A global model of island biogeography

Aim The goal of our study was to build a global model of island biogeography explaining bird species richness that combines MacArthur and Wilson's area–isolation theory with the species–energy theory. Location Global. Methods We assembled a global data set of 346 marine islands representing all types of climate, topography and degree of isolation on our planet, ranging in size from 10 ha to 800,000 km². We built a multiple regression model with the number of non‐marine breeding bird species as the dependent variable. Results We found that about 85–90% of the global variance in insular bird species richness can be explained by simple, contemporary abiotic factors. On a global scale, the three major predictors — area, average annual temperature and the distance separating the islands from the nearest continent — all have constraining (i.e. triangular rather than linear) relationships with insular bird species richness. We found that the slope of the species–area curve depends on both average annual temperature and total annual precipitation, but not on isolation. Insular isolation depends not only on the distance of an island from the continent, but also on the presence or absence of other neighbouring islands. Range in elevation — a surrogate for diversity of habitats — showed a positive correlation with bird diversity in warmer regions of the world, while its effect was negative in colder regions. We also propose a global statistical model to quantify the isolation‐reducing effect of neighbouring islands. Main conclusions The variation in avian richness among islands worldwide can be statistically explained by contemporary environmental variables. The equilibrium theory of island biogeography of MacArthur and Wilson and the species–energy theory are both only partly correct. Global variation in richness depends about equally upon area, climate (temperature and precipitation) and isolation. The slope of the species richness–area curve depends upon climate, but not on isolation, in contrast to MacArthur and Wilson's theory.     

Orchids of the West Indies: predictability of diversity and endemism

Aim We examined phytogeographical patterns of West Indian orchids, and related island area and maximum elevation with orchid species richness and endemism. We expected strong species–area relationships, but that these would differ between low and montane island groups. In so far as maximum island elevation is a surrogate for habitat diversity, we anticipated a strong relationship with maximum elevation and both species richness and endemism for montane islands. Location The West Indies. Methods Our data included 49 islands and 728 species. Islands were classified as either montane (≥ 300 m elevation) or low (< 300 m). Linear and multivariate regression analyses were run to detect relationships between either area or maximum island elevation and species richness or the number of island endemic species. Results For all 49 islands, the species–area relationship was strong, producing a z‐value of 0.47 (slope of the regression line) and explaining 46% of the variation. For 18 relatively homogeneous, low islands we found a non‐significant slope of z = −0.01 that explained only 0.1% of the variation. The 31 montane islands had a highly significant species–area relationship, with z = 0.49 and accounting for 65% of the variation. Species numbers were also strongly related to maximum island elevation. For all islands < 750 km², we found a small‐island effect, which reduced the species–area relationship to a non‐significant z = 0.16, with only 5% of the variation explained by the model. Species–area relationships for montane islands of at least 750 km² were strong and significant, but maximum elevation was the best predictor of species richness and accounted for 79% of the variation. The frequency of single‐island endemics was high (42%) but nearly all occurred on just nine montane islands (300 species). The taxonomic distribution of endemics was also skewed, suggesting that seed dispersability, while remarkable in some taxa, is very limited in others. Montane island endemics showed strong species–area and species–elevation relationships. Main conclusions Area and elevation are good predictors of orchid species diversity and endemism in the West Indies, but these associations are driven by the extraordinarily strong relationships of large, montane islands. The species richness of low islands showed no significant relationship with either variable. A small‐island effect exists, but the montane islands had a significant relationship between species diversity and maximum elevation. Thus, patterns of Caribbean orchid diversity are dependent on an interplay between area and topographic diversity.     

Species richness, environmental heterogeneity and area: a case study based on land snails in Skyros archipelago (Aegean Sea, Greece)

Aim To test the performance of the choros model in an archipelago using two measures of environmental heterogeneity. The choros model is a simple, easy‐to‐use mathematical relationship which approaches species richness as a combined function of area and environmental heterogeneity. Location The archipelago of Skyros in the central Aegean Sea (Greece). Methods We surveyed land snails on 12 islands of the archipelago. We informed the choros model with habitat data based on natural history information from the land snail species assemblage. We contrast this with habitat information taken from traditional vegetation classification to study the behaviour of choros with different measures of environmental heterogeneity. R² values and Akaike's information criterion (AIC) were used to compare the choros model and the Arrhenius species–area model. Path analysis was used to evaluate the variance in species richness explained by area and habitat diversity. Results Forty‐two land snail species were recorded, living in 33 different habitat types. The choros model with habitat types had more explanatory power than the classic species–area model and the choros model using vegetation types. This was true for all islands of the archipelago, as well as for the small islands alone. Combined effects of area and habitat diversity primarily explain species richness in the archipelago, but there is a decline when only small islands are considered. The effects of area are very low both for all the islands of the archipelago, and for the small islands alone. The variance explained by habitat diversity is low for the island group as a whole, but significantly increases for the small islands. Main conclusions The choros model is effective in describing species‐richness patterns of land snails in the Skyros Archipelago, incorporating ecologically relevant information on habitat occupancy and area. The choros model is more effective in explaining richness patterns on small islands. When using traditional vegetation types, the choros model performs worse than the classic species–area relationship, indicating that use of proxies for habitat diversity may be problematic. The slopes for choros and Arrhenius models both assert that, for land snails, the Skyros Archipelago is a portion of a larger biogeographical province. The choros model, informed by ecologically relevant habitat measures, in conjunction with path analysis points to the importance of habitat diversity in island species richness.     

Biogeographical patterns of blood parasite lineage diversity in avian hosts from southern Melanesian islands

Aim (1) To describe the species–area relationships among communities of Plasmodium and Haemoproteus parasites in different island populations of the same host genus (Aves: Zosterops). (2) To compare distance–decay relationships (turnover) between parasite communities and those with potential avian and dipteran hosts, which differ with respect to their movement and potential to disperse parasite species over large distances. Location Two archipelagos in the south‐west Pacific, Vanuatu and New Caledonia (c. 250 km west of Vanuatu) and its Loyalty Islands, with samples collected from a total of 16 islands of varying sizes (328–16,648 km²). Methods We characterized parasite diversity and distribution via polymerase chain reaction (PCR) from avian (Zosterops) blood samples. Bayesian methods were used to reconstruct the parasite phylogeny. In accordance with recent molecular evidence, we treat distinct mitochondrial DNA lineages as equivalent to species in this study. Path analysis and parasite lineage accumulation curves were used to assess the confounding effect of inadequate sampling on the estimation of parasite richness. Species–area and species–distance relationships were assessed using linear regression: distance–decay relationships were assessed using Mantel tests. Results Birds and mosquito species and Plasmodium lineages exhibited significant species–area relationships. However, Plasmodium lineages showed the weakest ‘species–area’ relationship; no relationship was found for Haemoproteus lineages. Avian species richness influenced parasite lineage richness more than mosquito species richness did. Within individual avian host species, the species–area relationship of parasites showed differing patterns. Path analysis indicated that sampling effort was unlikely to have a confounding effect on parasite richness. Distance from mainland (isolation effect) showed no effect on parasite richness. Community similarity decayed significantly with distance for avifauna, mosquito fauna and Plasmodium lineages but not for Haemoproteus lineages. Main conclusions Plasmodium lineages and mosquito species fit the power‐law model with steeper slopes than found for the avian hosts. The lack of species–distance relationship in parasites suggests that other factors, such as the competence of specific vectors and habitat features, may be more important than distance. The decay in similarity with distance suggests that the sampled Plasmodium lineages and their potential hosts were not randomly distributed, but rather exhibited spatially predictable patterns. We discuss these results in the context of the effects that parasite generality may have on distribution patterns.     

Geographical,anthropogenic and climatic determinants of bryophyte species composition and richness in the Shengsi archipelago,East China Sea

Introduction. Few attempts have been made to assess the comparative contributions of different environmental factors on species composition (SC) and richness (SR) of bryophytes on continental islands.

Methods. The bryophyte flora and the impact of seven environmental variables (island area, elevation, isolation, human disturbance, rainfall, vegetation cover, and exposed rock area) on 18 continental islands of the Shengsi archipelago in the East China Sea were investigated. Redundancy Analysis and Canonical Correspondence Analysis were used to determine to what extent the environmental variables could explain variation in species richness and species composition on these islands.

Key results & Conclusions. Island elevation, isolation, area and human disturbance intensity all significantly influenced bryophyte SC at island level, accounting for 12.7%, 9.9%, 8.8% and 7.8% of the total SC variation, respectively. Island area was the most important determinant of bryophyte SR (P?=?0.002), accounting for 58.3% of the total variation (9.7% by area per se and 48.6% confounded with other variables); elevation and human disturbance intensity also significantly influenced species richness, accounting for 10.5% and 6.9% of the total SR variation (conditional effects), respectively. Elevation and area had a positive interaction effect on SR while isolation exerted no significant effects (P?>?0.05). The relationships of bryophyte species number (S) with area (A) follow log₁₀ (S)?=?c?+?z?×?log₁₀ (A), with z values from 0.28 to 0.38. The effects of human disturbance on bryophyte SR followed the Gaussian model, supporting the ‘intermediate disturbance hypothesis’ to some extent.     

From plots to islands: species diversity at different scales

Aim To investigate how plant diversity of whole islands (‘gamma’) is related to alpha and beta diversity patterns among sampling plots within each island, thus exploring aspects of diversity patterns across scales. Location Nineteen islands of the Aegean Sea, Greece. Methods Plant species were recorded at both the whole‐island scale and in small 100 m² plots on each island. Mean plot species richness was considered as a measure of alpha diversity, and six indices of the ‘variation’‐type beta diversity were also applied. In addition, we partitioned beta diversity into a ‘nestedness’ and a ‘replacement’ component, using the total species richness recorded in all plots of each island as a measure of ‘gamma’ diversity. We also applied 10 species–area models to predict the total observed richness of each island from accumulated plot species richness. Results Mean alpha diversity was not significantly correlated with the overall island species richness or island area. The range of plot species richness for each island was significantly correlated with both overall species richness and area. Alpha diversity was not correlated with most indices of beta diversity. The majority of beta diversity indices were correlated with whole‐island species richness, and this was also true for the ‘replacement’ component of beta diversity. The rational function model provided the best prediction of observed island species richness, with Monod’s and the exponential models following closely. Inaccuracy of predictions was positively correlated with the number of plots and with most indices of beta diversity. Main conclusions Diversity at the broader scale (whole islands) is shaped mainly by variation among small local samples (beta diversity), while local alpha diversity is not a good predictor of species diversity at broader scales. In this system, all results support the crucial role of habitat diversity in determining the species–area relationship.     

On the importance of patch attributes, environmental factors and past human impacts as determinants of perennial plant species richness and diversity in Mediterranean semiarid steppes

Richness and diversity of perennial plant species were evaluated in 17 Stipa tenacissima steppes along a degradation gradient in semiarid SE Spain. The main objective of the study was to evaluate the relative importance of historical human impacts, small‐scale patch attributes and environmental factors as determinants of perennial plant species richness and diversity in S. tenacissima steppes, where vegetation is arranged as discrete plant patches inserted on a bare ground matrix. Partial least squares regression was used to determine the amount of variation in species richness and diversity that could be significantly explained by historical human impacts, patch attributes, and environmental factors together and separately. They explained up to 89% and 69% of the variation in species richness and diversity, respectively. In both cases, the predictive power of patch attributes models was higher than that of models consisting of abiotic characteristics and variables related to human impact, suggesting that patch attributes are the major determinants of species richness and diversity in semiarid S. tenacissima steppes. However, patch attributes alone are not enough to explain the observed variation in species richness and diversity. The area covered by late‐successional sprouting shrubs and the distance between consecutive patches were the most influencing individual variables on species richness and diversity, respectively. The implications of these results for the management of S. tenacissima steppes are discussed.     

Island biogeography of bats in Baja California, Mexico: patterns of bat species richness in a near-shore archipelago

Aim We studied the relationship between the size and isolation of islands and bat species richness in a near‐shore archipelago to determine whether communities of vagile mammals conform to predictions of island biogeography theory. We compared patterns of species richness in two subarchipelagos to determine whether area per se or differences in habitat diversity explain variations in bat species richness. Location Islands in the Gulf of California and adjacent coastal habitats on the Baja California peninsula in northwest Mexico. Methods Presence–absence surveys for bats were conducted on 32 islands in the Gulf of California using acoustic and mist‐net surveys. We sampled for bats in coastal habitats of four regions of the Baja peninsula to characterize the source pool of potential colonizing species. We fitted a semi‐log model of species richness and multiple linear regression and used Akaike information criterion model selection to assess the possible influence of log₁₀ area, isolation, and island group (two subarchipelagos) on the species richness of bats. We compared the species richness of bats on islands with greater vegetation densities in the southern gulf (n = 20) with that on drier islands with less vegetation in the northern gulf (n = 12) to investigate the relationship between habitat diversity and the species richness of bats. Results Twelve species of bats were detected on islands in the Gulf of California, and 15 species were detected in coastal habitats on the Baja peninsula. Bat species richness was related to both area and isolation of islands, and was higher in the southern subarchipelago, which has denser vegetation. Log₁₀ area was positively related to bat species richness, which increased by one species for every 5.4‐fold increase in island area. On average, richness declined by one species per 6.25 km increase in isolation from the Baja peninsula. Main conclusions Our results demonstrate that patterns of bat species richness in a near‐shore archipelago are consistent with patterns predicted by the equilibrium theory of island biogeography. Despite their vagility, bats may be more sensitive to moderate levels of isolation than previously expected in near‐shore archipelagos. Differences in vegetation and habitat xericity appear to be associated with richness of bat communities in this desert ecosystem. Although observed patterns of species richness were consistent with those predicted by the equilibrium theory, similar relationships between species richness and size and isolation of islands may arise from patch‐use decision making by individuals (optimal foraging strategies).     

Fish species richness decreases with salinity in tropical coastal lagoons

Aim To analyse the relationship between fish species richness and salinity, and to provide a simple linear model for fish diversity trends across salinity gradients in a tropical coastal lagoon that can be compared with other similar ecosystems and other communities. To reinforce our conclusions, the salinity–fish richness relationship was investigated at different spatial scales (sampling station, set of stations and whole lagoon) and for two different periods, separated by 18 years. Location The Terminos coastal lagoon, a shallow tropical lagoon (mean maximum depths ranging between 3.5 and 4.5 m), is located in the southern Gulf of Mexico (18.5–18.8° N, 91.3–91.9° W). The lagoon is 70 km long and 30 km wide, with a surface area of 1700 km². Methods Fish sampling, individual identification to the species level, and environmental variable measurements were carried out monthly at 17 sampling points. Multiple regression analysis with a backward selection procedure was used to relate fish species richness to environmental variables. Other statistical techniques, including cluster analysis and ancova , were applied to experimental data surveys. Results Among the different environmental variables, salinity was significantly and consistently related to fish species richness, whatever the period and the scale of observation. We found mainly significant negative correlations (P < 0.05) between fish species richness and salinity when sampling stations were analysed individually, and particularly for the river runoff zones with high variation in salinity throughout the year. For the entire lagoon, robust negative linear models were observed when fish species richness was organized into salinity ranges, with salinity explaining c. 8% of the variation in mean fish species richness (in a multiple regression analysis; 63–93% when considered in isolation). Main conclusions In the Terminos lagoon the relationship between fish species richness and salinity is mainly negative on any spatial scale. This result may be due partially to the penetration of freshwater fishes into estuarine areas following freshwater discharges, and partially to the dominance of estuarine taxa more able to tolerate low than high salinity values. Finally, we suggest that the ‘realized’ ecotone, where species from different origins really mix, is situated between 5 and 10‰, corresponding to the highest fish richness.     

Towards a more general species–area relationship: diversity on all islands, great and small

Aim

To demonstrate a new and more general model of the species–area relationship that builds on traditional models, but includes the provision that richness may vary independently of island area on relatively small islands (the small island effect).

Location

We analysed species–area patterns for a broad diversity of insular biotas from aquatic and terrestrial archipelagoes.

Methods

We used breakpoint or piecewise regression methods by adding an additional term (the breakpoint transformation) to traditional species–area models. The resultant, more general, species–area model has three readily interpretable, biologically relevant parameters: (1) the upper limit of the small island effect (SIE), (2) an estimate of richness for relatively small islands and (3) the slope of the species–area relationship (in semi‐log or log–log space) for relatively large islands.

Results

The SIE, albeit of varying magnitude depending on the biotas in question, appeared to be a relatively common feature of the data sets we studied. The upper limit of the SIE tended to be highest for species groups with relatively high resource requirements and low dispersal abilities, and for biotas of more isolated archipelagoes.

Main conclusions

The breakpoint species–area model can be used to test for the significance, and to explore patterns of variation in small island effects, and to estimate slopes of the species–area (semi‐log or log–log) relationship after adjusting for SIE. Moreover, the breakpoint species–area model can be expanded to investigate three fundamentally different realms of the species–area relationship: (1) small islands where species richness varies independent of area, but with idiosyncratic differences among islands and with catastrophic events such as hurricanes, (2) islands beyond the upper limit of SIE where richness varies in a more deterministic and predictable manner with island area and associated, ecological factors and (3) islands large enough to provide the internal geographical isolation (large rivers, mountains and other barriers within islands) necessary for in situ speciation.

     

Species richness, area and climate correlates

Aim Species richness–area theory predicts that more species should be found if one samples a larger area. To avoid biases from comparing species richness in areas of very different sizes, area is often controlled by counting the numbers of co‐occupying species in near‐equal area grid cells. The assumption is that variation in grid cell size accrued from working in a three‐dimensional world is negligible. Here we provide a first test of this idea. We measure the surface area of c. 50 × 50 km and c. 220 × 220 km grid cells across western Europe. We then ask how variation in the area of grid cells affects: (1) the selection of climate variables entering a species richness model; and (2) the accuracy of models in predicting species richness in unsampled grid cells. Location Western Europe. Methods Models are developed for European plant, breeding bird, mammal and herptile species richness using seven climate variables. Generalized additive models are used to relate species richness, climate and area. Results We found that variation in the grid cell area was large (50 × 50 km: 8–3311 km²; 220 × 220: 193–55,100 km²), but this did not affect the selection of variables in the models. Similarly, the predictive accuracy was affected only marginally by exclusion of area within models developed at the c. 50 × 50 km grid cells, although predictive accuracy suffered greater reductions when area was not included as a covariate in models developed for c. 220 × 220 km grid cells. Main conclusions Our results support the assumption that variation in near‐equal area cells may be of second‐order importance for models explaining or predicting species richness in relation to climate, although there is a possibility that drops in accuracy might increase with grid cell size. The results are, however, contingent on this particular data set, grain and extent of the analyses, and more empirical work is required.     

island biogeography of Day Geckos (Phelsuma) in the Indian Ocean

Summary Step-wise multiple regression was employed to probe the determinants of species diversity of day geckos (Phelsuma) in the Indian Ocean. Independent variables were area, elevation, and two measures of isolation. Distance from Madagascar and island height (an indicator of habitat diversity) were the two most important predictors of species richness. Similar studies on other taxa rarely find isolation to be a major factor. The relatively poor dispersal abilities of reptiles may explain why isolation, rather than attributes of the islands, are more important in this case. The regressions also indicate that habitat diversity (assumed to correlate with maximum island elevation) is more important than area per se in determining species diversity. These results agree with predictions of the equilibrium theory of island biogeography, but historical processes have also greatly influenced species richness.     

Macroinvertebrate richness patterns in North African streams

Aim To test the hypothesis that macroscale environmental variables explain local taxonomic richness of stream macroinvertebrates, and then to identify the relationships between these variables and benthic fauna richness in North Africa. Location North Africa, from West Morocco to East Tunisia. Methods Using a large‐scale data base made of 211 sampling sites gathered from an area of 500,000 km², an artificial neural network model has been built to identify and predict the influence of macroscale environmental variables on local macroinvertebrate richness. Results The correlation coefficient (r) between observed and estimated taxon richness values was 0.75 (P < 0.001), and the model explained more than 55% (r² = 0.563) of the macroinvertebrate richness variation. Macroinvertebrate richness was, therefore, accurately predicted using only three environmental variables accounting for hydrology (number of rainy days), geographical factors, i.e. connections between European and North African land masses (longitude) and climatic gradient (altitude). Main conclusions Stream macroinvertebrate richness in North Africa results from a combination of climatic, geographical and hydrological parameters. Although consistent with current biogeographic and ecological concepts mainly derived from European and North American streams, this study underlines the specificity of dry Mediterranean ecosystems. The shape of diversity patterns results from climatic conditions and their associated environmental seasonal dynamics, which screens geographical processes.     

The effects of environmental variables and human disturbance on woody species richness and diversity in a bamboo–deciduous forest in northeastern Thailand

Variations in species richness and diversity at a local scale are affected by a number of complex and interacting variables, including both natural environmental factors and human-made changes to the local environment. Here we identified the most important determinants of woody species richness and diversity at different growth stages (i.e. adult, sapling and seedling) in a bamboo–deciduous forest in northeast Thailand. A total of 20 environmental and human disturbance variables were used to determine the variation in species richness and diversity. In total, we identified 125 adult, 111 sapling (within fifty 20 × 20-m plots) and 89 seedling species (within one hundred and twenty 1 × 1-m subplots). Overall results from stepwise multiple regression analyses showed that environmental variables were by far the most important in explaining the variation in species richness and diversity. Forest structure (i.e. number of bamboo clumps and canopy cover) was important in determining the adult species richness and diversity (R ² = 0.48, 0.30, respectively), while topography (i.e. elevation) and human disturbance (i.e. number of tree stumps) were important in determining the sapling species richness and diversity (R ² = 0.55, 0.39, respectively). Seedling species richness and diversity were negatively related to soil phosphorus. Based on our results, we suggest that the presence of bamboos should be incorporated in management strategies for maintaining woody species richness and diversity in these forest ecosystems. Specifically, if bamboos cover the forest floor at high densities, it may be necessary to actively control these species for successful tree establishment.     

Squamate richness in the Brazilian Cerrado and its environmental–climatic associations

We investigate patterns of species richness of squamates (lizards, snakes, and amphisbaenians) in the Brazilian Cerrado, identifying areas of particularly high richness, and testing predictions of large‐scale richness hypotheses by analysing the relationship between species richness and environmental climatic variables. We used point localities from museum collections to produce maps of the predicted distributions for 237 Cerrado squamate species, using niche‐modelling techniques. We superimposed distributions of all species on a composite map, depicting richness across the ecosystem. Then, we performed a multiple regression analysis using eigenvector‐based spatial filtering (Principal Coordinate of Neighbour Matrices) to assess environmental–climatic variables that are best predictors of species richness. We found that the environmental–climatic and spatial filters multiple regression model explained 78% of the variation in Cerrado squamate richness (r² = 0.78; F = 32.66; P < 0.01). Best predictors of species richness were: annual precipitation, precipitation seasonality, altitude, net primary productivity, and precipitation during the driest quarter. A model selection approach revealed that several mechanisms related to the different diversity hypothesis might work together to explain richness variation in the Cerrado. Areas of higher species richness in Cerrado were located mainly in the south‐west, north, extreme east, and scattered areas in the north‐west portions of the biome. Partitioning of energy among species, habitat differentiation, and tolerance to variable environments may be the primary ecological factors determining variation in squamate richness across the Cerrado. High richness areas in northern Cerrado, predicted by our models, are still poorly sampled, and biological surveys are warranted in that region. The south‐western region of the Cerrado exhibits high species richness and is also undergoing high levels of deforestation. Therefore, maintenance of existing reserves, establishment of ecological corridors among reserves, and creation of new reserves are urgently needed to ensure conservation of species in these areas.     

Forest ecosystems of an Arizona Pinus ponderosa landscape: multifactor classification and implications for ecological restoration

Aim We developed an ecosystem classification within a 110,000‐ha Arizona Pinus ponderosa P. & C. Lawson (ponderosa pine) landscape to support ecological restoration of these forests. Specific objectives included identifying key environmental variables constraining ecosystem distribution and comparing plant species composition, richness and tree growth among ecosystems. Location The Coconino National Forest and the Northern Arizona University Centennial Forest, in northern Arizona, USA. Methods We sampled geomorphology, soils and vegetation on 66 0.05‐ha plots in open stands containing trees of pre‐settlement (c. 1875) origin, and on 26 plots in dense post‐settlement stands. Using cluster analysis and ordination of vegetation and environment matrices, we classified plots into ecosystem types internally similar in environmental and vegetational characteristics. Results We identified 10 ecosystem types, ranging from dry, black cinders/Phacelia ecosystems to moist aspen/Lathyrus ecosystems. Texture, organic carbon and other soil properties reflecting the effects of parent materials structured ecosystem distribution across the landscape, and geomorphology was locally important. Plant species composition was ecosystem‐specific, with C₃Festuca arizonica Vasey (Arizona fescue), for instance, abundant in mesic basalt/Festuca ecosystems. Mean P. ponderosa diameter increments ranged from 2.3–4.3 mm year^?1 across ecosystems in stands of pre‐settlement origin, and the ecosystem classification was robust in dense post‐settlement stands. Main conclusions Several lines of evidence suggest that although species composition may have been altered since settlement, the same basic ecosystems occurred on this landscape in pre‐settlement forests, providing reference information for ecological restoration. Red cinders/Bahia ecosystems were rare historically and > 30% of their area has been burned by crown fires since 1950, indicating that priority could be given to restoring this ecosystem's remaining mapping units. Ecosystem classifications may be useful as data layers in gap analyses to identify restoration and conservation priorities. Ecosystem turnover occurs at broad extents on this landscape, and restoration must accordingly operate across large areas to encompass ecosystem diversity. By incorporating factors driving ecosystem composition, this ecosystem classification represents a framework for estimating spatial variation in ecological properties, such as species diversity, relevant to ecological restoration.     

Fine‐scale determinants of butterfly species richness and composition in a mountain region

Aim Global patterns of species richness are often considered to depend primarily on climate. We aimed to determine how topography and land cover affect species richness and composition at finer scales. Location Sierra de Guadarrama (central Iberian Peninsula). Methods We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) at 600–2300 m elevation in a region of 10800 km². We recorded environmental variables at 100‐m resolution using GIS, and derived generalized linear models for species density (number of species per unit area) and expected richness (number of species standardized to number of individuals) based on variables of topoclimate (elevation and insolation) or land cover (vegetation type, geology and hydrology), or both (combined). We evaluated the models against independent data from the alternative study year. We also tested for differences in species composition among sites and years using constrained ordination (canonical correspondence analysis), and used variation partitioning analyses to quantify the independent and combined roles of topoclimate and land cover. Results Topoclimatic, land cover and combined models were significantly related to observed species density and expected richness. Topoclimatic and combined models outperformed models based on land cover variables, showing a humped elevational diversity gradient. Both topoclimate and land cover made significant contributions to models of species composition. Main conclusions Topoclimatic factors may dominate species richness patterns in regions with pronounced elevational gradients, as long as large areas of natural habitat remain. In contrast, both topoclimate and land cover may have important effects on species composition. Biodiversity conservation in mountainous regions therefore requires protection and management of natural habitats over a wide range of topoclimatic conditions, which may assist in facilitating range shifts and alleviating declines in species richness related to climate change.     

Predictability of plant and fungal species richness of old‐growth boreal forest islands

Abstract. The fragmentation and deterioration of old‐growth forest habitat by modern forestry have become a major threat to species diversity in Fennoscandia. In order to develop a conservation strategy for the remaining diversity it is essential to identify the existing diversity and to develop appropriate conservation and monitoring programs. For these purposes indicators of conservation value for administrative prioritization are required. This study examines the predictability of plant and fungal species richness on two spatial scales on 46 isolated old‐growth forest islands (0.17 ‐ 12 ha) in a forest‐wetland mosaic. We explore (1) to what extent area, isolation and stand structure variables can explain the variation in species richness and (2) if richness patterns of individual species groups correlate. Isolation showed no relation to species richness. Area explained 50 ‐ 70% of the variation in total species richness and was positively related to the density of crustose lichens and Red‐list species in island interiors. Stand structure variables explained 28 ‐ 66% of the residual variation in total species richness after controlling for island size, and 15 ‐ 73% of the variation in density of species in island interiors. The highest predictability of species richness was found among substrate‐specific fungi and Red‐list species. Different stand structure variables were found to explain richness in the different species groups, and only among a few species groups species richness correlated. Thus, species richness of one single species group is unlikely to be a good indicator for total biodiversity. The results show that measurements of stand size and stand structure variables may be a strong complementary tool, and sometimes a substitute to extensive species inventories when one aims to estimate and monitor plant and fungal species diversity in old‐growth Picea abies forests.     

Evolutionary assembly of island faunas reverses the classic island–mainland richness difference in Anolis lizards

Aim Islands are widely considered to be species depauperate relative to mainlands but, somewhat paradoxically, are also host to many striking adaptive radiations. Here, focusing on Anolis lizards, we investigate if cladogenetic processes can reconcile these observations by determining if in situ speciation can reduce, or even reverse, the classical island–mainland richness discrepancy. Location Caribbean islands and the Neotropical mainland. Methods We constructed range maps for 203 mainland anoles from museum records and evaluated whether geographical area could account for differences in species richness between island and mainland anole faunas. We compared the island species–area relationship with total mainland anole diversity and with the richness of island‐sized mainland areas. We evaluated the role of climate in the observed differences by using Bayesian model averaging to predict island richness based on the mainland climate–richness relationship. Lastly, we used a published phylogeny and stochastic mapping of ancestral states to determine if speciation rate was greater on islands, after accounting for differences in geographical area. Results Islands dominated by in situ speciation had, on average, significantly more species than similarly sized mainland regions, but islands where in situ speciation has not occurred were species depauperate relative to mainland areas. Results were similar at the scale of the entire mainland, although marginally non‐significant. These findings held even after accounting for climate. Speciation has not been faster on islands; instead, when extinction was assumed to be low, speciation rate varied consistently with geographical area. When extinction was high, there was some evidence that mainland speciation was faster than expected based on area. Main conclusions Our results indicate that evolutionary assembly of island faunas can reverse the general pattern of reduced species richness on islands relative to mainlands.     

Factors influencing vascular plant diversity on 22 islands off the coast of eastern North America

Aim The influence of physiographic and historical factors on species richness of native and non‐native vascular plants on 22 coastal islands was examined. Location Islands off the coast of north‐eastern USA and south‐eastern Canada between 41° and 45° N latitude were studied. Island size ranges from 3 to 26,668 ha. All islands were deglaciated between 15,000 and 11,000 yr bp ; all but the four New Brunswick islands were attached to the mainland until rising sea level isolated them between 14,000 and 3800 yr bp . Methods Island species richness was determined from floras compiled or revised since 1969. Simple and multiple regression and rank correlation analysis were employed to assess the relative influence of independent variables on species richness. Potential predictors included island area, latitude, elevation, distance from the mainland, distance from the nearest larger island, number of soil types, years since isolation, years since deglaciation, and human population density. Results Native vascular plant species richness for the 22 islands in this study is influenced most strongly by island area, latitude, and distance from the nearest larger island; richness increases with island area, but decreases with latitude and distance from the nearest larger island as hypothesized. That a similar model employing distance from the mainland does not meet the critical value of P confirms the importance of the stepping‐stone effect. Habitat diversity as measured by number of soil types is also an important predictor of native plant species richness, but at least half of its influence can be attributed to island area, with which it is correlated. Two historical factors, years since deglaciation and years since isolation, also appear to be highly correlated with native species richness, but their influence cannot be separated from that of latitude for the present sample size. Non‐native vascular plant species richness is influenced primarily by island area and present‐day human population density, although human population density may be a surrogate for the cumulative effect of several centuries of anthropogenic impacts related to agriculture, hunting, fishing, whaling, tourism, and residential development. Very high densities of ground‐nesting pelagic birds may account for the high percentage of non‐native species on several small northern islands. Main conclusions Many of the principles of island biogeography that have been applied to oceanic islands apply equally to the 22 islands in this study. Native vascular plant species richness for these islands is strongly influenced by physiographic factors. Influence of two historical factors, years since deglaciation and years since isolation, cannot be assessed with the present sample size. Non‐native vascular plant species richness is influenced by island area as well as by human population density; human population density may be a surrogate for other anthropogenic impacts.