Hierarchical partitioning of ant diversity: implications for conservation of biogeographical diversity in arid and semi‐arid areas

Aim The scale of observation is important in detecting the spatial variation of biological assemblages, which should be taken into consideration for an appropriate plan of biogeographical conservation. We investigated whether (1) World Wildlife Fund’s ecoregion units are the appropriate scale for conserving ant diversity in Iran, (2) each ecoregion represents a distinct ant community composition and (3) patterns of diversity partitioning differ among four ecoregions. Location Iran, a sampling transect along four arid and semi‐arid ecoregions. Methods We applied hierarchical partitioning to data collected from a nested sampling design including four hierarchical levels: ‘local’, ‘landscape’, ‘ecoregional’ and ‘whole‐region’. Observed alpha and beta diversity components were compared with values of null distributions. Hierarchical cluster analysis was applied to evaluate similarity of ant species composition among ecoregions. Results Partitioning of whole‐region species richness showed that 85% of the species richness was generated by beta diversity among ecoregions and landscapes. The highest value of diversity was generated by beta diversity among ecoregions. Unlike whole‐region partitioning, separate partitioning within each ecoregion revealed that beta component among localities contributed to species richness of each ecoregion. Ecoregions showed different patterns of diversity partitioning. The alpha component contributed largely to the total diversity of two ecoregions, but for two other ecoregions, beta component contributed more than alpha component. Cluster analysis identified four discrete ant species compositions; however, it split landscapes of one ecoregion into two distinct groups. Main conclusions Whole‐region diversity partitioning indicates that ecoregions represent the appropriate scale for conserving ant diversity and that each ecoregion has a distinct ant fauna. However, different conservation strategies should be considered for different ecoregions owing to the differing scales of variation within them. Boundaries of ecoregions remain a subject for further studies. The influence of climate change on ecoregional boundaries should be considered and should be predicted with respect to future conservation maps.     

The variation of tree beta diversity across a global network of forest plots

Aims With the aim of understanding why some of the world's forests exhibit higher tree beta diversity values than others, we asked: (1) what is the contribution of environmentally related variation versus pure spatial and local stochastic variation to tree beta diversity assessed at the forest plot scale; (2) at what resolution are these beta‐diversity components more apparent; and (3) what determines the variation in tree beta diversity observed across regions/continents? Location World‐wide. Methods We compiled an unprecedented data set of 10 large‐scale stem‐mapping forest plots differing in latitude, tree species richness and topographic variability. We assessed the tree beta diversity found within each forest plot separately. The non‐directional variation in tree species composition among cells of the plot was our measure of beta diversity. We compared the beta diversity of each plot with the value expected under a null model. We also apportioned the beta diversity into four components: pure topographic, spatially structured topographic, pure spatial and unexplained. We used linear mixed models to interpret the variation of beta diversity values across the plots. Results Total tree beta diversity within a forest plot decreased with increasing cell size, and increased with tree species richness and the amount of topographic variability of the plot. The topography‐related component of beta diversity was correlated with the amount of topographic variability but was unrelated to its species richness. The unexplained variation was correlated with the beta diversity expected under the null model and with species richness. Main conclusions Because different components of beta diversity have different determinants, comparisons of tree beta diversity across regions should quantify not only overall variation in species composition but also its components. Global‐scale patterns in tree beta diversity are largely coupled with changes in gamma richness due to the relationship between the latter and the variation generated by local stochastic assembly processes.     

The influence of geographical and ecological factors on island beta diversity patterns

Aim To investigate the importance of various island characteristics in determining spatial patterns of variations in beta diversity for various animal groups. Location Analyses are presented for 10 animal groups living on the Aeolian Islands, a volcanic archipelago in the central Mediterranean, near Sicily. Methods Three hypotheses were formulated to explain patterns of beta diversity: the target‐area–distance effect, stepping stone dispersal and island age. Matrices of inter‐island dissimilarities were constructed under each hypothesis and correlated with matrices of faunal dissimilarities using Mantel tests. For the ‘target‐area–distance effect’ hypothesis, inter‐island dissimilarities were calculated using island sizes and distances to nearest mainland areas. For the ‘stepping stone dispersal’ hypothesis, inter‐island distances were measured. Finally, for the ‘island age’ hypothesis, inter‐island dissimilarities were calculated on the basis of the geological age of the islands. Cluster analysis was used to investigate inter‐island faunal relationships. Results Support for a target‐area–distance effect was found only for birds. For these highly mobile animals, inter‐island distances had no significant effects on beta diversity. Birds are known to colonize islands by crossing large sea barriers and thus they can easily reach the Aeolian Islands, which are close to source areas (notably Sicily). Inter‐island distances had a significant role in determining patterns of beta diversity in most invertebrates. For Mollusca, Opiliones, Chilopoda, Heteroptera, coprophagous Scarabaeoidea, and Tenebrionidae, even relatively short distances preclude invertebrates from colonizing an island regularly from the mainland, and most colonization probably results from inter‐island faunal exchanges. Island age was proved to be important only for orthopterans. Main conclusions The origin of most of the Aeolian invertebrate fauna is quite recent, and species appear to have established on the islands predominantly by stepping stone dispersal. Birds, which are highly mobile organisms, follow more direct mainland–island dynamics. As further studies on other islands become available, comparative analyses will confirm whether the factors influencing variations in beta diversity in this study and their relationships with species dispersal ability are consistent across scales and geographical context.     

Vascular plant species richness in relation to habitat diversity and island area in the Finnish Archipelago

Aim The aim of this study is to explore the interrelationships between island area, species number and habitat diversity in two archipelago areas. Location The study areas, Brunskär and Getskär, are located in an archipelago in south‐western Finland. Methods The study areas, 82 islands in Brunskär and 78 in Getskär, were classified into nine habitat types based on land cover. In the Brunskär area, the flora (351 species) was surveyed separately for each individual habitat on the islands. In the Getskär area, the flora (302 species) was surveyed on a whole‐island basis. We used standard techniques to analyse the species–area relationship on a whole‐island and a habitat level. We also tested our data for the small island effect (SIE) using breakpoint and path analysis models. Results Species richness was significantly associated with both island area and habitat diversity. Vegetated area in particular, defined as island area with the rock habitat subtracted, proved to be a strong predictor of species richness. Species number had a greater association with island area multiplied by the number of habitats than with island area or habitat number separately. The tests for a SIE in the species–area relationship showed the existence of a SIE in one of the island groups. No SIE could be detected for the species–vegetated area relationship in either of the island groups. The strength of the species–area relationship differed considerably between the habitats. Main conclusions The general principles of island biogeography apply well to the 160 islands in this study. Vascular plant diversity for small islands is strongly influenced by physiographic factors. For the small islands with thin and varying soil cover, vegetated area was the most powerful predictor of species richness. The species–area curves of various habitats showed large variations, suggesting that the measurement of habitat areas and establishment of habitat‐based species lists are needed to better understand species richness on islands. We found some evidence of a SIE, but it is debatable whether this is a ‘true’ SIE or a soil cover/habitat characteristics feature.     

Do commonly used indices of β‐diversity measure species turnover?

Abstract. Indices of β‐diversity are of two major types, (1) those that measure among‐plot variability in species composition independently of the position of individual plots on spatial or environmental gradients, and (2) those that measure the extent of change in species composition along predefined gradients, i.e. species turnover. Failure to recognize this distinction can lead to the inappropriate use of some β‐diversity indices to measure species turnover. Several commonly‐used indices of β‐diversity are based on Whittaker's β_W (β_W = γ/α, where γ is the number of species in an entire study area and α is the number of species per plot within the study area). It is demonstrated that these indices do not take into account the distribution of species on spatial or environmental gradients, and should therefore not be used to measure species turnover. The terms ‘β‐diversity’ and ‘species turnover’ should not be used interchangeably. Species turnover can be measured using matrices of compositional similarity and physical or environmental distances among pairs of study plots. The use of indices of β‐diversity and similarity‐distance curves is demonstrated using simulated data sets.     

Introductions do not compensate for functional and phylogenetic losses following extinctions in insular bird assemblages

The ratio of species extinctions to introductions has been comparable for many insular assemblages, suggesting that introductions could have ‘compensated’ for extinctions. However, the capacity for introduced species to replace ecological roles and evolutionary history lost following extinction is unclear. We investigated changes in bird functional and phylogenetic diversity in the wake of extinctions and introductions across a sample of 32 islands worldwide. We found that extinct and introduced species have comparable functional and phylogenetic alpha diversity. However, this was distributed at different positions in functional space and in the phylogeny, indicating a ‘false compensation’. Introduced and extinct species did not have equivalent functional roles nor belong to similar lineages. This makes it unlikely that novel island biotas composed of introduced taxa will be able to maintain ecological roles and represent the evolutionary histories of pre‐disturbance assemblages and highlights the importance of evaluating changes in alpha and beta diversity concurrently.     

Plants on small islands revisited: the effects of spatial scale and habitat quality on the species–area relationship

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration.     

Species–area relationships in the Andaman and Nicobar Islands emerge because rarer species are disproportionately favored on larger islands

The island species–area relationship (ISAR) describes how the number of species increases with increasing size of an island (or island‐like habitat), and is of fundamental importance in island biogeography and conservation. Here, we use a framework based on individual‐based rarefaction to infer whether ISARs result from passive sampling, or whether some processes are acting beyond sampling (e.g., disproportionate effects and/or habitat heterogeneity). Using data on total and relative abundances of four taxa (birds, butterflies, amphibians, and reptiles) from multiple islands in the Andaman and Nicobar archipelago, we examine how different metrics of biodiversity (total species richness, rarefied species richness, and abundance‐weighted effective numbers of species emphasizing common species) vary with island area. Total species richness increased for all taxa, as did rarefied species richness controlling for a given sampling effort. This indicates that the ISAR did not result because of passive sampling, but that instead, some species were disproportionately favored on larger islands. For birds, frogs, and lizards, this disproportionate effect was only associated with species that were rarer in the samples, but for butterflies, both more common and rarer species were affected. Furthermore, for the two taxa for which we had plot‐level data (reptiles and amphibians), within‐island β‐diversity did not increase with island size, suggesting that within‐island compositional effects were unlikely to be driving these ISARs. Overall, our results indicate that the ISARs of these taxa are most likely driven by disproportionate effects, that is, where larger islands are important sources of biodiversity beyond a simple sampling expectation, especially through their influence on rarer species, thus emphasizing their role in the preservation and conservation of species.     

Island theory, matrix effects and species richness patterns in habitat fragments

Island biogeography theory, created initially to study diversity patterns on islands, is often applied to habitat fragments. A key but largely untested assumption of this application of theory is that landscape matrix species composition is non‐overlapping with that of the islands. We tested this assumption in successional old field patches in a closely mowed matrix, and because our patches are appropriately viewed as sets of contiguous habitat units we studied patterns of species richness per unit area. Previous studies at our site did not find that diversity patterns on patch ‘islands’ conformed to predictions of island biogeography theory. Our results indicate that when matrix species are removed from the patch samples, diversity patterns conform better to theory. We suggest that classical island theory remains an appropriate tool to study diversity patterns in fragmented habitats, but that allowances should be made for spill‐over colonization of ‘islands’ from the ‘sea’.     

Island biogeography and the species richness of introduced mammals on New Zealand offshore islands

Aim To investigate and establish the significance of various island biogeographic relationships (geographical, ecological and anthropological) with the species richness of introduced mammals on offshore islands. Location The 297 offshore islands of the New Zealand archipelago (latitude: 34–47°S; longitude: 166–179°E). Methods Data on New Zealand offshore islands and the introduced mammals on them were collated from published surveys and maps. The species richness of small and large introduced mammals were calculated for islands with complete censuses and regressed on island characteristics using a Poisson distributed error generalized linear model. To estimate the ‘z‐value’ for introduced mammals on New Zealand islands, least‐squares regression was used [log₁₀ S vs. log₁₀ A]. Results High collinearity was found between the area, habitat diversity and elevation of islands. The island characteristics related to the species richness of introduced mammals differed predictably between large and small mammals. The species richness of introduced large mammals was mostly related to human activities on islands, whereas species richness of introduced small mammals was mostly related to island biogeographical parameters. The ‘z‐value’ for total species richness is found to be expectedly low for introduced mammals. Main conclusions Distance appears to have become ecologically trivial as a filter for introduced mammal presence on New Zealand offshore islands. There is strong evidence of a ‘small island’ effect on New Zealand offshore islands. The species richness of both small and large introduced mammals on these islands appears to be most predominantly related to human use, although there is some evidence of natural dispersal for smaller species. The ecological complexity of some islands appears to make them less invasible to introduced mammals. Some human activities have an interactive effect on species richness. A small number of islands have outlying species richness values above what the models predict, suggesting that the presence of some species may be related to events not accounted for in the models.     

Incorporating functional dissimilarities into sample‐based rarefaction curves: from taxon resampling to functional resampling

Question: Indices of functional diversity have been seen as the key for integrating information on species richness with measures that focus on those components of community composition related to ecosystem functioning. For comparing species richness among habitats on an equal‐effort basis, so‐called sample‐based rarefaction curves may be used. Given a study area that is sampled for species presence and absence in N plots, sample‐based rarefaction generates the expected number of accumulated species as the number of sampled plots increases from 1 to N. Accordingly, the question for this study is: can we construct a ‘functional rarefaction curve’ that summarizes the expected functional dissimilarity between species when n plots are drawn at random from a larger pool of N plots? Methods: In this paper, we propose a parametric measure of functional diversity that is obtained by combining sample‐based rarefaction techniques that are usually applied to species richness with Rao's quadratic diversity. For a given set of N presence/absence plots, the resulting measure summarizes the expected functional dissimilarity at an increasingly larger cumulative number of plots n (n≤N). Results and Conclusions: Due to its parametric nature, the proposed measure is progressively more sensitive to rare species with increasing plot number, thus rendering this measure adequate for comparing the functional diversity of species assemblages that have been sampled with variable effort.     

High species diversity and turnover in granite inselberg floras highlight the need for a conservation strategy protecting many outcrops

Determining patterns of plant diversity on granite inselbergs is an important task for conservation biogeography due to mounting threats. However, beyond the tropics there are relatively few quantitative studies of floristic diversity, or consideration of these patterns and their environmental, biogeographic, and historical correlates for conservation. We sought to contribute broader understanding of global patterns of species diversity on granite inselbergs and inform biodiversity conservation in the globally significant Southwest Australian Floristic Region (SWAFR). We surveyed floristics from 16 inselbergs (478 plots) across the climate gradient of the SWAFR stratified into three major habitats on each outcrop. We recorded 1,060 species from 92 families. At the plot level, local soil and topographic variables affecting aridity were correlated with species richness in herbaceous (HO) and woody vegetation (WO) of soil‐filled depressions, but not in woody vegetation on deeper soils at the base of outcrops (WOB). At the outcrop level, bioclimatic variables affecting aridity were correlated with species richness in two habitats (WO and WOB) but, contrary to predictions from island biogeography, were not correlated with inselberg area and isolation in any of the three habitats. Species turnover in each of the three habitats was also influenced by aridity, being correlated with bioclimatic variables and with interplot geographic distance, and for HO and WO habitats with local site variables. At the outcrop level, species replacement was the dominant component of species turnover in each of the three habitats, consistent with expectations for long‐term stable landscapes. Our results therefore highlight high species diversity and turnover associated with granite outcrop flora. Hence, effective conservation strategies will need to focus on protecting multiple inselbergs across the entire climate gradient of the region.     

生境片段化对千岛湖地表甲虫物种多样性的影响

在千岛湖片段化景观中选取20个陆桥岛屿和8个大陆样点,从2012年7月到2014年4月,按季度(春、夏、秋季)6次采用巴氏陷阱法收集地表甲虫,分析其物种多度、组成、多样性和季节动态,以及不同岛屿上的地表甲虫的物种多样性与岛屿面积和隔离度等岛屿空间特征的关系.结果表明: 共收集记录到地表甲虫26科101种3370头.大陆和大岛地表甲虫的物种丰富度有显著差异,且小岛地表甲虫密度显著高于大陆;大陆地表甲虫的物种组成变化较大,而岛屿上分布的地表甲虫的物种组成则变化较小.地表甲虫的物种丰富度与岛屿面积呈显著正相关,密度与隔离度呈显著正相关.夏季岛屿上地表甲虫物种丰富度高于春秋两季,岛屿与大陆样地的Shannon指数、Simpson指数和Pielou均匀度指数均在夏季最高、秋季最低.     

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.     

Testing island biogeography theory with visitation rates of birds to British islands

Aim We consider three hypotheses – MacArthur and Wilson’s island biogeography theory (IBT), Lack’s habitat diversity idea and the ‘target effect’– that explain the pattern of decreased species richness on small and distant islands. Location We evaluate these hypotheses using a detailed dataset on the occurrence and abundance of terrestrial birds on nine islands off the coast of Britain and the Republic of Ireland. Methods  Unlike previous studies, we compile data on species that visit the islands, rather than just those that breed on them. We divided the species into five mutually exclusive categories based upon their migratory status and where they regularly breed: British residents, summer visitors to Britain, winter visitors to Britain, and vagrants from Europe or beyond Europe. For each species group on each island we calculated the average number of species visiting each year. We then regressed the average number of species against island area and distance to the mainland (all variables were log‐transformed). We also compared the average number of species visiting each island with the average number of species breeding on each island. Results  Average number of visiting British residents decreased significantly with increasing island distance, but showed no relationship with island area. There was no significant relationship between island area or island distance and average number of summer or winter visitors. European and non‐European vagrants likewise showed no relationship between numbers of species visiting and island distance. However, the relationship between island area and number of visiting species was significant for both these categories; as island area increases so too does the number of visiting species. Main conclusions  As predicted by IBT, there were fewer visiting species on more distant islands. There were substantially more visitors to each island than breeding species, supporting Lack’s argument that lower bird richness is not a result of varying immigration rates (as predicted by IBT) but rather a result of some other island property, e.g. fewer resources. Birds make a decision to either leave an island or stay and breed. The target effect was also clearly demonstrated by the increase in European and non‐European breeders with increasing island size.     

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.     

Patterns of species richness on very small islands: the plants of the Aegean archipelago

Aim To investigate the species–area relationship (SAR) of plants on very small islands, to examine the effect of other factors on species richness, and to check for a possible Small Island Effect (SIE). Location The study used data on the floral composition of 86 very small islands (all < 0.050 km²) of the Aegean archipelago (Greece). Methods We used standard techniques for linear and nonlinear regression in order to check several models of the SAR, and stepwise multiple regression to check for the effects of factors other than area on species richness (‘habitat diversity’, elevation, and distance from nearest large island), as well as the performance of the Choros model. We also checked for the SAR of certain taxonomic and ecological plant groups that are of special importance in eastern Mediterranean islands, such as halophytes, therophytes, Leguminosae and Gramineae. We used one‐way anova to check for differences in richness between grazed and non‐grazed islands, and we explored possible effects of nesting seabirds on the islands’ flora. Results Area explained a small percentage of total species richness variance in all cases. The linearized power model of the SAR provided the best fit for the total species list and several subgroups of species, while the semi‐log model provided better fits for grazed islands, grasses and therophytes. None of the nonlinear models explained more variance. The slope of the SAR was very high, mainly due to the contribution of non‐grazed islands. No significant SIE could be detected. The Choros model explained more variance than all SARs, although a large amount of variance of species richness still remained unexplained. Elevation was found to be the only important factor, other than area, to influence species richness. Habitat diversity did not seem important, although there were serious methodological problems in properly defining it, especially for plants. Grazing was an important factor influencing the flora of small islands. Grazed islands were richer than non‐grazed, but the response of their species richness to area was particularly low, indicating decreased floral heterogeneity among islands. We did not detect any important effects of the presence of nesting seabird colonies. Main conclusions Species richness on small islands may behave idiosyncratically, but this does not always lead to a typical SIE. Plants of Aegean islets conform to the classical Arrhenius model of the SAR, a result mainly due to the contribution of non‐grazed islands. At the same time, the factors examined explain a small portion of total variance in species richness, indicating the possible contribution of other, non‐standard factors, or even of stochastic effects. The proper definition of habitat diversity as pertaining to the taxon examined in each case is a recurrent problem in such studies. Nevertheless, the combined effect of area and a proxy for environmental heterogeneity is once again superior to area alone in explaining species richness.     

Resource heterogeneity does not explain the diversity–productivity relationship across a boreal island fertility gradient

Many studies at the regional scale have found either negative or hump‐shaped relationships between productivity and diversity, and some theories propose that these occur because soil resource heterogeneity is either lower or less important in more productive environments. However, there have been few explicit tests of these theories in natural ecosystems. We evaluated the relationship between soil resource heterogeneity and plant richness within a well characterized system of 30 islands in northern Sweden across which soil fertility and productivity declines, and species richness increases, as a consequence of ecosystem retrogression. On each island we created a spatially explicit grid consisting of 49 sampling points in a 9.5 m quadrat, which we used to quantify spatial heterogeneity of five soil variables (NH₄⁺‐N, amino N, PO₄^?‐P, microbial biomass, and decomposition), and plant community composition. Using a hierarchical Bayesian approach, we estimated mean semivariograms of each variable for each island size class to compare three components of spatial heterogeneity: total variability, spatial grain, and patchiness. This analysis showed that variability within islands was usually lowest on small islands, where species richness was highest and productivity lowest; however, NH₄⁺‐N and amino N had greater patchiness and spatial grain on small islands. We did not detect any significant across‐island correlations between whole‐plot plant species richness and either whole‐plot standard deviation or coefficient of variation of any soil variable. Using partial Mantel tests, we found that mean correlation coefficients between within‐plot plant community composition and the soil variables were never significant for any island size class, and did not differ between island size classes. Our findings do not provide any evidence that soil resource heterogeneity controls the productivity–diversity relationship in this system, and suggests other mechanisms are primarily responsible.     

Effects of habitat fragmentation on the functional diversity of insects in Thousand Island Lake,China

Due to habitat fragmentation, the loss of species diversity has been extensively studied. On the contrary, the effects of habitat fragmentation on functional diversity is still poorly understood. In the Thousand Island Lake, we conducted studies of insect functional diversity on a set of 29 isolated islands. We used 10 functional diversity indices from three aspects (functional richness, functional evenness and functional divergence) to respectively describe functional diversity of insects on sample islands. We found the following results: (i) The functional indices selected could reflect the functional diversity of sample islands and it is further proved that in general, three components of functional diversity were independent of each other; (ii) Sample islands could be divided into two categories, island JSD and the remaining islands; (iii) Functional richness increased with island area and shape index, but had no significant correlation with isolation. Likewise, both functional evenness and functional divergence had no significant correlation with island attributes. The conclusion to emphasize from our research is that: (i) habitat fragmentation reduced the biological functional diversity to some extent, further demonstrating the importance of habitat continuity in biodiversity protection; and (ii) for functional diversity protection of insects in a fragmented landscape, an island which has high approximate shape index values of at least hundred hectare magnitude order has a critical promoting effect.     

Plant species diversity of Adriatic islands: An introductory survey

Abstract

The European Mediterranean region is one of the world's major centres of biodiversity. Research on plant species diversity in this region has neglected the area along the eastern part of the Adriatic basin in comparison to the other Mediterranean areas. The main aim of this study was to focus on this neglected area, by supplying data which is at present lacking in order to discuss the species-area relationship (SAR), floristic richness and endemism of the Adriatic islands and coast. Floristic data for 106 Croatian islands collected by different authors were integrated, systematised and presented in a form usable by other researchers worldwide. The Power (Arrhenius) function was used for modelling (by non-linear regression) the SAR. Residuals around the regression curve (as indicators of floristic diversity without the influence of island area) were calculated for each island. The proportion of endemics in the total island flora varies from 0% up to 28.6%, and 17.5% for narrow endemics. Floristic richness of the broader region was estimated (on the basis of SAR extrapolation) on 1807 species for all Croatian islands, and on 2797 species for the entire Mediterranean area in Croatia.