Re‐approaching the small island effect

Aim To propose a new approach to the small island effect (SIE) and a simple mathematical procedure for the estimation of its upper limit. The main feature of the SIE is that below an upper size threshold an increase of species number with increase of area in small islands is not observed. Location Species richness patterns from different taxa and insular systems are analysed. Methods Sixteen different data sets from 12 studies are analysed. Path analysis was used for the estimation of the upper limit of the SIE. We studied each data set in order to detect whether there was a certain island size under which the direct effects of area were eliminated. This detection was carried out through the sequential exclusion of islands from the largest to the smallest. For the cases where an SIE was detected, a log‐log plot of species number against area is presented. The relationships between habitat diversity, species number and area are studied within the limits of the SIE. In previous studies only area was used for the detection of the SIE, whereas we also encompass habitat diversity, a parameter with well documented influence on species richness, especially at small scales. Results An SIE was detected in six out of the 16 studied cases. The upper limit of the SIE varies, depending on the characteristics of the taxon and the archipelago under study. In general, the values of the upper limit of the SIE calculated according to the approach undertaken in our study differ from the values calculated in previous studies. Main conclusions Although the classical species–area models have been used to estimate the upper limit of the SIE, we propose that the detection of this phenomenon should be undertaken independently from the species–area relationship, so that the net effects of area are calculated excluding the surrogate action of area on other variables, such as environmental heterogeneity. The SIE appears when and where area ceases to influence species richness directly. There are two distinct SIE patterns: (1) the classical SIE where both the direct and indirect effects of area are eliminated and (2) the cryptic SIE where area affects species richness indirectly. Our approach offers the opportunity of studying the different factors influencing biodiversity on small scales more accurately. The SIE cannot be considered a general pattern with fixed behaviour that can be described by the same model for different island groups and taxa. The SIE should be recognized as a genuine but idiosyncratic phenomenon.     

Temporal changes in the island flora at different scales in the archipelago of SW Finland

Question: How have species richness and vegetation patterns changed in a group of islands in the northern Baltic Sea over a 58‐yr period of changing land use and increasing eutrophication? Location: A group of 116 islands, the Brunskär sub‐archipelago, in SW Finland. Methods: A complete survey of vascular plant species performed in 1947–1949 by Skult was repeated by our group using the same methodology in 2005–2007 (historical versus contemporary, respectively). DCAs were performed and total number of species, extinction–colonization rates, species frequency changes and mean Ellenberg indicator values for light, moisture and nitrogen and Eklund indicator values for dependence of human cultural influence were obtained for each island and relevé. Results: Species richness has declined on large islands and increased on small islands. The increase in number of species on small islands is driven by a strong increase in frequency of shore species, which in turn is induced by more productive shores. The decrease in species richness on large islands is related to overgrowth of open semi‐natural habitats after cessation of grazing and other agricultural practices. Conclusions: After the late 1940s, open habitats, which were created and maintained by cattle grazing and other traditional agricultural activities, have declined in favour of woody shrub and forest land. Shores have been stabilized and influenced by the eutrophication of the Baltic Sea, and the vegetation has become more homogeneous. This development, resulting in lower species diversity, poses a challenge for the preservation of biodiversity both on a local and on a landscape level.     

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).     

Small island biogeography in the Gulf of California: lizards, the subsidized island biogeography hypothesis, and the small island effect

Aim We used insular lizard communities to test the predictions of two hypotheses that attempt to explain patterns of species richness on small islands. We first address the subsidized island biogeography (SIB) hypothesis, which predicts that spatial subsidies may cause insular species richness to deviate from species–area predictions, especially on small islands. Next, we examine the small island effect (SIE), which suggests small islands may not fit the traditional log‐linear species–area curve. Location Islands with arthropodivorous lizard communities throughout the Gulf of California. Methods To evaluate the SIB hypothesis, we first identified subsidized and unsubsidized islands based on surrogate measures of allochthonous productivity (i.e. island size and bird presence). Subsequently, we created species–area curves from previously published lizard species richness and island area data. We used the residuals and slopes from these analyses to compare species richness on subsidized and unsubsidized islands. To test for an SIE, we used breakpoint regression to model the relationship between lizard species richness and island area. We compared results from this model to results from the log‐linear regression model. Results Subsidized islands had a lower slope than unsubsidized islands, and the difference between these groups was significant when small islands were defined as < 1 km². In addition to comparing slopes, we tested for differences in the magnitude of the residuals (from the species–area regression of all islands) for subsidized vs. unsubsidized islands. We found no significant patterns in the residual values for small vs. large islands, or between islands with and without seabirds. The SIE was found to be a slightly better predictor of lizard species richness than the traditional log‐linear model. Main conclusions Predictions of the SIB hypothesis were partially supported by the data. The absence of a significant SIE may be a result of spatial subsidies as explained by the SIB hypothesis and data presented here. We conclude by suggesting potential scenarios to test for interactions between these two small island hypotheses. Future studies considering factors affecting species richness should examine the possible role of spatial subsidies, an SIE, or a synergistic effect of the two in data sets with small islands.     

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.     

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.     

Drivers of diversity in Macaronesian spiders and the role of species extinctions

Aim To identify the biogeographical factors underlying spider species richness in the Macaronesian region and assess the importance of species extinctions in shaping the current diversity. Location The European archipelagos of Macaronesia with an emphasis on the Azores and Canary Islands. Methods Seven variables were tested as predictors of single‐island endemics (SIE), archipelago endemics and indigenous spider species richness in the Azores, Canary Islands and Macaronesia as a whole: island area; geological age; maximum elevation; distance from mainland; distance from the closest island; distance from an older island; and natural forest area remaining per island – a measure of deforestation (the latter only in the Azores). Different mathematical formulations of the general dynamic model of oceanic island biogeography (GDM) were also tested. Results Island area and the proportion of remaining natural forest were the best predictors of species richness in the Azores. In the Canary Islands, area alone did not explain the richness of spiders. However, a hump‐shaped relationship between richness and time was apparent in these islands. The island richness in Macaronesia was correlated with island area, geological age, maximum elevation and distance to mainland. Main conclusions In Macaronesia as a whole, area, island age, the large distance that separates the Azores from the mainland, and the recent disappearance of native habitats with subsequent unrecorded extinctions seem to be the most probable explanations for the current observed richness. In the Canary Islands, the GDM model is strongly supported by many genera that radiated early, reached a peak at intermediate island ages, and have gone extinct on older, eroded islands. In the Azores, the unrecorded extinctions of many species in the oldest, most disturbed islands seem to be one of the main drivers of the current richness patterns. Spiders, the most important terrestrial predators on these islands, may be acting as early indicators for the future disappearance of other insular taxa.     

Habitat diversity, ecological requirements of species and the Small Island Effect

Aim  To explore the causal factors leading to a significant Small Island Effect (SIE), that is, the absence of the commonly found species–area relationships below an island size, on the terrestrial isopod communities from a large number of islands.
Location  Ninety islands of the Aegean Sea (Greece).
Methods  The detection of a significant SIE is assessed through the application of all three methods available in the literature. Species are divided into generalists and specialists. We tested if the minimum area and the area range of each species' occurrences differ between generalists and specialists. Next, we searched for differences in the ratios of specialists to generalists above and below the SIE threshold, and tested their cumulative ratios when islands are arranged according to increasing area, altitude or habitat diversity in order to identify the threshold where they become statistically indistinguishable from the ratio of the total set of islands.
Results  Our results indicate a strong effect of habitat availability on the SIE. Communities of islands within the SIE range, host a higher percentage of generalists. An analysis of the specific habitat requirements shows that, for isopods, the crucial factor is the lack of habitats related to inland waters from small islands.
Main conclusions  The distribution of habitats on islands of different size is of major importance for the occurrence of a SIE. The relative representation of specialist and generalist species on islands of different size plays an important role in shaping SIE-related patterns. Conservation efforts should pay special attention on freshwater habitats, especially on small Aegean islands. Identifying the causal factors of SIE, combined with a thorough knowledge of the ecological requirements of species can offer insights into identifying habitat types and groups of species that are more vulnerable to alterations of the environment.     

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.

     

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.     

Seashore in the mountain: limestone‐associated land snail fauna on the oceanic Hahajima Island (Ogasawara Islands,Western Pacific)

Because land snails inhabiting the seashore are most likely to be carried by ocean currents or by attaching to seabirds, land snail fauna on oceanic islands include species derived from the mainland ancestors inhabiting the seashore. If habitat use of the island descendants is constrained by the ecology of the mainland ancestor, the island species that moved from the coastal habitat to the inland habitat may still be restricted to relatively exposed microhabitats with high pH, calcium carbonate‐rich substrates, and poor litter cover. We tested this hypothesis by investigating the association between environmental conditions and species diversity of seashore‐derived species of the endemic land snails on the oceanic Hahajima Island (Ogasawara Islands). Seashore‐derived species showed higher species richness on limestone outcrops than non‐limestone areas, whereas the other species showed no significant increase in species richness in limestone outcrops. There was a higher proportion of seashore‐derived species on the limestone ridges than on the soil of dolines, even in the limestone area. Accordingly, the species derived from the seashore of the mainland are restricted to microhabitats with poor vegetation cover, poor litter cover, high pH, and calcium carbonate‐rich substrates, which supports the hypothesis that the inland species on an island derived from the mainland seashore still prefer environments similar to the seashore. In addition, the seashore‐derived species on the limestone outcrop include cave‐dwellers lacking functional eyes. This suggests that the probability of colonizing a cave environment is restricted to seashore‐derived species. The findings obtained in the present study suggest that habitat use of the ancestral lineages can constrain habitat use of the descendants, even in the oceanic islands with depauperate fauna. This bias in the species composition on the limestone outcrop constrains lineages that can colonize and adapt to the inside of caves, and therefore, habitat use of the ancestral lineages affects the ability of descendant lineages to colonize novel habitats. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102 , 686–693.     

Colonization of Sphagnum on land uplift islands in the Baltic Sea: time, area, distance and life history

Aim To test whether species richness of Sphagnum mosses on islands in a land uplift archipelago is related to island age, area or connectivity, and whether the frequency of different species can be predicted by their life history and autecology. Location The northern Stockholm archipelago in the Baltic Sea, east‐central Sweden, with a current land uplift rate of 4.4 mm year^?1. Methods We sampled 17 islands differing in area (0.55–55 ha), height (3.6–18 m, representing c. 800–4000 years of age) and distance from mainland (1.6–41 km). For each Sphagnum patch we measured area, height above sea level, horizontal distance from the shore and shading from vascular plants. Factors affecting island species richness, species frequency and habitats on the islands were tested by stepwise regressions. Species frequency was tested on nine life history and autecological variables, including estimated abundance and spore output on the mainland, habitat preference and distribution. Results We recorded 500 patches of 19 Sphagnum species, distributed in 83 rock pools on 14 islands. Island species richness correlated positively with island area and with degree of shelter by surrounding islands, while distance from the mainland, connectivity, height or age did not add to the model. Species frequency (number of colonized islands and rock pools) was mainly predicted by spore output on the mainland and by habitat preference (swamp forest species were more frequent than others), while spore size, for example, did not add to the model. Species differed in mean height above and horizontal distance from the shore, area of occupied rock pools and in the degree of shading of patches. The mean horizontal distance from the shore and the area of occupied rock pools correlated positively with the normal growth position above the water table among species. Spore capsules were found in only 2% of patches, mostly in the bisexual Sphagnum fimbriatum. Main conclusions The presence of Sphagnum in the Stockholm archipelago seems to be governed by regional spore production and habitat demands. Sphagnum does not appear to be dispersal limited at distances up to 40 km and time spans of centuries. Species with a high regional spore output have had a higher colonization rate, which, together with the rarity of spore capsules on the islands, indicate the mainland as a source for colonization rather than dispersal among islands. Swamp forest species seem more tolerant to the island conditions (summer droughts and some salt spray) than open mire species. The different distances from the sea occupied by the species indicate a slow, continuous succession and species replacement towards the island interior as islands are being uplifted and thus expand in area. This partly explains why larger islands harbour more species. Our results thus support some of the island biogeographical theories related to the species–area relationship.     

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.     

Ant communities on small tropical islands: effects of island size and isolation are obscured by habitat disturbance and ‘tramp’ ant species

Aim Comparisons among islands offer an opportunity to study the effects of biotic and abiotic factors on small, replicated biological communities. Smaller population sizes on islands accelerate some ecological processes, which may decrease the time needed for perturbations to affect community composition. We surveyed ants on 18 small tropical islands to determine the effects of island size, isolation from the mainland, and habitat disturbance on ant community composition. Location Thousand Islands Archipelago (Indonesian name: Kepulauan Seribu) off Jakarta, West Java, Indonesia. Methods Ants were sampled from the soil surface, leaf litter and vegetation in all habitat types on each island. Island size, isolation from the mainland, and land‐use patterns were quantified using GIS software. The presence of settlements and of boat docks were used as indicators of anthropogenic disturbance. The richness of ant communities and non‐tramp ant species on each island were analysed in relation to the islands’ physical characteristics and indicators of human disturbance. Results Forty‐eight ant species from 5 subfamilies and 28 genera were recorded from the archipelago, and approximately 20% of the ant species were well‐known human‐commensal ‘tramp’ species. Islands with boat docks or human settlements had significantly more tramp species than did islands lacking these indicators of anthropogenic disturbance, and the diversity of non‐tramp species decreased with habitat disturbance. Main conclusions Human disturbance on islands in the Thousand Islands Archipelago promotes the introduction and/or establishment of tramp species. Tramp species affect the composition of insular ant communities, and expected biogeographical patterns of ant richness are masked. The island with the greatest estimated species richness and the greatest number of unique ant species, Rambut Island, is a forested bird sanctuary, highlighting the importance of protected areas in preserving the diversity of species‐rich invertebrate faunas.     

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.     

Island biogeography of the Mediterranean sea: the species–area relationship for terrestrial isopods

Aim We looked at the biogeographical patterns of Oniscidean fauna from the small islands of the Mediterranean Sea in order to investigate the species–area relationship and to test for area‐range effects. Location The Mediterranean Sea. Methods We compiled from the literature a data set of 176 species of Oniscidea (terrestrial isopods) distributed over 124 Mediterranean islands. Jaccard's index was used as input for a UPGMA cluster analysis. The species–area relationship was investigated by applying linear, semi‐logarithmic, logarithmic and sigmoid models. We also investigated a possible ‘small island effect’ (SIE) by performing breakpoint regression. We used a cumulative and a sliding‐window approach to evaluate scale‐dependent area‐range effects on the log S/log A regression parameters. Results Based on similarity indexes, results indicated that small islands of the Mediterranean Sea can be divided into two major groups: eastern and western. In general, islands from eastern archipelagos were linked together at similarity values higher than those observed for western Mediterranean islands. This is consistent with a more even distribution of species in the eastern Mediterranean islands. Separate archipelagos in the western Mediterranean could be discriminated, with the exception of islets, which tended to group together at the lowest similarity values regardless of the archipelago to which they belong. Islets were characterized by a few common species with large ranges. The species–area logarithmic model did not always provide the best fit. Most continental archipelagos showed very similar intercepts, higher than the intercept for the Canary island oceanic archipelago. Sigmoid regression returned convex curves. Evidence for a SIE was found, whereas area‐range effects that are dependent on larger scale analyses were not unambiguously supported. Main conclusions The Oniscidea fauna from small islands of the Mediterranean Sea is highly structured, with major and minor geographical patterns being identifiable. Some but not all of the biogeographical complexity can be explained by interpreting the different shapes of species–area curves. Despite its flexibility, the sigmoid model tested did not always provide the best fit. Moreover, when the model did provide a good fit the curves looked convex, not sigmoid. We found evidence for a SIE, and minor support for scale‐dependent area‐range effects.     

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’.     

The influence of matrix and edges on species richness patterns of ground beetles (Coleoptera: Carabidae) in habitat islands

Aim The aim of this study was to analyse whether, and how, the inclusion of habitat specialists and edge‐preferring species modifies the species–area relationship predictions of the island biogeography theory for an insect group (ground beetles, Coloptera: Carabidae) living in natural fragments. Species–habitat island area relationships applied to terrestrial habitat islands can be distorted by the indiscriminate inclusion of all species occurring in the fragments. Matrices surrounding terrestrial habitat fragments can provide colonists that do not necessarily distinguish the fragment from the matrix and can survive and reproduce there. Edge‐preferring species can further distort the expected relationship, as smaller fragments have larger edge:core ratios. Location Nineteen forest fragments were studied in the Bereg Plain, Hungary, and SW Ukraine. This area contains natural forest patches, mainly of oak and hornbeam, and supports a mountain entomofauna. Methods Ground beetles (Carabidae) present in the 19 forest patches were categorized into generalists, forest specialists and edge‐preferring species. We analysed the relationship between species richness and fragment area using species richness in the different categories. Results The assemblages contained a high share of generalist species (species that occur also in the surrounding matrix). Forest patch size and the number of generalist species showed a marginally significant negative relationship, indicating that generalist species were more important in smaller patches. Forest specialist species richness was correlated positively with patch area. Edge‐preferring species were shown to influence the species–area relationship: the number of edge‐preferring species increased with the edge:area ratio. Main conclusions Both generalist and edge‐preferring species can considerably distort the species–area relationship. Island biogeography theory can be applied to habitat islands only if the habitat islands are defined correctly from the viewpoint of the target species.     

How island size and isolation affect bee and wasp ensembles on small tropical islands: a case study from Kepulauan Seribu,Indonesia

Aim To study the effects of isolation and size of small tropical islands on species assemblages of bees (superfamily Apoidea) and wasps (superfamily Vespoidea). Location Twenty islands in the Kepulauan Seribu Archipelago off the coast of west Java, Indonesia. The size of surveyed islands ranges between 0.75 and 41.32 ha; their distance from the coast of Java varies between 3 and 62 km. Methods Field work was conducted from February to May 2005. Bees and wasps were caught with a sweep net during sampling units of 15 min, continuing until four consecutive samples revealed no new species. Total species richness was quantified by the estimators Chao 2, first‐order jackknife and Michaelis–Menten. The software binmatnest was used to test for nestedness of species assemblages. Similarities of species composition between islands were quantified by Sørensen’s similarity index. Results Eighty‐two species were recorded on the 20 surveyed islands. Species richness declined with increasing isolation of islands from the source area, Java. Although the size of the largest island exceeded that of the smallest island by a factor of almost 60, island size only very weakly affected species richness of bees; no effect of island size was found for wasps. Mean body size of species decreased with increasing island isolation. Nestedness of island faunas was only weakly developed. Species composition of both superfamilies was affected by island isolation, but not by island size. Main conclusions While the species–isolation relationship on the very small islands of Kepulauan Seribu followed the prediction of MacArthur and Wilson’s equilibrium theory, the absence of a species–area relationship indicated a weak ‘small‐island effect’, at least in wasps. The combination of an only weakly developed pattern of nested species subsets, the shift in species compositions and the decline of mean body size with increasing island isolation from the source area indicates that biotic interactions and different species traits contribute to the shaping of communities of bees and wasps within the archipelago. The potential of biotic interactions for generating distribution patterns of species within the archipelago is also emphasized by the observed restriction of some species with apparently high dispersal abilities to outer islands.     

Are species–area relationships from entire archipelagos congruent with those of their constituent islands?

Aim To establish the extent to which archipelagos follow the same species–area relationship as their constituent islands and to explore the factors that may explain departures from the relationship. Location Thirty‐eight archipelagos distributed worldwide. Methods We used ninety‐seven published datasets to create island species–area relationships (ISARs) using the Arrhenius logarithmic form of the power model. Observed and predicted species richness of an archipelago and of each of its islands were used to calculate two indices that determined whether the archipelago followed the ISAR. Archipelagic residuals (ArcRes) were calculated as the residual of the prediction provided by the ISAR using the total area of the archipelago, standardized by the total richness observed in the archipelago. We also tested whether any characteristic of the archipelago (geological origin and isolation) and/or taxon accounts for whether an archipelago fits into the ISAR or not. Finally, we explored the relationship between ArcRes and two metrics of nestedness. Results The archipelago was close to the ISAR of its constituent islands in most of the cases analysed. Exceptions arose for archipelagos where (i) the slopes of the ISAR are low, (ii) observed species richness is higher than expected by the ISAR and/or (iii) distance to the mainland is small. The archipelago's geological origin was also important; a higher percentage of oceanic archipelagos fit into their ISAR than continental ones. ArcRes indicated that the ISAR underpredicts archipelagic richness in the least isolated archipelagos. Different types of taxon showed no differences in ArcRes. Nestedness and ArcRes appear to be related, although the form of the relationship varies between metrics. Main conclusions Archipelagos, as a rule, follow the same ISAR as their constituent islands. Therefore, they can be used as distinct units themselves in large‐scale biogeographical and macroecological studies. Departure from the ISAR can be used as a crude indicator of richness‐ordered nestedness, responsive to factors such as isolation, environmental heterogeneity, number and age of islands.