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.     

Species richness, rarity and endemicity on Italian offshore islands: complementary signals from island-focused and species-focused analyses

Aims To investigate the relative explanatory power of source faunas and geographical variables for butterfly incidence, frequency, richness, rarity, and endemicity on offshore islands. Location The western Italian offshore islands (Italy and Malta). Methods Thirty‐one islands were examined. Data were taken from our own field surveys and from the literature. Two approaches were undertaken, described as island‐focused and species‐focused, respectively. Offshore islands were allocated to their neighbouring source landmasses (Italian Peninsula, Sicily and Sardinia–Corsica) and compared with each other for faunal attributes, source and island geography. Generalized linear and stepwise multiple regression models were then used to determine the relationships of island species richness, rarity and endemicity with potential geographical predictors and source richness, rarity, and endemicity (island‐focused). Species frequency and incidence were assessed in relation to geographical and source predictors using stepwise linear and logistic regression, and inter‐island associations were examined using K‐Means clustering and non‐metric scaling (species‐focused). Results The analysis reveals firm evidence for the influence of the nearest large landmass sources on island species assemblages, richness, rarity and endemicity. A clear distinction in faunal affinities occurs between the Sardinian islands and islands lying offshore from the Italian mainland and Sicily. Islands neighbouring these three distinct sources differ significantly in richness, rarity and endemicity. Source richness, rarity, and endemicity have explanatory power for island richness, rarity, and endemicity, respectively, and together with island geography account for a substantial part of the variation in island faunas (richness 59%, rarity 60% and endemicity 64%). Source dominates the logistic regression parameters predicting the incidence of island species [13 (38%) of 34 species that could be analysed]; three ecological factors (source frequency, flight period and maximal altitude at which species live) explained 75% of the variation in the occurrence of species on the islands. Species found more frequently on islands occurred more frequently at sources, had longer flight periods, and occurred at lower altitudes at the sources. The incidence of most species on islands (84%) is correctly predicted by the same three variables. Main conclusions The Italian region of the Mediterranean Sea has a rich butterfly fauna comprising endemics and rare species as well as more cosmopolitan species. Analysis of island records benefited from the use of two distinct approaches, namely island‐focused and species‐focused, that sift distinct elements in island and source faunas. Clear contemporary signals appear in island–source relationships as well as historical signals. Differences among faunas relating to sources within the same region caution against assuming that contemporary (ecological) and historical (evolutionary) influences affect faunas of islands in different parts of the same region to the same extent. The implications of source–island relationships for the conservation of butterflies within the Italian region are considered, particularly for the long‐term persistence of species.     

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.     

Extinction‐driven changes in frugivore communities on oceanic islands

Global change and human expansion have resulted in many species extinctions worldwide, but the geographic variation and determinants of extinction risk in particular guilds still remain little explored. Here, we quantified insular extinctions of frugivorous vertebrates (including birds, mammals and reptiles) across 74 tropical and subtropical oceanic islands within 20 archipelagos worldwide and investigated extinction in relation to island characteristics (island area, isolation, elevation and climate) and species’ functional traits (body mass, diet and ability to fly). Out of the 74 islands, 33 islands (45%) have records of frugivore extinctions, with one third (mean: 34%, range: 2–100%) of the pre‐extinction frugivore community being lost. Geographic areas with more than 50% loss of pre‐extinction species richness include islands in the Pacific (within Hawaii, Cook Islands and Tonga Islands) and the Indian Ocean (Mascarenes, Seychelles). The proportion of species richness lost from original pre‐extinction communities is highest on small and isolated islands, increases with island elevation, but is unrelated to temperature or precipitation. Large and flightless species had higher extinction probability than small or volant species. Across islands with extinction events, a pronounced downsizing of the frugivore community is observed, with a strong extinction‐driven reduction of mean body mass (mean: 37%, range: –18–100%) and maximum body mass (mean: 51%, range: 0–100%). The results document a substantial trophic downgrading of frugivore communities on oceanic islands worldwide, with a non‐random pattern in relation to geography, island characteristics and species’ functional traits. This implies severe consequences for ecosystem processes that depend on mutualistic plant–animal interactions, including ecosystem dynamics that result from the dispersal of large‐seeded plants by large‐bodied frugivores. We suggest that targeted conservation and rewilding efforts on islands are needed to halt the defaunation of large and non‐volant seed dispersers and to restore frugivore communities and key ecological interactions.     

Narrow water barriers prevent multiple colonizations and limit gene flow among California Channel Island wild buckwheats (Eriogonum: Polygonaceae)

The relative roles of chance colonization and subsequent gene flow in the development of insular endemic biotas have been extensively studied in remote oceanic archipelagos, but are less well characterized on nearshore island systems. The current study investigated patterns of colonization and divergence between and within two wild buckwheat species (Polygonaceae), Eriogonum arborescens and E. giganteum, endemic to the California Channel Islands to determine whether geographical isolation is driving diversification. Using plastid and nuclear sequence data and microsatellite allele frequencies, we determined that gene flow in these Eriogonum spp. is restricted by isolation. The data suggest that successful colonization of and gene flow among the islands are infrequent. Colonization appears to have followed a stepping‐stone model that is consistent with a north‐to‐south pattern across the islands. This colonization pattern coupled with relatively little post‐colonization inter‐island gene flow, particularly among southern islands, has generated a pattern of more divergent lineages on the isolated southern islands. These results run counter to the general expectation that all islands close to a continental source should receive a high level of gene flow. Finally, management recommendations focused on protecting the lineages from loss of private alleles and the erosion of the remaining genetic diversity are offered.     

Biodiversity growth on the volcanic ocean islands and the roles of in situ cladogenesis and immigration: case with the reptiles

Models for biodiversity growth on the remote oceanic islands assume that in situ cladogenesis is a major contributor. To test this, we compiled occurrence data for 194 terrestrial reptile species on 53 volcanically‐constructed middle‐ to low‐latitude landmasses worldwide. Despite 273 native island‐species records, there are only 8–12 cases of the phenomenon, including just two radiations. Diversification frequencies are largely uncorrelated with island area, age, maximum altitude, and isolation. Furthermore, there is no indication that the presence of non‐sister congeners on an island stymies the process. Diversity on individual oceanic islands therefore results primarily from immigration and anageneis, but this is not a simple matter. Clusters that are difficult to reach (far or challenging to get to) or thrive upon (e.g. Canaries, Galápagos) have relatively few clades (3–8), some of which have many species (6–14), and all host at least one endemic genus. In these settings, diversity grows mainly by intra‐archipelago transfer followed by within‐island anagenetic speciation. In contrast, those island groups that are easier to disperse to (characterized by short distances and conducive transit conditions) and harbour more benign habitats (e.g. Comoros, Lesser Antilles) have been settled by many ancestor‐colonizers (≥ 14), but each clade has few derived species (≤ 4). These archipelagoes lack especially distinctive lineages. Models explaining the assembly and growth of terrestrial biotic suites on the volcanic ocean islands thus need to accommodate these new insights.     

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.     

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.     

Terrestrial bird community patterns on the coralline islands of the Dahlak Archipelago, Red Sea, Eritrea

Aim This study aims to explain the patterns of species richness and nestedness of a terrestrial bird community in a poorly studied region. Location Twenty‐six islands in the Dahlak Archipelago, Southern Red Sea, Eritrea. Methods The islands and five mainland areas were censused in summer 1999 and winter 2001. To study the importance of island size, isolation from the mainland and inter‐island distance, I used constrained null models for the nestedness temperature calculator and a cluster analysis. Results Species richness depended on island area and isolation from the mainland. Nestedness was detected, even when passive sampling was accounted for. The nested rank of islands was correlated with area and species richness, but not with isolation. Idiosyncrasies appeared among species‐poor and species‐rich islands, and among common and rare species. Cluster analysis showed differences among species‐rich islands, close similarity among species‐poor and idiosyncratic islands, and that the compositional similarity among islands decreased with increasing inter‐island distance. Thus, faunas of species‐poor, smaller islands were more likely to be subsets of faunas of species‐rich, larger islands if the distance between the islands was short. Main conclusions Species richness and nestedness were related to island area, and nestedness also to inter‐island distances but not to isolation from the mainland. Thus, nestedness and species richness are not affected in the same way by area and distance. Moreover, idiosyncrasies may have been the outcome of species distributions among islands being influenced also by non‐nested distributions of habitats, inter–specific interactions, and differences in species distributions across the mainland. Idiosyncrasies in nested patterns may be as important as the nested pattern itself for conservation – and conservation strategies based on nestedness and strong area effects (e.g. protection of only larger islands) may fail to preserve idiosyncratic species/habitats.     

Subjecting the theory of the small‐island effect to Ockham’s razor

Species–area curves from islands and other isolates often differ in shape from sample‐area curves generated from mainlands or sections of isolates (or islands), especially at finer scales. We examine two explanations for this difference: (1) the small‐island effect (SIE), which assumes the species–area curve is composed of two distinctly different curve patterns; and (2) a sigmoid or depressed isolate species–area curve with no break‐points (in arithmetic space). We argue that the application of Ockham’s razor – the principle that the simplest, most economical explanation for a hypothesis should be accepted over less parsimonious alternatives – leads to the conclusion that the latter explanation is preferable. We hold that there is no reason to assume the ecological factors or patterns that affect the shapes of isolate (or island) curves cause two distinctly different patterns. This assumption is not required for the alternative, namely that these factors cause a single (though depressed) isolate species–area curve with no break‐points. We conclude that the theory of the small‐island effect, despite its present standing as an accepted general pattern in nature, should be abandoned.     

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.     

Increase of island endemism with altitude – speciation processes on oceanic islands

Understanding speciation on oceanic islands is a major topic in current research on island biogeography. Within this context, it is not an easy task to differentiate between the influence of elevation as an indicator for habitat diversity and island age as an indicator for the time available for diversification. One reason for this is that erosion processes reduce the elevation of islands over time. In addition, the geographic distance to source ecosystems might differ among habitats, which could lead to habitat‐specific reduction of species immigration, niche occupation and diversification. We used the percentage of single island endemic species (pSIE) in five different zonal ecosystems (distributed in altitude) on the Canary Islands as an indicator for diversification. We tested whether diversification increases with altitude due to a greater ecological isolation of high elevation ecosystems on oceanic islands under the assumption of a low elevation source region on the mainland. In addition we tested whether the ‘hump‐shaped’ (unimodal) relationship between pSIE and island age as well as the linear relationship between species richness and pSIE is consistent across spatial scales. We also analyse a potential influence of island area and habitat area. We found that pSIE increases with elevation. The relations between species richness as well as age with pSIE are consistent across scales. We conclude that high elevation ecosystems are ecologically isolated. Surprisingly, the altitudinal belt with the strongest human influences has the highest values of pSIE. We successfully transfer the ‘general dynamic theory of island biogeography’ to the ecosystem scale, which provides multiple opportunities for future studies. With this approach we find that the effects of elevation on diversification can be separated from those of island age.     

Inferring dispersal: a Bayesian approach to phylogeny-based island biogeography, with special reference to the Canary Islands

Aim Oceanic islands represent a special challenge to historical biogeographers because dispersal is typically the dominant process while most existing methods are based on vicariance. Here, we describe a new Bayesian approach to island biogeography that estimates island carrying capacities and dispersal rates based on simple Markov models of biogeographical processes. This is done in the context of simultaneous analysis of phylogenetic and distributional data across groups, accommodating phylogenetic uncertainty and making parameter estimates more robust. We test our models on an empirical data set of published phylogenies of Canary Island organisms to examine overall dispersal rates and correlation of rates with explanatory factors such as geographic proximity and area size. Location Oceanic archipelagos with special reference to the Atlantic Canary Islands. Methods The Canary Islands were divided into three island‐groups, corresponding to the main magmatism periods in the formation of the archipelago, while non‐Canarian distributions were grouped into a fourth ‘mainland‐island’. Dispersal between island groups, which were assumed constant through time, was modelled as a homogeneous, time‐reversible Markov process, analogous to the standard models of DNA evolution. The stationary state frequencies in these models reflect the relative carrying capacity of the islands, while the exchangeability (rate) parameters reflect the relative dispersal rates between islands. We examined models of increasing complexity: Jukes–Cantor (JC), Equal‐in, and General Time Reversible (GTR), with or without the assumption of stepping‐stone dispersal. The data consisted of 13 Canarian phylogenies: 954 individuals representing 393 taxonomic (morphological) entities. Each group was allowed to evolve under its own DNA model, with the island‐model shared across groups. Posterior distributions on island model parameters were estimated using Markov Chain Monte Carlo (MCMC) sampling, as implemented in MrBayes 4.0, and Bayes Factors were used to compare models. Results The Equal‐in step, the GTR, and the GTR step dispersal models showed the best fit to the data. In the Equal‐in and GTR models, the largest carrying capacity was estimated for the mainland, followed by the central islands and the western islands, with the eastern islands having the smallest carrying capacity. The relative dispersal rate was highest between the central and eastern islands, and between the central and western islands. The exchange with the mainland was rare in comparison. Main conclusions Our results confirm those of earlier studies suggesting that inter‐island dispersal within the Canary Island archipelago has been more important in explaining diversification within lineages than dispersal between the continent and the islands, despite the close proximity to North Africa. The low carrying capacity of the eastern islands, uncorrelated with their size or age, fits well with the idea of a historically depauperate biota in these islands but more sophisticated models are needed to address the possible influence of major recent extinction events. The island models explored here can easily be extended to address other problems in historical biogeography, such as dispersal among areas in continental settings or reticulate area relationships.     

A global comparison of plant invasions on oceanic islands

Oceanic islands have long been considered to be particularly vulnerable to biotic invasions, and much research has focused on invasive plants on oceanic islands. However, findings from individual islands have rarely been compared between islands within or between biogeographic regions. We present in this study the most comprehensive, standardized dataset to date on the global distribution of invasive plant species in natural areas of oceanic islands. We compiled lists of moderate (5–25% cover) and dominant (>25% cover) invasive plant species for 30 island groups from four oceanic regions (Atlantic, Caribbean, Pacific, and Western Indian Ocean). To assess consistency of plant behaviour across island groups, we also recorded present but not invasive species in each island group.We tested the importance of different factors discussed in the literature in predicting the number of invasive plant species per island group, including island area and isolation, habitat diversity, native species diversity, and human development. Further we investigated whether particular invasive species are consistently and predictably invasive across island archipelagos or whether island-specific factors are more important than species traits in explaining the invasion success of particular species.We found in total 383 non-native spermatophyte plants that were invasive in natural areas on at least one of the 30 studied island groups, with between 3 and 74 invaders per island group. Of these invaders about 50% (181 species) were dominants or co-dominants of a habitat in at least one island group. An extrapolation from species accumulation curves across the 30 island groups indicates that the total current flora of invasive plants on oceanic islands at latitudes between c. 35°N and 35°S may eventually consist of 500–800 spermatophyte species, with 250–350 of these being dominant invaders in at least one island group. The number of invaders per island group was well predicted by a combination of human development (measured by the gross domestic product (GDP) per capita), habitat diversity (number of habitat types), island age, and oceanic region (87% of variation explained). Island area, latitude, isolation from continents, number of present, non-native species with a known invasion history, and native species richness were not retained as significant factors in the multivariate models.Among 259 invaders present in at least five island groups, only 9 species were dominant invaders in at least 50% of island groups where they were present. Most species were invasive only in one to a few island groups although they were typically present in many more island groups. Consequently, similarity between island groups was low for invader floras but considerably higher for introduced (but not necessarily invasive) species – especially in pairs of island groups that are spatially close or similar in latitude. Hence, for invasive plants of natural areas, biotic homogenization among oceanic islands may be driven by the recurrent deliberate human introduction of the same species to different islands, while post-introduction processes during establishment and spread in natural areas tend to reduce similarity in invader composition between oceanic islands. We discuss a number of possible mechanisms, including time lags, propagule pressure, local biotic and abiotic factors, invader community assembly history, and genotypic differences that may explain the inconsistent performance of particular invasive species in different island groups.     

Nestedness in island faunas: novel insights into island biogeography through butterfly community profiles of colonization ability and migration capacity

Aim To relate variation in the migration capacity and colonization ability of island communities to island geography and species island occupancy. Location Islands off mainland Britain and Ireland. Methods Mean migration (transfer) capacity and colonization (establishment) ability (ecological indices), indexed from 12 ecological variables for 56 butterfly species living on 103 islands, were related to species nestedness, island and mainland source geography and indices using linear regression models, RLQ analysis and fourth‐corner analysis. Random creation of faunas from source species, rank correlation and rank regression were used to examine differences between island and source ecological indices, and relationships to island geography. Results Island butterfly faunas are highly nested. The two ecological indices related closely to island occupancy, nestedness rank of species, island richness and geography. The key variables related to migration capacity were island area and isolation; for colonization ability they were area, isolation and longitude. Compared with colonization ability, migration capacity was found to correlate more strongly with island species occupancy and species richness. For island faunas, the means for both ecological indices decreased, and variation increased, with increasing island species richness. Mean colonization ability and migration capacity values were significantly higher for island faunas than for mainland source faunas, but these differences decreased with island latitude. Main conclusions The nested pattern of butterfly species on islands off mainland Britain and Ireland relates strongly to colonization ability but especially to migration capacity. Differences in colonization ability among species are most obvious for large, topographically varied islands. Generalists with abundant multiple resources and greater migration capacity are found on all islands, whereas specialists are restricted to large islands with varied and long‐lived biotopes, and islands close to shore. The inference is that source–sink dynamics dominate butterfly distributions on British and Irish islands; species are capable of dispersing to new areas, but, with the exception of large and northern islands, facilities (resources) for permanent colonization are limited. The pattern of colonization ability and migration capacity is likely to be repeated for mainland areas, where such indices should provide useful independent measures for assessing the conservation status of faunas within spatial units.     

无居民海岛开发生态损害评估——以象山县大羊屿岛为例

无居民海岛独特的生态系统和地理位置决定了受损后的修复成本极高、开发难度极大,其保护与开发已经成为国内外学界关注的重点。基于海岛生态系统服务价值理论构建了无居民海岛开发的生态损害评估模型,以我国首个公开拍卖使用权的大羊屿岛为例验证模型的科学性和可行性,并与2018年调整后的无居民海岛使用金征收标准中生态损害成本额度进行对比分析。研究结果表明：（1）大羊屿岛开发的生态损害补偿金为1644.82万元。其中,陆域开发行为所需的生态损害补偿金为890.19万元,高于海洋开发行为所造成的生态损害补偿金;（2）通过本文计算的海岛陆域生态损害补偿金高出现行海岛使用金标准中的生态损害成本371.90万元,2018年旅游用岛使用金征收标准仍有上调空间。对无居民海岛开发的生态损害评估可以增强政府和企业对于海岛资源的保护意识,重新权衡无居民海岛开发的利弊,避免对海岛资源过度和盲目的开发。     

Not as the crow flies: assessing effective isolation for island biogeographical analysis

Aim To evaluate the role of island isolation in explaining the distribution of vascular plant species in a dense freshwater archipelago, specifically comparing conventional measures of island isolation with landscape measures of island isolation. Location Data were collected from 35 islands within Massasauga Provincial Park on the eastern shores of the Georgian Bay, Ontario, Canada. Methods Sampled islands were located using stratified random selection based on location and size variation. The number of species was recorded along stratified random transects. Island isolation variables included distance to the mainland, distance to the nearest island, largest gap in a stepping‐stone sequence, distance to the closest upwind point of land, and a landscape measure of island isolation. The landscape measure of isolation was quantified as the percentage of the land area within 100, 250, 500, 1000, 1500 and 2000 m of each island’s perimeter. The isolation variables were calculated within a geographical information system (GIS). Dependent variables in the regression analyses included species richness, the logarithm of species richness and residuals of the species–area relationship. Independent variables included island isolation variables and their logarithmic transformations. Results Isolation plays a role, albeit small, in explaining species richness in the study area. In the regression analyses, the landscape measure of isolation provided a better fit than conventional measures of island isolation. Islands with less land than water within a 250‐m buffer were more effectively isolated and had fewer species present than islands surrounded by a greater proportion of water. Main conclusions Consistent with the species–isolation relationship, fewer species were present on more isolated islands within the Massasauga study area, as elucidated using a series of island buffers in a GIS. Applying a landscape measure of isolation to similar dense, freshwater archipelagos may elucidate species–isolation patterns not evident through conventional, straight‐line distance measurements of island isolation. The low value of the regression coefficients as well as the isolation history and high density of the Massasauga islands suggests caution in extending the results, especially to dissimilar archipelagos.     

Population Genetic Structure and Conservation of the Galápagos Petrel (Pterodroma phaeopygia)

The Galápagos petrel (Pterodroma phaeopygia) is endemic to the Galápagos archipelago, where it is known to breed only on five islands. The species has been listed as critically endangered due to habitat deterioration and predation by introduced mammals. Significant morphological and behavioural differences among petrels nesting on different islands suggest that island populations may differ genetically. Furthermore, nesting phenology suggests that genetically differentiated seasonal populations may exist within at least one island. We analysed variation in six microsatellite loci and part of the mitochondrial ATPase 6/8 gene in 206 Galápagos petrels sampled from all five islands. No evidence of genetic structuring within islands was found, although statistical power was low. In contrast, significant differences occurred among island populations. For the microsatellite loci, private alleles occurred at all islands, sometimes at high frequency; global and pairwise estimates of genetic differentiation were all statistically significant; Bayesian analysis of genotypes frequencies provided strong support for three genetic populations; and most estimates of migration between populations did not differ significantly from zero. Only two ATPase haplotypes were found, but the geographic distribution of haplotypes indicated significant differentiation among populations. For conservation purposes, populations from Floreana, Santa Cruz, San Cristóbal and Santiago should be regarded as separate genetic management units. Birds from Isabela appear to be derived recently from the Santiago population, and the population on San Cristóbal appears to be a mixture of birds from other populations. However, considering ecological and behavioural differences among birds from different islands, we recommend that all five populations be protected.     

Predators in natural fragments: foraging ecology of wolves in British Columbia's central and north coast archipelago

Aim Predator–prey dynamics in fragmented areas may be influenced by spatial features of the landscape. Although little is known about these processes, an increasingly fragmented planet underscores the urgency to predict its consequences. Accordingly, our aim was to examine foraging behaviour of an apex mammalian predator, the wolf (Canis lupus), in an archipelago environment. Location Mainland and adjacent archipelago of British Columbia, Canada; a largely pristine and naturally fragmented landscape with islands of variable size and isolation. Methods We sampled 30 mainland watersheds and 29 islands for wolf faeces in summers 2000 and 2001 and identified prey remains. We examined broad geographical patterns and detailed biogeographical variables (area and isolation metrics) as they relate to prey consumed. For island data, we used Akaike Information Criteria to guide generalized linear regression model selection to predict probability of black‐tailed deer (main prey; Odocoileus hemionus) in faeces. Results Black‐tailed deer was the most common item in occurrence per faeces (63%) and occurrence per item (53%) indices, representing about 63% of mammalian biomass. Wolves consumed more deer on islands near the mainland (65% occurrence per item) than on the mainland (39%) and outer islands (45%), where other ungulates (mainland only) and small mammals replaced deer. On islands, the probability of detecting deer was influenced primarily by island distance to mainland (not by area or inter‐landmass distance), suggesting limited recolonization by deer from source populations as a causal mechanism. Main conclusions Although sampling was limited in time, consistent patterns among islands suggest that population dynamics in isolated fragments are less stable and can result in depletion of prey. This may have important implications in understanding predator–prey communities in isolation, debate regarding wolf–deer systems and logging in temperate rain forests, and reserve design.     

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.