果显示,在西双版纳州级尺度上,蝴蝶群落结构在不同生境类型间存在极显著差异,在县域尺度上,仅勐腊区域蝴蝶群落结构在不同生境类型间存在显著差异。蝴蝶物种丰富度和多度不仅受到生境类型的影响,还受到温度、年均降水和海拔的影响。【结论】本研究结果表明,在区域变动尺度上,生境类型对西双版纳蝴蝶的多样性的影响较大,而温度、年均降水和海拔是维持蝴蝶物种多样性的重要因素。这些发现对当前人类导致的生境丧失和气候变化时代生物多样性的保护具有重要意义。     

Biotic interactions boost spatial models of species richness

Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts.     

Negative relationships between species richness and evenness render common diversity indices inadequate for assessing long-term trends in butterfly diversity

Species richness and evenness, the two principle components of species diversity, are frequently used to describe variation in species assemblages in space and time. Compound indices, including variations of both the Shannon–Wiener index and Simpson’s index, are assumed to intelligibly integrate species richness and evenness into all-encompassing measures. However, the efficacy of compound indices is disputed by the possibility of inverse relationships between species richness and evenness. Past studies have assessed relationships between various diversity measures across survey locations for a variety of taxa, often finding species richness and evenness to be inversely related. Butterflies are one of the most intensively monitored taxa worldwide, but have been largely neglected in such studies. Long-term butterfly monitoring programs provide a unique opportunity for analyzing how trends in species diversity relate to habitat and environmental conditions. However, analyzing trends in butterfly diversity first requires an assessment of the applicability of common diversity measures to butterfly assemblages. To accomplish this, we quantified relationships between butterfly diversity measures estimated from 10 years of butterfly population data collected in the North Saskatchewan River Valley in Edmonton, Alberta, Canada. Species richness and evenness were inversely related within the butterfly assemblage. We conclude that species evenness may be used in conjunction with richness to deepen our understandings of assemblage organization, but combining these two components within compound indices does not produce measures that consistently align with our intuitive sense of species diversity.     

A comparison of methods for mapping species ranges and species richness

Aim  Maps of species richness are the basis for applied research and conservation planning as well as for theoretical research investigating patterns of richness and the processes shaping these patterns. The method used to create a richness map could influence the results of such studies, but differences between these methods have been insufficiently evaluated. We investigate how different methods of mapping species ranges can influence patterns of richness, at three spatial resolutions.
Location  California, USA.
Methods  We created richness maps by overlaying individual species range maps for terrestrial amphibians and reptiles. The methods we used to create ranges included: point-to-grid maps, obtained by overlaying point observations of species occurrences with a grid and determining presence or absence for each cell; expert-drawn maps; and maps obtained through species distribution modelling. We also used a hybrid method that incorporated data from all three methods. We assessed the correlation and similarity of the spatial patterns of richness maps created with each of these four methods at three different resolutions.
Results  Richness maps created with different methods were more correlated at lower spatial resolutions than at higher resolutions. At all resolutions, point-to-grid richness maps estimated the lowest species richness and those derived from species distribution models the highest. Expert-drawn maps and hybrid maps showed intermediate levels of richness but had different spatial patterns of species richness from those derived with the other methods.
Main conclusions  Even in relatively well-studied areas such as California, different data sources can lead to rather dissimilar maps of species richness. Evaluating the strengths and weaknesses of different methods for creating a richness map can provide guidance for selecting the approach that is most appropriate for a given application and region.