Kostas A. Triantis

Bio: Kostas A. Triantis is an academic researcher from National and Kapodistrian University of Athens. The author has contributed to research in topics: Species richness & Insular biogeography. The author has an hindex of 36, co-authored 79 publications receiving 4397 citations. Previous affiliations of Kostas A. Triantis include University of the Azores & University of Oxford.

ORIGINAL ARTICLE: A general dynamic theory of oceanic island biogeography

Abstract: Aim MacArthur and Wilson’s dynamic equilibrium model of island biogeography provides a powerful framework for understanding the ecological processes acting on insular populations. However, their model is known to be less successful when applied to systems and processes operating on evolutionary and geological timescales. Here, we present a general dynamic model (GDM) of oceanic island biogeography that aims to provide a general explanation of biodiversity patterns through describing the relationships between fundamental biogeographical processes – speciation, immigration, extinction – through time and in relation to island ontogeny. Location Analyses are presented for the Azores, Canaries, Galapagos, Marquesas and Hawaii. Methods We develop a theoretical argument from first principles using a series of graphical models to convey key properties and mechanisms involved in the GDM. Based on the premises (1) that emergent properties of island biotas are a function of rates of immigration, speciation and extinction, (2) that evolutionary dynamics predominate in large, remote islands, and (3) that oceanic islands are relatively short-lived landmasses showing a characteristic humped trend in carrying capacity (via island area, topographic variation, etc.) over their life span, we derive a series of predictions concerning biotic properties of oceanic islands. We test a subset of these predictions using regression analyses based largely on data sets for native species and single-island endemics (SIEs) for particular taxa from each archipelago, and using maximum island age estimates from the literature. The empirical analyses test the power of a simple model of diversity derived from the GDM: the log(Area) + Time + Time2 model (ATT2), relative to other simpler time and area models, using several diversity metrics. Results The ATT2 model provides a more satisfactory explanation than the alternative models evaluated (for example the standard diversity–area models) in that it fits a higher proportion of the data sets tested, although it is not always the most parsimonious solution. Main conclusions The theoretical model developed herein is based on the key dynamic biological processes (migration, speciation, extinction) combined with a simple but general representation of the life cycle of oceanic islands, providing a framework for explaining patterns of biodiversity, endemism and diversification on a range of oceanic archipelagos. The properties and predictions derived from the model are shown to be broadly supported (1) by the empirical analyses presented, and (2) with reference to previous phylogenetic, ecological and geological studies.

Islands as model systems in ecology and evolution: prospects fifty years after MacArthur‐Wilson

Abstract: The study of islands as model systems has played an important role in the development of evolutionary and ecological theory. The 50th anniversary of MacArthur and Wilson's (December 1963) article, ‘An equilibrium theory of insular zoogeography’, was a recent milestone for this theme. Since 1963, island systems have provided new insights into the formation of ecological communities. Here, building on such developments, we highlight prospects for research on islands to improve our understanding of the ecology and evolution of communities in general. Throughout, we emphasise how attributes of islands combine to provide unusual research opportunities, the implications of which stretch far beyond islands. Molecular tools and increasing data acquisition now permit re‐assessment of some fundamental issues that interested MacArthur and Wilson. These include the formation of ecological networks, species abundance distributions, and the contribution of evolution to community assembly. We also extend our prospects to other fields of ecology and evolution – understanding ecosystem functioning, speciation and diversification – frequently employing assets of oceanic islands in inferring the geographic area within which evolution has occurred, and potential barriers to gene flow. Although island‐based theory is continually being enriched, incorporating non‐equilibrium dynamics is identified as a major challenge for the future.

Island biogeography: Taking the long view of nature’s laboratories

Abstract: BACKGROUND Ever since Darwin, natural scientists have turned to islands for inspiration and for model systems. For the past half century, they have done so largely within the paradigm established by Robert H. MacArthur and Edward O. Wilson’s Theory of Island Biogeography , which provided a quantitative, dynamic framework, based upon assumptions of geographically predictable patterns of immigration, extinction, and speciation. Although this approach has proven productive, its application to remote archipelagos and evolutionary time scales has been hampered by a rather static view of islands themselves, despite mounting evidence of their dynamism as platforms. We review recent progress in integrating the largely ecological thinking of their theory with insights on the longer-term dynamics of both the islands and their biotas. ADVANCES Classification and analysis of marine islands by their geophysical dynamics, and of their species by how they colonized, provides a step toward a more nuanced biogeography out of which new insights are already emerging. This perspective is exemplified by the general dynamic model of oceanic island biogeography, which predicts how immigration, speciation, and extinction respond to the typical life cycle of hotspot islands, with phases of emergence, development, and submergence. The model successfully predicts such emergent patterns as the occurrence of peak diversification on youthful, expanding islands with maximum vacant niche space. Diversity patterns analyzed for large numbers of data sets have confirmed the importance of in situ evolutionary dynamics on remote archipelagos, which typically possess steep island species–area relationships, especially for endemic taxa. We may infer that variations in propagule flow among islands within archipelagos are important in modulating these emergent diversity patterns. There is, for example, good support for an “island progression rule” in which older land masses donate colonists to younger islands (consistent with the generalization of islands as “sinks”), but there is also increasing evidence of “reverse colonization,” including from islands to continental regions. Advances are also being made in linking such island biogeographical models with the classic traits and syndromes of insular species, although this first demands that previous generalizations are rigorously reexamined using expanded data sets and modern techniques of analysis. A classic insular syndrome is the loss of dispersability of formerly dispersive species following island colonization, for which there is now good evidence for several taxa, including many genera of land birds. Yet, paradoxically, and perhaps controversially, it has also been inferred that many species of plants lacking specialized dispersal adaptations can colonize quite remote islands, often by nonstandard means of transport. Unfortunately, island evolutionary syndromes, such as loss of flight in birds, frequently predispose species to heightened extinction risk when islands are colonized and transformed by humans, as we also document. OUTLOOK Developments in theory and in analytical and modeling capabilities within biological and Earth system science, and the pooling of large numbers of data sets, enhancing statistical power, collectively hold the promise of a new synthesis in island biogeography. This synthesis will need to accommodate evidence of the long-term dynamics of remote island systems, whereby some lineages persist far longer than any particular island platform, while others founder as their sole island home sinks under the waves. The promise is of a biogeography in the tradition of the MacArthur–Wilson theory, generating and testing predictive models, but extended to accommodate a more sophisticated suite of insular geological and environmental dynamics, combined with a fuller understanding of patterns and processes of gene flow within and between archipelagos.

The island species–area relationship: biology and statistics

Abstract: Aim We conducted the most extensive quantitative analysis yet undertaken of the form taken by the island species–area relationship (ISAR), among 20 models, to determine: (1) the best-fit model, (2) the best-fit model family, (3) the best-fit ISAR shape (and presence of an asymptote), (4) system properties that may explain ISAR form, and (5) parameter values and interpretation of the logarithmic implementation of the power model. Location World-wide. Methods We amassed 601 data sets from terrestrial islands and employed an information-theoretic framework to test for the best-fit ISAR model, family, and shape, and for the presence/absence of an asymptote. Two main criteria were applied: generality (the proportion of cases for which the model provided an adequate fit) and efficiency (the overall probability of a model, when adequate, being the best at explaining ISARs; evaluated using the mean overall AICc weight). Multivariate analyses were used to explore the potential of island system properties to explain trends in ISAR form, and to describe variation in the parameters of the logarithmic power model. Results Adequate fits were obtained for 465 data sets. The simpler models performed best, with the power model ranked first. Similar results were obtained at model family level. The ISAR form is most commonly convex upwards, without an asymptote. Island system traits had low descriptive power in relation to variation in ISAR form. However, the z and c parameters of the logarithmic power model show significant pattern in relation to island system type and taxon. Main conclusions Over most scales of space, ISARs are best represented by the power model and other simple models. More complex, sigmoid models may be applicable when the spatial range exceeds three orders of magnitude. With respect to the log power model, z-values are indicative of the process(es) establishing species richness and composition patterns, while c-values are indicative of the realized carrying capacity of the system per unit area. Variation in ISAR form is biologically meaningful, but the signal is noisy, as multiple processes constrain the ecological space available within island systems and the relative importance of these processes varies with the spatial scale of the system.

A model for the species–area–habitat relationship

Abstract: Aim To propose a model (the choros model) for species diversity, which embodies number of species, area and habitat diversity and mathematically unifies area per se and habitat hypotheses. Location Species richness patterns from a broad scale of insular biotas, both from island and mainland ecosystems are analysed. Methods Twenty-two different data sets from seventeen studies were examined in this work. The r2 values and the Akaike's Information Criterion (AIC) were used in order to compare the quality of fit of the choros model with the Arrhenius species–area model. The classic method of log-log transformation was applied. Results In twenty of the twenty-two cases studied, the proposed model gave a better fit than the classic species–area model. The values of z parameter derived from choros model are generally lower than those derived from the classic species–area equation. Main conclusions The choros model can express the effects of area and habitat diversity on species richness, unifying area per se and the habitat hypothesis, which as many authors have noticed are not mutually exclusive but mutually supplementary. The use of habitat diversity depends on the specific determination of the ‘habitat’ term, which has to be defined based on the natural history of the taxon studied. Although the values of the z parameter are reduced, they maintain their biological significance as described by many authors in the last decades. The proposed model can also be considered as a stepping-stone in our understanding of the small island effect.

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.