First comprehensive assessment of dipteran diversity and vectorial potential in northeastern Algeria: Ecological, veterinary, and one health perspectives.

Aim The partition of the geographical variation in Argentinian terrestrial mammal species richness (SR) into environmentally, human and spatially induced variation.Location Argentina, using the twenty‐three administrative provinces as the geographical units.Methods We recorded the number of terrestrial mammal species in each Argentinian province, and the number of species belonging to particular groups (Marsupialia, Placentaria, and among the latter, Xenarthra, Carnivora, Ungulates and Rodentia). We performed multiple regressions of each group's SR on environmental, human and spatial variables, to determine the amounts of variation explained by these factors. We then used a variance partitioning procedure to specify which proportion of the variation in SR is explained by each of the three factors exclusively and which proportions are attributable to interactions between factors.Results For marsupials, human activity explains the greatest part of the variation in SR. The purely environmental and purely human influences on all mammal SR explain a similarly high proportion of the variation in SR, whereas the purely spatial influence accounts for a smaller proportion of it. The exclusive interaction between human activity and space is negative in carnivores and rodents. For rodents, the interaction between environment and spatial situation is also negative. In the remaining placental groups, pure spatial autocorrelation explains a small proportion of the variation in SR.Main conclusions Environmental factors explain most of the variation in placental SR, while Marsupials seem to be mainly affected by human activity. However, for edentates, carnivores, and ungulates the pure human influence is more important than the pure spatial and environmental influences. Besides, human activity disrupts the spatial structure caused by the history and population dynamics of rodents and, to a lesser extent, of carnivores. The historical events and population dynamics on the one hand, and the environment on the other, cause rodent SR to vary in divergent directions. In the remaining placental groups the autocorrelation in SR is mainly the result of autocorrelation in the environmental and human variables.

Most studies of coral reef fish communities have been restricted to site-attached species on small, isolated patches of habitat. Few have investigated spatial variation in fish species richness in relation to predictions based on stochastic or deterministic processes of community organisation. Our aims were to: (1) compare species richness on contiguous and fragmented reef habitats, and (2) investigate the mechanisms underlying spatial variation in species richness. Quantitative comparison of species-area curves for contiguous and patchy coral reef indicated that patch reefs support more species than equivalent areas of contiguous reef. However, Monte-Carlo simulated rarefaction curves indicated little difference in the species-individuals relationship for both habitats. Rarefaction was employed to eliminate variation in species richness among sites due to differences in sample size (number of fish present). After removal of sample-size effects, multiple regression models explained 30% and 25% of total variability in species richness on contiguous and patchy coral reef based on variation in habitat structure (e.g., depth, shelter availability, substratum characteristics). To investigate the likely importance of stochastic processes in determining spatial variation in species richness, we compared the species-individuals relationship from contiguous reef sites with the relationships derived from null models involving the random reallocation of fish among sites. Comparisons of the observed data with the outcomes of the null models indicated that spatial variation in species richness was not wholly attributable to stochastic processes. We suggest that the observed patterns of species richness may reflect species interactions (e.g., competition and predation) within fish communities.

Mapping landscape variation in tree species richness (SR) is essential to the long term management and conservation of forest ecosystems. The current study examines the prospect of mapping field assessments of SR in a high-elevation, deciduous forest in northern Iran as a function of 16 biophysical variables representative of the area’s unique physiography, including topography and coastal placement, biophysical environment, and forests. Basic to this study is the development of moderate-resolution biophysical surfaces and associated plot-estimates for 202 permanent sampling plots. The biophysical variables include: (i) three topographic variables generated directly from the area’s digital terrain model; (ii) four ecophysiologically-relevant variables derived from process models or from first principles; and (iii) seven variables of Landsat-8-acquired surface reflectance and two, of surface radiance. With symbolic regression, it was shown that only four of the 16 variables were needed to explain 85% of observed plot-level variation in SR (i.e., wind velocity, surface reflectance of blue light, and topographic wetness indices representative of soil water content), yielding mean-absolute and root-mean-squared error of 0.50 and 0.78, respectively. Overall, localised calculations of wind velocity and surface reflectance of blue light explained about 63% of observed variation in SR, with wind velocity accounting for 51% of that variation. The remaining 22% was explained by linear combinations of soil-water-related topographic indices and associated thresholds. In general, SR and diversity tended to be greatest for plots dominated by Carpinus betulus (involving ≥ 33% of all trees in a plot), than by Fagus orientalis (median difference of one species). This study provides a significant step towards describing landscape variation in SR as a function of modelled and satellite-based information and symbolic regression. Methods in this study are sufficiently general to be applicable to the characterisation of SR in other forested regions of the world, providing plot-scale data are available for model generation.

Patterns in species richness from a wide range of plant communities in Ku‐ring‐gai Chase National Park, New South Wales, Australia, were examined in relation to a number of environmental variables, including soil physical and chemical characteristics. Total species richness and richness of three growth‐form types (trees, shrubs and ground cover) were determined in duplicate 500‐m2 quadrats from 50 sites on two geological substrata: Hawkesbury Sandstone and Narrabeen shales and sandstones. Generalized linear models (GLM) were used to determine the amount of variation in species richness that could be significantly explained by the measured environmental variables. Seventy‐three per cent of the variation in total species richness was explained by a combination of soil physical and chemical variables and site attributes. The environmental variables explained 24% of the variation in tree species richness, 67% of the variation in shrub species richness and 62% of the variation in ground cover species richness. These results generally support the hypothesis of an environmental influence on patterns in total species richness and richness of shrubs and ground cover species. However, tree species richness was not adequately predicted by any of the measured environmental variables; the present environment exerts little influence on the richness of this growth‐form type. Historical factors, such as fire or climatic/environmental conditions at time of germination or seedling establishment, may be important in determining patterns in tree species richness at the local scale.

Patterns in species richness from a wide range of plant communities in Ku-ring-gai Chase National Park, New South Wales, Australia, were examined in relation to a number of environmental variables, including soil physical and chemical characteristics. Total species richness and richness of three growth-form types (trees, shrubs and ground cover) were determined in duplicate 500-m2 quadrats from 50 sites on two geological substrata: Hawkesbury Sandstone and Narrabeen shales and sandstones. Generalized linear models (GLM) were used to determine the amount of variation in species richness that could be significantly explained by the measured environmental variables. Seventy-three per cent of the variation in total species richness was explained by a combination of soil physical and chemical variables and site attributes. The environmental variables explained 24% of the variation in tree species richness, 67% of the variation in shrub species richness and 62% of the variation in ground cover species richness. These results generally support the hypothesis of an environmental influence on patterns in total species richness and richness of shrubs and ground cover species. However, tree species richness was not adequately predicted by any of the measured environmental variables; the present environment exerts little influence on the richness of this growth-form type. Historical factors, such as fire or climatic/environmental conditions at time of germination or seedling establishment, may be important in determining patterns in tree species richness at the local scale.

Although detected long ago, latitudinal disparity in species richness lacks a consensus regarding its underlying mechanisms. We evaluated whether the main predictions derived from the tropical niche conservatism hypothesis help to explain differences regarding species richness and turnover of species and lineages between forests located in tropical and subtropical climates. If tropical niches are retained, we predict that only a subset of tropical lineages disperses and establishes outside the tropics; tip‐level phylogenetic clustering increases outside the tropics; and the climatic variation drives species richness indirectly via constraints to the distribution of lineages. We compiled 58 checklists along tropical and subtropical sites of riparian forests in southeastern South America. We tested the frequency of niches shifts for species and lineages and the abundance of taxa in each climate. Next, we checked the likelihood of pathways linking climatic and spatial predictors directly with species richness and via phylogenetic clustering estimates. Several lineages only occurred in the tropics, and the number of species and lineages that occurred in both climates was lower than expected by chance. Conversely, few lineages were exclusively subtropical and diversified in the subtropics. Phylogenetic clustering increased in subtropical sites and was correlated with decreasing species richness. An interaction between mean temperature of coldest quarter and precipitation seasonality explained most variation in species richness via increases in phylogenetic clustering. These results support an important contribution of climatic niche conservatism to explain richness disparities between tropics and subtropics, mainly because of the inability of most lineages to colonize the subtropics, which is very likely related to cold intolerance. Since niche conservatism likely drives most of the variation in tree species richness in the region, it provides a mechanistic interpretation of the observed patterns, thus fostering the understanding of richness disparities between these tropical and subtropical tree communities.

Recording effort biases the species richness cited in plant distribution atlases

In riparian wetlands total standing crop often fails to account for a significant part of the observed variation in species richness and species composition within communities. In this study, we used abundance of the dominant species instead of total standing crop as the biotic predictor variable and investigated its relationships with species composition and species richness in communities dominated by Phragmites australis (Cav.) Trin. ex Steudel. This was done by measuring soil organic matter content, litter cover and elevation, Phragmites abundance (standing crop and stem density) and species composition in 78 releves. In addition, we tried to identify the environmental boundaries of Phragmites communities by sampling releves in neighbouring communities. Two gradients were related to a decline in Phragmites abundance: one gradient, perpendicular to the shoreline, was mainly related to increased elevation and the second gradient ran parallel to the shoreline and was related to increased amounts of soil organic matter. Within the releves dominated by Phragmites, stem density of Phragmites and litter cover were the only factors significantly related to species composition in the RDA solution. Litter cover and standing crop of the dominant accounted for 64% of the variation in species richness within the Phragmites-dominated community. These results show that dead and living biomass of the dominant species may account for a substantial part of the variation in species composition and species richness within a single community.

The species–area relationship: an exploration of that ‘most general, yet protean pattern’¹

Bird abundance trends have been correlated with habitat changes in urban developed areas but have seldom been associated with specific patterns of urban-related habitat changes. We examined breeding bird–habitat relationships in 334 random plots ranging from undisturbed natural to highly developed land in Tucson, Arizona. In each plot we quantified 19 variables describing three land cover patterns (habitat physiognomy, floristics, and spatial relationships of native habitat fragments) and correlated them with abundances of 21 bird species. Abundances of 17 bird species were associated with variables describing land cover pattern. In addition, we correlated abundance, species richness, and evenness for three bird guilds (non-natives, natives, and a native indicator guild) with land cover variables. Housing density best explained the variation in species richness for both the non-native (r2 = 0.79) and the indicator guilds (r2 = −0.69), whereas area of Upland Sonoran vegetative cover (r2 = 0.56) and distance from undisturbed washes (r2 = −0.56) correlated most strongly with the native-bird group. Finally, we developed and tested regression models predicting species richness for each bird guild. The following variables loaded into the predictive models: house density; percentage cover of paved areas; exotic, Upland Sonoran, and undisturbed riparian vegetation; and distance from undisturbed washes. The models explained 71% of the variation in non-native bird species richness, 56% of the variation in native bird species richness, and 60% of the variation in species richness for the indicator guild of birds. The correlations and regression models can be used to predict species richness responses to future residential development in the Tucson area.

Despite the numerous studies on the large-scale patterns of species richness, the spatial variation and determinants of species richness for alpine plant are still an outstanding question and critical to future biodiversity conservation. The genus Saxifraga is a typical alpine plant group with high species richness in the Himalaya-Hengduan mountain regions, China. We performed simple regression models and variance partitioning to assess the importance of different factors, especially soil-related ones, in driving Saxifraga richness patterns. The results showed that environmental energy, habitat heterogeneity, and soil heterogeneity together dominated the spatial variation of species richness. The coarse fragments volume of soil, elevation range, and soil heterogeneity, are positively related to Saxifraga richness. Soil slightly outperforms habitat heterogeneity in predicting the spatial variation of Saxifraga species richness with an explanatory power of 39.3% and 36.6%, respectively. Environmental energy, such as the maximum temperature of the warmest quarter, is negatively correlated with species richness and explains 44.8% of spatial variation of Saxifraga richness. Multiple regression models, including three variables, each representing energy, soil, and habitat heterogeneity, can only explain 53.1% variation of species richness. Variance partitioning outscored 26% of the shared effects of the three variables, while the independent effect of each variable is less than 10%. These results indicated the energy, soil, and habitat heterogeneity together are primary determinants of the spatial variation of Saxifraga species richness. However, there are probably other hidden factors predicting species richness variation due to the low explanatory power of the multiple regression models. Our study emphasizes the significance of soil properties in determining species richness patterns in China, especially for the alpine plant groups. The negative association of species richness with temperature suggests a potential threat of alpine biodiversity loss in HHM from future warming.

Apparent regular variation in the distributions of organisms along geographical gradients has always fascinated ecologists. Variation in species richness with latitude has received the most attention, of course, but variation in species richness with elevation also has been of considerable interest and study. Precisely how and why species richness varies with elevation remains controversial (Wolda 1987, McCoy 1990, Colwell and Hurtt 1994, Rahbek 1995, 1997, Fleishman et al. 1998). Part of the reason for the continuing controversy is the fact that species richness is only an index, a manageable substitute for the set of distributions of individual species along an elevational gradient. Any explanation proposed for apparent regular variation in species richness with elevation can be, at best, only a loose reflection of the complicated autecological relationships between the individual species and elevation. The more species the proposed explanation is able to accommodate, the closer it will come to explaining variation in species richness, but any single explanation may not be suitable for a wide range of species (Lawton 1996). Another part of the reason for the continuing controversy about how and why species richness varies with elevation involves sampling problems (McCoy 1990, Rahbek 1995). Simply comparing species richness from one location to another can involve many sampling problems (Gotelli and Colwell 2001), but when such comparisons are made along gradients, the problems multiply. Understanding the causes of variation in species richness with elevation may have been hampered, for example, because different studies typically do not encompass the same elevational range and because the elevation of true maximum species richness sometimes occurs outside the sampled range (McCoy 1990). Ultimately, sampling problems even could lead to erroneous views of how species richness varies along elevational gradients (Rahbek 1995). Sampling problems such as those just described for studies of variation in species richness along elevational gradients are instances of a general problem in ecology that I term gradients. Veiled gradients arise from the fact that the outcome of any examination of a local gradient elevation, in this case is contingent upon the temporal and spatial frameworks employed. Over short time periods or across small geographical scales, only a portion of the gradient is likely to be revealed, the remainder of the gradient being veiled in time or space. Failure to realize that only a portion of the gradient is likely to be revealed in studies that are temporally or spatially restricted could obscure any true relationship that might exist (Allen and Starr 1982, McCoy 1990, McCoy and Bell 1991, Korner 2000). A ready example of how veiled gradients can influence interpretation of the variation in species richness with elevation can be found in the recent literature. Fleishman et al. (2000) determined that butterfly species richness increased with elevation in one of the canyons they studied but decreased in the other (Fig. 1). They attributed the apparent difference in the distribution of species richness with elevation to differences in climatic severity between the two canyons. The elevational ranges that were sampled were not the same in the two canyons, however, raising the possibility of a sampling problem. Samples (n = 102) from the first canyon (Toiyabe Range) spanned an elevational range of 1917-3272 m, whereas samples (n = 49) from the second canyon (Toquima Range) spanned an elevational range of 1872-2750 m. Ideally, we would like to unveil the distribution of species richness with elevation by extending the gradient in the Toquima Range to 3272 m, but we cannot do so with the available data. We can find out what the distribution of species richness with elevation would look like if the gradient in the Toiyabe Range were veiled to 2750 m, however. Examining changes in richness with elevation when the gradients are of the same length dramatically alters the interpretation of the relationship (Fig. 1). The apparent decline in species richness with elevation in the Toiyabe Range essentially disappears. Furthermore, an alternative interpretation of the data now suggests itself: that

Plant-diversity hotspots on a global scale are well established, but smaller local hotspots within these must be identified for effective conservation of plants at the global and local scales. We used the distributions of endemic and endemic-threatened species of Myrtaceae to indicate areas of plant diversity and conservation importance within the Atlantic coastal forests (Mata Atlântica) of Brazil. We applied 3 simple, inexpensive geographic information system (GIS) techniques to a herbarium specimen database: predictive species-distribution modeling (Maxent); complementarity analysis (DIVA-GIS); and mapping of herbarium specimen collection locations. We also considered collecting intensity, which is an inherent limitation of use of natural history records for biodiversity studies. Two separate areas of endemism were evident: the Serra do Mar mountain range from Paraná to Rio de Janeiro and the coastal forests of northern Espírito Santo and southern Bahia. We identified 12 areas of approximately 35 km(2) each as priority areas for conservation. These areas had the highest species richness and were highly threatened by urban and agricultural expansion. Observed species occurrences, species occurrences predicted from the model, and results of our complementarity analysis were congruent in identifying those areas with the most endemic species. These areas were then prioritized for conservation importance by comparing ecological data for each.

Biodiversity is severely threatened by habitat destruction. As a consequence of habitat destruction, the remaining habitat becomes more fragmented. This results in time-lagged population extirpations in remaining fragments when these are too small to support populations in the long term. If these time-lagged effects are ignored, the long-term impacts of habitat loss and fragmentation will be underestimated. We quantified the magnitude of time-lagged effects of habitat fragmentation for 157 nonvolant terrestrial mammal species in Madagascar, one of the biodiversity hotspots with the highest rates of habitat loss and fragmentation. We refined species' geographic ranges based on habitat preferences and elevation limits and then estimated which habitat fragments were too small to support a population for at least 100 years given stochastic population fluctuations. We also evaluated whether time-lagged effects would change the threat status of species according to the International Union for the Conservation of Nature (IUCN) Red List assessment framework. We used allometric relationships to obtain the population parameters required to simulate the population dynamics of each species, and we quantified the consequences of uncertainty in these parameter estimates by repeating the analyses with a range of plausible parameter values. Based on the median outcomes, we found that for 34 species (22% of the 157 species) at least 10% of their current habitat contained unviable populations. Eight species (5%) had a higher threat status when accounting for time-lagged effects. Based on 0.95-quantile values, following a precautionary principle, for 108 species (69%) at least 10% of their habitat contained unviable populations, and 51 species (32%) had a higher threat status. Our results highlight the need to preserve continuous habitat and improve connectivity between habitat fragments. Moreover, our findings may help to identify species for which time-lagged effects are most severe and which may thus benefit the most from conservation actions.

Aim A near universal truth in North America is that species richness increases from the Arctic Circle to the Central American tropics. Latitude is regarded as a major explanatory variable in species density, although it is only a surrogate for underlying ecological variables. I aimed to elucidate those underlying ecological variables that are associated with variation in bat species richness across the entire North American continent, providing a portrait of the macroecology of the order Chiroptera and its familial components.Methods I determined the number of bat species recorded for every state in Mexico and the United States, every province or territory in Canada, and every country in Central America. For each of these entities (n = 99), I also gathered basic data on mean annual precipitation, variation across the year (July vs. January) in mean temperature, mean January temperature, range in elevation (topographic relief), per cent vegetative cover and median latitude. Using a variety of linear regression and model‐fitting techniques, I analysed the strength and direction of the relationship between species richness and environmental variables for the order Chiroptera as a whole and separately for each of four familial groups: Molossidae (free‐tailed bats), Phyllostomidae (New World leaf‐nosed bats), Vespertilionidae (evening bats), and a set of six families (the Desmodontidae, Emballonuridae, Furipteridae, Natalidae, Noctilionidae, and Thyropteridae) represented in North America relatively poorly.Results and main conclusions Save for the Vespertilionidae, species richness of bats increased towards the Panamanian Isthmus. The Phyllostomidae and the set of miscellaneous families are particularly speciose in tropical Central America, with many fewer species occurring through subtropical Mexico into (in some cases) the southernmost United States. The Molossidae extends farther north, sparingly into the middle of the United States. Species density of the Vespertilionidae peaks in central and western Mexico and the southernmost United States, declining south through tropical southern Mexico and Central America and north through the central United States into Canada. Annual precipitation, January temperature, and topography are good predictors of species richness in the Chiroptera and the Molossidae, precipitation, topography, and temperature range in the Phyllostomidae, January temperature and topography in the Vespertilionidae, and precipitation alone in the collection of families. Vegetative cover explained little variation in the Chiroptera as a whole or in any family. After accounting for the effects of the environmental variables, latitude explained an insignificant amount of the residual variation in species richness. Bat families differ in their ecology, so studies of bat biogeography in North America may be misleading if they are examined only at the ordinal level.