Nestedness in insular floras: spatiotemporal variation and underlying mechanisms

Aims Nestedness is a characteristic of insular metacommunity structure. Relatively few studies, however, have attempted to evaluate temporal changes in nestedness, or elucidate the mechanisms underlying nestedness. I evaluated both spatial and temporal patterns of nestedness in the insular floras of four archipelagoes of small islands in the Bahamas and the potential underlying environmental gradients.Methods The NODF (a nestedness metric based on overlap and decreasing fill) and the matrix temperature measure, T, were used to quantify nestedness in insular floras on small islands near Abaco, Andros, Great Exuma and the Exuma Cays, Bahamas. Two different null models were employed for each nestedness measure. Six environmental variables were evaluated in relation to nestedness by ordering islands according to gradients and recalculating NODF scores.Important findings All archipelagoes were significantly nested. Nestedness among sites contributed more to overall nestedness than did nestedness among species. NODF scores varied among archipelagoes, but were surprisingly constant over time. Ordering islands by vegetated area yielded the highest nestedness scores for three archipelagoes; ordering islands by protection from exposure yielded the highest nestedness score for one archipelago. Nestedness scores varied little over time even though species compositions changed, indicating that extinctions occurred in a deterministic manner. The relative importance of area suggests extinction is an important mechanism in producing nestedness. Attempting to determine the relative importance of immigrations or extinctions requires some assumptions, however, and both processes are likely cumulative in most cases.     

Global diversity of island floras from a macroecological perspective

Islands harbour a significant portion of all plant species worldwide. Their biota are often characterized by narrow distributions and are particularly susceptible to biological invasions and climate change. To date, the global richness pattern of islands is only poorly documented and factors causing differences in species numbers remain controversial. Here, we present the first global analysis of 488 island and 970 mainland floras. We test the relationship between island characteristics (area, isolation, topography, climate and geology) and species richness using traditional and spatial models. Area is the strongest determinant of island species numbers ( R ² = 0.66) but a weaker predictor for mainlands ( R ² = 0.25). Multivariate analyses reveal that all investigated variables significantly contribute to insular species richness with area being the strongest followed by isolation, temperature and precipitation with about equally strong effects. Elevation and island geology show relatively weak yet significant effects. Together these variables account for 85% of the global variation in species richness.     

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

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

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.     

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.

     

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.     

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.     

温州沿海小型海岛植物丰富度和β多样性及其影响因子

于2012-2015年调查了温州沿海20个小型无居民海岛的植物组成,共记录到维管束植物366种,隶属于95科244属,其中草本植物226种木本植物140种。拟合了5个种-面积关系模型,采用赤池信息量AIC对模型进行选择,发现种-面积-生境类型关系模型SAH_nR权重系数最大,为40.26%,两种断点回归种-面积关系模型BR-SAR权重系数分别仅为6.94%和0.43%,表明基于这20个海岛拟合的种-面积关系不存在小岛屿效应。岛屿植物物种丰富度主要受面积A影响,离大陆距离,I_m对丰富度无显著作用;偏相关分析表明除A外,周长/面积比PAR和岛屿生境多样性指数H_d显著影响了植物丰富度,其逐步回归方程分别为:植物总丰富度S=76.714+1.696A-0.046PAR,R~2=0.839;木本植物丰富度S_(-woody)=6.525+0.455A+24.544H_d,R~2=0.697;草本植物丰富度S_(-herbaceous)=66.899+1.285A-0.04PAR-23.434H_d,R~2=0.865。偏最小二乘回归PLS分析中岛屿空间特征参数对岛屿物种相似性指数重要性排序为:I_m(0.61)I_i(0.56)PAR(0.49)A(0.20)岸线长度Per(0.14)生境类型H(0.072)岛屿高程E(0.065)岛屿形状指数SI(0.05)。由此可见,近岸的小型海岛植物丰富度并不总是由岛屿面积来决定;隔离度对岛屿植物β多样性影响较大。     

Breaking taboos in the tropics: incest promotes colonization by wood-boring beetles

• 1 Inbreeding and parthenogenesis are especially frequent in colonizing species of plants and animals, and inbreeding in wood‐boring species in the weevil families Scolytinae and Platypodidae is especially common on small islands. In order to study the relationship between colonization success, island attributes and mating system in these beetles, we analysed the relative proportions of inbreeders and outbreeders for 45 Pacific and Old World tropical islands plus two adjacent mainland sites, and scored islands for size, distance from nearest source population, and maximum altitude.
• 2 The numbers of wood‐borer species decreased with decreasing island size, as expected; the degree of isolation and maximum island altitude had negligible effects on total species numbers.
• 3 Numbers of outbreeding species decreased more rapidly with island size than did those of inbreeders. Comparing species with similar ecology (e.g. ambrosia beetles) showed that this difference was best explained by differential success in colonization, rather than by differences in resource utilization or sampling biases. This conclusion was further supported by analyses of data from small islands, which suggested that outbreeding species have a higher degree of endemism and that inbreeding species are generally more widespread.
• 4 Recently established small populations necessarily go through a period of severe inbreeding, which should affect inbreeding species much less than outbreeding ones. In addition, non‐genetic ecological and behavioural (‘Allee’) effects are also expected to reduce the success of outbreeding colonists much more than that of inbreeders: compared with inbreeders, outbreeders are expected to have slower growth rates, have greater difficulties with mate‐location and be vulnerable to random extinction over a longer period.

     

Impact of geographical isolation on genetic differentiation in insular and mainland populations of Weigela coraeensis (Caprifoliaceae) on Honshu and the Izu Islands

Aim To provide insights into genetic differentiation between insular endemic Weigela coraeensis var. fragrans and its progenitor variety W. coraeensis var. coraeensis, the population genetic structure of both varieties was examined, and factors promoting genetic differentiation between the two taxa were explored. Location The natural range of W. coraeensis (sensu lato) throughout mainland Japan (Honshu) and the Izu Islands. Methods The analysis included 349 and 504 individuals across the mainland (Honshu) and the Izu Islands, respectively, using 10 allozyme and 10 microsatellite loci. The population genetic structure of W. coraeensis was assessed by analysing genetic diversity indices for each population, genetic differentiation among populations, model‐based Bayesian clustering or distance‐based clustering, and bottleneck tests. Results The level of genetic diversity in each of the populations on the Izu Islands was negatively correlated with geographical distance between each island and the mainland. The populations on the mainland and on the Izu Islands were genetically differentiated to a certain extent; however, the microsatellite analyses suggested that gene flow also occurred between the mainland and the islands, and among individual islands. These microsatellite analyses also suggested recent bottlenecks in several populations in both areas. Main conclusions The decrease in genetic diversity throughout the Izu Islands, which correlated with distance to the mainland, Honshu, may be the result of a repeated founder effect occurring at a series of inter‐island colonizations from north to south. The stepping stone‐like configuration of the islands may have played a role in the dispersal of the species. Geographical isolation by sea would effectively result in genetic differentiation of W. coraeensis between mainland Honshu and the Izu Islands, although some gene flow may still occur between Honshu and the northern Izu Islands. The differentiation process of the endemic plants on the Izu Islands is anagenetic but not completed, and the study of these plants will provide insightful knowledge concerning the evolution of insular endemics.     

Habitat amount hypothesis and passive sampling explain mammal species composition in Amazonian river islands

Nested structures of species assemblages have been frequently associated with patch size and isolation, leading to the conclusion that colonization–extinction dynamics drives nestedness. The ‘passive sampling’ model states that the regional abundance of species randomly determines their occurrence in patches. The ‘habitat amount hypothesis’ also challenges patch size and isolation effects, arguing that they occur because of a ‘sample area effect’. Here, we (a) ask whether the structure of the mammal assemblages of fluvial islands shows a nested pattern, (b) test whether species’ regional abundance predicts species’ occurrence on islands, and (c) ask whether habitat amount in the landscape and matrix resistance to biological flow predict the islands’ species composition. We quantified nestedness and tested its significance using null models. We used a regression model to analyze whether a species’ relative regional abundance predicts its incidence on islands. We accessed islands’ species composition by an NMDS ordination and used multiple regression to evaluate how species composition responds to habitat amount and matrix resistance. The degree of nestedness did not differ from that expected by the passive sampling hypothesis. Likewise, species’ regional abundance predicted its occurrence on islands. Habitat amount successfully predicted the species composition on islands, whereas matrix resistance did not. We suggest the application of habitat amount hypothesis for predicting species composition in other patchy systems. Although the island biogeography perspective has dominated the literature, we suggest that the passive sampling perspective is more appropriate for explaining the assemblages’ structure in this and other non‐equilibrium patch systems. Abstract in Portuguese is available with online material.     

Patterns of fish community composition along a river affected by agricultural and urban disturbance in south-central Chile

Patterns of fish community composition in a south-central Chile river were investigated along the altitudinal-spatial and environmental gradient and as a function of anthropogenic factors. The spatial pattern of fish communities in different biocoenotic zones of the Chillan River is influenced by both natural factors such a hydrologic features, habitat, and feeding types, and also by water quality variables which can reduce the diversity and abundance of sensitive species. A principal component analysis incorporating both water quality parameters and biomarker responses of representative fish species was used to evaluate the status of fish communities along the spatial gradient of the stream. The abundance and diversity of the fish community changed from a low in the upper reaches where the low pollution-tolerant species such as salmonid dominated, to a reduced diversity in the lower reaches of the river where tolerant browser species such as cypriniformes dominated. Even though the spatial pattern of fish community structure is similar to that found for the Chilean Rivers, the structure of these communities is highly influenced by human disturbance, particularly along the lower reaches of the river. Handling editor: C. Sturmbauer     

Small area and low connectivity constrain the diversity of plant life strategies in temporary ponds

Aim

(i) To determine whether area and connectivity of temporary ponds can predict plant species diversity, and the diversity and abundance of different plant life histories; (ii) To explore whether pond connectivity with the river prior to river regulation predicts better plant diversity patterns than current pond connectivity, suggestive of possible effects of connectivity loss.

Location

Eastern Carpathian Mountains, Romania, Europe.

Methods

We fitted linear and generalized linear models (LM and GLM) to examine whether pond area and current distance from the Olt River predict plant species richness, Shannon diversity and relative cover of different social behaviour types and overall plant species richness and Shannon diversity. Using historical maps, we measured pond distance from the river ca. 60 years before the Olt River was regulated, and we refitted the LM and GLM models using pond area and past distance from the river as independent variables.

Results

Total plant species richness increased with pond area, and it decreased with the distance from the river, but total plant Shannon diversity index was affected, positively, only by pond area. The strength of responses to pond area and connectivity of species richness, Shannon diversity and relative cover varied across the different social behaviour types. Past and current distances between ponds and riverbeds had similar effects on plant diversity, with some evidence for stronger effect of the present connectivity on specialist species Shannon diversity and a weaker effect on disturbance tolerants, generalists and competitors.

Main Conclusions

Pond area and connectivity with the landscape are important predictors of the diversity of plant life history strategies, and therefore, useful tools in pond conservation. Consistent species richness and Shannon diversity responses of wetland specialists to pond area and connectivity make this life history type well suited for monitoring pond condition.