Evolutionary species–area curves as revealed by single-island endemics: insights for the inter-provincial species–area relationship

The species–area relationship (SAR) between different biological provinces is one of the most interesting, but least explored aspects of the well-known species–area pattern. Following the usage that a biological province is a region whose species have for the most part evolved within it, rather than immigrating from somewhere else, we propose that islands can be considered equivalent to biological provinces for single island endemic species (SIEs). Hence, analyses of the relationships between numbers of SIEs and island area can be used as model systems to explore the form of inter-provincial SARs. We analyzed 13 different data sets derived from 11 sources, using the power (log–log) model. Eleven of the SIE–area relationships were statistically significant, explaining high proportions of the variance in SIE numbers (R² 0.57–0.95). The z-values (slopes) of the statistically significant SIE–area relationships ranged from 0.47 to 1.13, with a mean value of 0.80 (SD±0.24).
All the island systems in which SIE represent >50% of species exhibited z-values for the SARs of native species higher than those deemed typical of archipelagic SARs. The SIE–area slopes are quite similar to those previously calculated for inter-provincial SARs, indicating that, when speciation becomes the dominant process adding to the species richness of assemblages, high z-values should be anticipated, regardless of the biogeographical scale of the study system.     

Self-similarity in species–area relationship and in species abundance distribution

In an influential paper, Harte et al. highlighted the scaling or 'self-similar' character of the power law species–area relationship (SAR), and used this feature to derive a species abundance distribution (SAD) and an endemics–area relationship. Here I show that their analysis was incorrect and leads to unrealistic results. I develop a different approach and obtain different results, both for SAD and for endemism. In particular, I show that the power law SAR is naturally associated with the power law statistical distribution, which is the only self-similar distribution and closely matches empirical SADs. The results in this paper shed light on some of the main issues that have been discussed with regard to SARs: their relationship with the lognormal and with the neutral theory, the relative importance of sampling effects vs other mechanisms, and the deviations from a power law. The equations that I develop are simple and easy to apply to field studies.     

The species–area relationship does not have an asymptote!

Aim

To attack a widespread myth.

Location

World‐wide.

Methods

Simple mathematical logical and empirical examples.

Results

As both species and area are finite and non‐negative, the species–area relationship is limited at both ends. The log species–log area relationship is normally effectively linear on scales from about 1 ha to 10⁷ km². There are no asymptotes. At the intercontinental scale it may get steeper; at small scales it may in different cases get steeper or shallower or maintain its slope.

Main conclusion

The species–area relationship does not have an asymptote.

     

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.

     

Testing species–stone area and species–bryophyte cover relationships in riverine macroinvertebrates at small scales

1. The species–area relationship is considered amongst the few genuine laws in ecology. Although positive species richness–stone area relationships have been found previously in stream systems, very few studies have simultaneously examined species–individuals, individuals–area, species–bryophyte biomass and individuals–bryophyte biomass relationships. We examined these relationships based on temporally replicated assessments of macroinvertebrates on stones at two river sites. 2. We found only one significant species–area relationship out of six relationship tested, and two significant individuals–area relationships. Even these significant relationships were weak, however. By contrast, we detected significant and rather strong relationships between species richness and the number of individuals at both river sites on all three sampling dates. We also found significant relationships of both species richness and the number of individuals with bryophyte biomass at both river sites on all sampling occasions. One of the river sites was disturbed by a bulldozer, and the species–bryophyte biomass relationships were somewhat stronger after the disturbance event. 3. Our findings are quite surprising, given that there were very weak species–area relationships on stream stones. By contrast, our results suggest a pivotal role for bryophyte biomass in determining the species richness and the number of individuals of stream macroinvertebrates at this small scale. The most probably origin of these relationships begins with bryophyte cover, which determines the number of individuals, and subsequently passively affects species richness. Thus, there is not necessarily a direct mechanism that determines the variability of species richness on stream stones. 4. Experimental studies are needed to disentangle the various mechanisms (e.g. passive sampling, provision of more food, more niche space, flood disturbance refugia) by which bryophyte biomass affects stream macroinvertebrates.     

Insect–fern interactions: macrolepidopteran utilization and species–area association

Abstract.

• 1 The generalization that ferns are under-utilized by phytophagous insects in comparison to angiosperms may be invalid because of biases involving plant growth form, plant range, and unequal sampling efforts.
• 2 Comparison of nineteen fern species with 652 herb species, the angjosperm growth form most similar to the ferns, indicates no significant difference in the mean number of supported macrolepidopteran species. When the herbs are subdivided into annuals, biennials and perennials, only the annual herbs are significantly different than the ferns.
• 3 Comparisons of the occurrence distributions for ferns and the herb categories also demonstrate that only the annual herbs support more macrolepidopteran species than the ferns. The same results are obtained when random assemblages of herbs are created that are the same size as the fern assemblage.
• 4 Both the occurrence distributions and the species–area relationship for the ferns indicate that host records for insects feeding on ferns may be grossly incomplete.
• 5 The similarity of exploitation of ferns and perennial herbs by the Macro-lepidoptera suggests that other foliage feeding insects may also use ferns at levels equivalent to angiosperms.

     

Diversity of ectomycorrhizal fungi in Britain: a test of the species–area relationship, and the role of host specificity

The host range of ectomycorrhizal (ECM) fungi in Britain was examined by compilation of a data matrix from published literature sources, based primarily on accounts of sporocarp associations with particular host genera. Information was gathered for 577 species of ECM fungi belonging to 51 genera, and 25 genera of host trees, representing the majority of ECM fungal species and host genera recorded in Britain.
Pronounced variation was recorded in the number of ECM fungal species associated with different host genera, with over 200 species recorded with Betula , Fagus , Pinus and Quercus . There was a positive linear relationship ( r ²=0·47, P =0·007) between the number of species of ECM fungi associated with different host genera and the total area occupied by each tree genus in Britain (both values log-transformed). There was also variation in the number of species of ECM fungi which were apparently specific to particular host genera, values ranging from zero (in 15 genera) to >40 in the case of Betula and Fagus . In total, 233 fungal species appeared to be specific to a single host genus (i.e. 40% of those surveyed). Comparison of the ECM mycota associated with different host genera by PCA accounted for 17% of the total variation, with genera belonging to the Fagaceae ( Quercus , Fagus and Castanea ) tending to cluster together, indicating a degree of overlap in their ECM associates. Exotic conifer species, which displayed a lower ECM diversity than would be expected from their distributional areas, were characterized by a high degree of overlap with the ECM associates of Pinus and Betula .
These results indicate that the abundance of different genera of host trees and variation in host specificity could provide a basis for understanding patterns of diversity in ECM fungi within Britain.     

A comparison of the species–time relationship across ecosystems and taxonomic groups

The species–time relationship (STR) describes how the species richness of a community increases with the time span over which the community is observed. This pattern has numerous implications for both theory and conservation in much the same way as the species–area relationship (SAR). However, the STR has received much less attention and to date only a handful of papers have been published on the pattern. Here we gather together 984 community time-series, representing 15 study areas and nine taxonomic groups, and evaluate their STRs in order to assess the generality of the STR, its consistency across ecosystems and taxonomic groups, its functional form, and its relationship to local species richness. In general, STRs were surprisingly similar across major taxonomic groups and ecosystem types. STRs tended to be well fit by both power and logarithmic functions, and power function exponents typically ranged between 0.2 and 0.4. Communities with high richness tended to have lower STR exponents, suggesting that factors increasing richness may simultaneously decrease turnover in ecological systems. Our results suggest that the STR is as fundamental an ecological pattern as the SAR, and raise questions about the general processes underlying this pattern. They also highlight the dynamic nature of most species assemblages, and the need to incorporate time scale in both basic and applied research on species richness patterns.     

The importance of samples and isolates for species–area relationships

Species–area relationships (SARs) are a key tool for understanding patterns of species diversity. A framework for the interpretation of SARs and their prediction under different landscape configurations remains elusive, however. This article addresses one of these configurations: how species' minimum-area requirements affect the shape of island or other isolate Species–area curves. We distinguish between two classes of SARs: sample-area curves, compiled entirely within larger contiguous areas, and isolate curves, compiled between isolated areas. We develop this conceptual and graphic model in order to illuminate landscape-scale diversity patterns, to discuss how various landscape and species characteristics affect outcomes, and to investigate the dynamics of local extinction under conditions of habitat fragmentation. Minimum-area effects on actual islands and other isolates predictably cause Species–area curves either to be sigmoid in arithmetic space or to be lowered for smaller areas. In order to illustrate the inherent shape of isolate curves, this study fits convex and sigmoid regression models to empirical isolate (island) data sets that cover the small scales expected to include inflection points.     

Species–area relationship of Neotropical waterbird assemblages in remnant wetlands: looking at the mechanisms

Aim We investigated the relative role of area, isolation, microhabitat diversity and number of individuals as explanatory factors defining the richness of waterbirds in wetland remnants. Location Freshwater marshes along the Atlantic coastal zone of South Brazil. (30°56′–30°22′S; 50°58–50°22′W; Fig. 1 ).

Figure 1 Open in figure viewer PowerPoint The study area (dashed line), in the Atlantic coastal zone of Brazil, is characterized by a high concentration of remnant wetlands used by resident and migratory waterbirds. Waterbirds were surveyed monthly along 2003 in 42 randomly selected wetland remnants.     

Patterns in the species–environment relationship depend on both scale and choice of response variables

Multi-scale investigations of species–environment relationships are an important tool in ecological research. The scale at which independent and dependent variables are measured, and how they are coded for analysis, can strongly influence the relationships that are discovered. However, little is known about how the coding of the dependent variable set influences community-level analyses. In this study, we used canonical correspondence analysis to quantify species–environment relationships between environmental factors collected at three spatial scales and the structure of a forest bird community in the Oregon coast range. The main question in our analysis was how coding the bird data as abundance versus presence/absence affected the nature and strength of observed relationships. As we expected, the structure of the bird community was better described overall using abundance data than it was using presence/absence data. However, individual species and life-history groups appeared to exhibit different species–environment relationships in abundance versus presence/absence data. In particular, common species with a high frequency of occurrence among sample points exhibited a stronger 'abundance' signature, whereas uncommon species with a low frequency of occurrence exhibited a stronger 'presence/absence' signature. In addition, the apparent importance of plot-level factors in explaining the variation in the bird community was greater for abundance data, whereas patch and landscape factors were more important in the presence/absence data. Thus, conclusions about the relative importance of factors at different scales is largely contingent on the way in which the species-response data are coded for analysis. For communities as a whole, and for individual species within them, the strength and nature of species–environment relationships can differ dramatically between analyses using presence/absence versus abundance data.     

Tea and health: the underlying mechanisms

Detailed multidisciplinary research on the effect of tea and the associated tea polyphenols has led to major advances on the underlying mechanisms. In most studies, green and black tea have similar effects, four of which are reviewed in this paper. 1) Tea polyphenols are powerful antioxidants that may play a role in lowering the oxidation of LDL-cholesterol, with a consequent decreased risk of heart disease, and also diminish the formation of oxidized metabolites of DNA, with an associated lower risk of specific types of cancer. 2) Tea and tea polyphenols selectively induce Phase I and Phase II metabolic enzymes that increase the formation and excretion of detoxified metabolites of carcinogens. 3) Tea lowers the rate of cell replication and thus the growth and development of neoplasms. 4) Tea modifies the intestinal microflora, reducing undesirable bacteria and increasing beneficial bacteria. The accumulated knowledge suggests that regular tea intake by humans might provide an approach to decrease the incidence of and mortality from major chronic diseases.     

Sepsis: molecular mechanisms underlying lipopolysaccharide recognition

Sepsis is an often-fatal response of the immune system against microbial pathogens. The molecular mechanisms that have been designed to protect the host from invading pathogens are responsible for the damage and injury. It is now widely known that this crucial response of the immune system is mediated by innate immunity, which employs a plethora of pattern recognition receptors that recognise motifs expressed by pathogens. A lack of knowledge of the mediators involved in innate recognition has led to unsuccessful attempts at designing effective therapeutic interventions for sepsis. However, in recent years, great leaps forward have been achieved in our knowledge of these mediators. In this review we attempt to unravel the molecular mechanisms underlying bacterial recognition, particularly recognition of bacterial lipopolysaccharide, and we propose future potential therapeutic targets for septic shock.