Challenges, Advances and Perspectives in Island Biogeography Paulo A.V

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opinions, perspectives & reviews frontiers of biogeography 8.2, e29136, 2016 perspective Challenges, advances and perspectives in island biogeography Paulo A.V. Borges1, Pedro Cardoso1,2, Rosalina Gabriel1, Claudine Ah-Peng3 and Brent C. Emerson4 1CE3C – Centre for Ecology, Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores – Departamento de Ciências e Engenharia do Ambiente, 9700-042 Angra do Heroísmo, Açores, Portugal; [email protected]; [email protected]; 2Finnish Museum of Natural History, University of Helsinki, 00014 Helsinki, Finland. pe- [email protected]; 3Université de La Réunion, UMR PVBMT, Pôle de Protection des Plantes, 97410 Saint-Pierre, Ile de La Réunion, France. [email protected]; 4Is- land Ecology and Evolution Research Group, Instituto de Productos Naturales y Agrobiología, 38206 La Laguna, Tenerife, Canary Islands, Spain. [email protected]

Abstract. Island biogeographical research is becoming more and more fashionable, with the continuous identification of new challenges that are critical for the advancement of science. In this contribution we identify biases and limitations associated with island biogeographical studies, and also describe recent advances and propose new perspectives. The main proposals include: 1) downscaling island biogeographical studies to local/plot scale; 2) investigating geographical patterns of intra-specific genetic variation to infer dispersal processes among and within islands; 3) using applied biogeographical research to respond to the current island biodiversity crisis; and 4) applying new computer-intensive methods such as artificial intelligence (AI) approaches. Keywords. Agent-based Models (ABM), dispersal, island biogeography, plot-scale surveys, sample bias

Introduction using any diversity metric, even at the island scale After MacArthur and Wilson’s (1963) paper and (Gray and Cavers 2014), for example because un- their book on “The Theory of Island Biogeogra- recorded anthropogenic extinctions may mask phy” (MacArthur and Wilson 1967), the study of current patterns (Cardoso et al. 2010, Faurby and islands received a boost, and they were used as Svenning 2015), there are many recent advances model systems for many purposes, in particular in island biogeography that Fernández-Palacios et for investigating drivers of species richness and al. (2015: 14) described as “a new golden era in composition. A search of the Web of Science data- island biogeography”. base using “island biogeography” as a topic for the The most recent and important theoretical period 1967–2015, generated about 9000 publica- advance in island biogeography has been the tions that include a diversity of sub-topics and tax- ‘General Dynamic Model of Oceanic Island Bioge- onomic units, which largely surpass the island ography’ (GDM) (Whittaker et al. 2008), high- scale and include the application of the original lighting the relevance of island ontogeny for pro- concepts of MacArthur and Wilson’s (1963, 1967) cesses of species diversification in remote volcanic works to isolated continental systems, primarily archipelagos. This proposal has inspired many in- ‘habitat islands’. novative empirical and theoretical studies across a Traditional island biogeographical studies range of archipelagos (reviewed in Borregaard et applied to oceanic islands are based on whole- al. 2016). Another useful concept is that of archi- island diversity indicators collated over decades, pelagos as replicates, which allow the investiga- using the islands of a particular archipelago as tion of drivers of diversity in many taxa, at large replicates. Although one has to be careful when scales (Triantis et al. 2015). Also, a better under-

frontiers of biogeography, ISSN 1948-6596 — © 2016 the authors; journal compilation © 2016 The International Biogeography Society 1 front. Biogeogr. 8.2, e29136, 2016 P.A.V. Borges et al. — perspectives in island biogeography standing of the palaeo-dynamics of remote ocean- Biases and limitations associated with island ic archipelagos is particularly relevant for classical biogeographical studies biogeographical and evolutionary studies, as Biases shown recently by Fernández-Palacios et al. (2010, Biases associated with sampling effort are im- 2016) and Rijsdijk et al. (2014). Methodologically, portant in any ecological or biogeographical study. the use of Bayesian approaches is becoming in- We undertook a search of the Azores Bioportal1 to creasingly important in island biogeography, since investigate the impact of the knowledge of species it allows the development of dynamic time- diversity in the nine Azorean islands on species– constrained models that use results of prior anal- area relationship (SAR) slope on a temporal scale. yses in subsequent modelling (see Gray and Cav- For this, we computed a SAR curve of each decade ers 2014). Considering the relative contribution of for the nine islands using the power function S = ecology (colonization, extinction) and evolution CAz linearized in the double logarithmic form logS (speciation), these approaches also give flexibility = logC + zlogA. For Lepidoptera and Coleoptera, in investigating how the geographical characteris- the slope value was stable in the last eight dec- tics of island archipelagos and their taxa influence ades (Fig. 1), which reflects the fact that a large diversity patterns (Patiño et al. 2015, Triantis et al. proportion of the entomological surveys and taxo- 2015). nomic work in the Azores in the first decades of In this contribution, we first look at biases the 20th century was concentrated in those two and limitations associated with island biogeo- taxonomic groups (see a literature review in Bor- graphical studies, and then describe recent ad- ges and Vieira 1994). However, only recently does vances and propose new perspectives: 1) applying the sampling effort across the nine islands seem to island biogeographical models to local/plot scale; be good enough to generate stable SAR slopes for 2) investigating geographical patterns of intra- Bryophytes, Hemiptera and Araneae. This means specific genetic variation to infer dispersal pro- that the sampling effort across multiple islands of cesses among and within islands; 3) using the an archipelago should be controlled for, when per- emergence of applied biogeographical research to forming complex statistical analyses. Changes in respond to the current island biodiversity crisis; the slope may also be due to changes in habitat and 4) implementing new computer-intensive area and/or paying the extinction debt (Cardoso et methods such as artificial intelligence (AI). al. 2010, Triantis et al. 2010).

Figure 1. Temporal variation of the SAR slopes for a log–log model relating the nine Azorean island areas with species richness for their mosses, liverworts and hornworts (Bryophyta), spiders (Araneae), true bugs (Hemiptera), beetles (Coleoptera) and moths and butterflies (Lepidoptera).

1 http://www.atlantis.angra.uac.pt/, last accessed 30th June 2016

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Limitations al. 2013), and Guadeloupe (Azevedo et al. un- We can divide limitations related to island biogeo- published) and we call for more widespread use of graphical studies into two types: i) those intrinsic this type of small-scale physical climate model. to island systems, and ii) those that may also ap- Alternatively, for small islands authors can: (a) use ply to continental biogeographical studies. the local-scale dynamical climate model MUKLI- MO_3 parameterized with data from local mete- Limitations intrinsic to islands orological stations (Mifka and Aloise 2014); (b) run The first main limitation is the Linnaean shortfall: local climate models using approaches like multi- the faunas and floras of many islands and small ple regressions with residual kriging and universal archipelagos are not well known. Moreover, as kriging, based on weather stations in combination shown in Fig. 1, even for well surveyed archipela- with predictors from GCMs. gos, bias can arise owing to uneven sampling effort between islands (see also Gray and Cavers Limitations not exclusive to islands 2014), and endemic species inventories are still The number of resident researchers in islands is largely incomplete (see Lobo and Borges 2010). rather small and their universities usually rather The fact that few islands are available to recent in origin (less than 50 years), which leads to apply robust statistical models that involve multi- inconsistencies and asymmetries in the knowledge ple regression and variable selection is a serious of the distributions of different taxonomic groups limitation. As an alternative, the use of mixed- among islands and archipelagos. This taxonomic effects models was recently proposed (Bunnefeld shortfall is not exclusive to islands (see e.g. Cardo- and Phillimore 2012), as they incorporate in the so et al. 2011, Meyer et al. 2015), but is particular- same analysis islands from multiple archipelagos ly important, as revealed by the few large-scale and/or taxa, while controlling for data structure multi-archipelago biogeographical studies which and idiosyncrasies derived from fixed factors not are restricted to either land plants (e.g. Patiño et under study (e.g. archipelagos and taxa for study- al. 2014, Weigelt et al. 2015) or birds (e.g. Kalmar ing SAR or the GDM). These have been successful- and Currie 2006). ly applied in recent studies, for example for bryo- Long-term biodiversity data are either rare phytes (Patiño et al. 2013) and land-snails or almost absent for islands, which hampers the (Cameron et al. 2013). study of the biogeography of extinctions (but see Another important limitation associated Triantis et al. 2010) and temporal dynamics of is- with biogeographical studies on islands is related land biota. Satellite cover is also comparably poor to the availability of present and future climate in islands – in terms of both quality of image be- data. Islands are often small, while global climate cause of high percentages of cloud cover (see e.g. models are necessarily made at relatively coarse Gil et al. 2013), and the lower frequency of satel- resolutions (1x1 km or larger). In addition, the lite visits compared to continental areas. This specificities of oceanic island topography and con- clearly limits the acquisition of data for island eco- sequent climate can hardly be reflected using systems. The limited availability of data on land global or large-scale circulation models. To over- uses, vegetation types, and geological and edaphic come such a shortfall a simple layer model was features is not exclusive to islands but is frequent- proposed by Azevedo et al. (1998), based on the ly a problem for many island systems. For in- transformations experienced by an air mass cross- stance, CORINE or the IUCN habitat categories are ing over a mountain, simulating the evolution of mostly useless in the Azores, Madeira or Canary an air parcel's physical properties starting from Islands. They are good only for large scales. the sea level. This model has been applied suc- Given these biases and limitations, island cessfully within Macaronesian islands at very small biogeographical studies are challenging. Here we scales, namely in Azores (see e.g. Borges et al. propose four further avenues to develop studies 2006, Hortal et al. 2010), and Madeira (Boieiro et of biogeography on islands.

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Toward local scale biogeography: recent ex- La Palma in Canary Islands; Réunion in the Masca- amples mostly from Macaronesia renes; Tahiti in French Polynesia; and Guadeloupe Downscaling regional island biogeographical stud- in the Caribbean) to understand bryophytes’ and ies to the local scale facilitates the generation of ferns’ ecological and biogeographical processes hypotheses using diversity metrics that are based across elevational transects and islands. on intensive fieldwork using standardized sam- A project recently approved by the Portu- pling strategies in different sites within different guese Foundation for Science and Technology, 5 islands and within different archipelagos. Studies MACDIV , aims to characterize cross-scale varia- using plot-scale surveys for testing island biogeo- tion of taxonomic, functional and phylogenetic graphical models are generally lacking (but see diversities (alpha and beta), from plot to archipel- Borges and Brown 1999, Gruner 2007, Karger et ago scales, sampling spiders from 10 islands in the al. 2014). However, some ongoing projects in Azores, Madeira, Canary Islands and Cape Verde. 6 Macaronesia and other archipelagos address this In Hawaii, the project Dimensions in Biodiversity limitation with plot-level data to understand is- was initiated in 2014, aiming to understand pro- land ecological processes across archipelagos, cesses at the interface between ecology and evo- which may also shed light on island biogeograph- lution in four islands, by studying small plots in ical patterns and processes. The first study, which Metrosideros mesic and wet forest (see Gillespie started in 1999, is the BALA project (Biodiversity 2016). of Arthropods from the Laurisilva of Azores). This The results obtained with studying regional has yielded a wealth of publications for the Azores –local processes allow the implementation of ad- (see Borges et al. 2005, Ribeiro et al. 2005 and vanced statistical methods to reveal mechanisms Borges et al. 2011 for a review; also see the BALA driving the distribution of species and observed project website2). The BALA project generated diversity patterns. With these kinds of plot-based standardized plot data for 100 sites across seven studies, replicated in many islands and archipela- islands of the Azores for epigean and canopy ar- gos, we expect to identify regional spatial, histori- thropods, and these are still being exploited (see cal and environmental factors that may influence e.g. Rigal et al. 2013, Cardoso et al. 2014, local diversity (taxonomic, functional and phyloge- Matthews et al. 2014). netic) patterns and processes in islands. Results of Two recent projects, implemented within the projects BALA, ISLANDBIODIV, MOVECLIM, the 2011 European FP7 NetBiome call, investigate Dimensions in Biodiversity and MACDIV will also diversity and biogeographical patterns in islands contribute to understanding long-term ecological across archipelagos: ISLANDBIODIV3 and processes, since permanent plots can be MOVECLIM4 (see also Gabriel et al. 2014 and Coe- resampled over time. lho et al. 2016). In the case of ISLANDBIODIV, the intensive sampling and surveying of 30 plots (ten Dispersal within and among islands in each island) for vascular plants, springtails, spi- Island biogeographical theory, when reduced to ders and beetles in Terceira Island (Azores), Tene- its fundamental components, leaves us with three rife (Canary Islands) and La Réunion (Mascarenes) key biological processes: colonization, extinction allows, for the first time, tests of the emergent and speciation. Colonization and speciation con- properties of island species’ community structures tribute to the accumulation of species on islands, across archipelagos. In the case of MOVECLIM, an while extinction has the opposite effect. Classic elevation-stratified protocol (Ah-Peng et al. 2012) island theory describes a hypothesized theoretical was applied within several islands (Pico in Azores; relationship between colonization and extinction

2 http://islandlab.uac.pt/projectos/ver.php?id=65, last accessed 30th June 2016 3 http://island-biodiv.org/, last accessed 30th June 2016 4 http://moveclim.blogspot.com/, last accessed 30th June 2016 5 http://ce3c.ciencias.ulisboa.pt/research/projects/ver.php?id=61, last accessed 30th June 2016 6 http://nature.berkeley.edu/hawaiidimensions/, last accessed 30th June 2016

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(MacArthur and Wilson 1963, 1967), and empirical of beetle communities have revealed that varia- data reveal that speciation may also be embedded tion in community composition is strongly ex- within this model (Emerson and Kolm 2005). Colo- plained by individual species’ dispersal limitation nization history among islands over long evolu- (Baselga et al. 2013). It will be interesting to see tionary timescales is recorded within the phyloge- whether this extends to speciation on islands, netic relationships of species, although it must be where one might expect selective pressures to taken into account that extinction removes spe- hold more explanatory power. The kind of com- cies and thus it also removes colonization history, munity-level ecological sampling protocols de- which is likely to be more problematic for deeper scribed in the previous section provide an exploit- phylogenies (Emerson 2002). Many studies have able framework for the application of intra- sought to use phylogeny to extrapolate coloniza- specific genetic sampling to test the hypotheses tion history among islands, and Bayesian methods presented here. have been developed to summarize these at the While phylogenetic sampling can tell us community level (Sanmartín et al. 2008). In con- which species or lineages originate from coloniza- trast to phylogenetic sampling, there has been tion events between islands, such studies typically less emphasis on population-level sampling within say little about what might have driven subse- species or species complexes to investigate dis- quent speciation within islands. In contrast, popu- persal over more recent timescales, both among lation-level molecular sampling within species and within islands. If one starts with a simple null complexes distributed across multiple islands hypothesis that most speciation within an island is offers the potential to explore both dispersal and of allopatric origin, then a sampling framework speciation, and any potential interactions be- can be implemented to ask “do species sampled tween these two processes (Emerson and Faria from taxa with a history of in situ speciation show 2014). The work of Jordal et al. (2006) provides a higher genetic structuring than species sampled clear demonstration of one such interaction. A from non-diversified lineages?” Because geo- double colonization of the Canary Island of La Pal- graphically referenced intraspecific genetic data ma from El Hierro by the beetle species Aphanar- can be used to estimate gene flow and genetic thrum glabrum was followed by limited admixture connectivity among individuals, this question may between the two founding populations, presuma- be rephrased as “does dispersal limitation pro- bly with negative fitness consequences, facilitating mote speciation within islands?” character displacement and the completion of A second null hypothesis that can be tested reproductive isolation. Recent work by Hendrickx within this framework is that dispersal promotes et al. (2015) implicates ongoing dispersal of flight- speciation via colonization, by asking the question ed species among islands in the repeated evolu- “do species sampled from taxa with a history of tion of flightless ecotypes of Calasoma beetles in speciation via colonization show less genetic the Galapagos islands. Molecular sampling within structure than species sampled from taxa where a closely related complex of nine species within in situ speciation has been more important?” For the weevil genus Laparocerus in the Canary Is- the same reason provided above, this question lands indicates species’ origins from multiple may be rephrased as “does dispersal promote founding events of different species followed by speciation between islands?” These two null hy- genetic admixture (Faria et al. 2016). All three potheses provide a framework to test the extent studies demonstrate a speciation dynamic with a to which the distribution of biodiversity within less-than-simple dispersal history that would not and among islands fits a neutral model where the be so easily discernable among more distantly dynamics of colonization and speciation are medi- related species. ated by individual species’ dispersal limitations. Sampling closely related species complexes There are parallels here to recent continental reduces the impact of both (i) species extinctions studies where the sampling and DNA sequencing and (ii) the turnover of genetic variation within

frontiers of biogeography, ISSN 1948-6596 — © 2016 the authors; journal compilation © 2016 The International Biogeography Society 5 front. Biogeogr. 8.2, e29136, 2016 P.A.V. Borges et al. — perspectives in island biogeography species through time that eventually erases signa- A fundamental question in island biogeogra- tures of divergence and gene flow in the specia- phy and ecological studies responding directly to tion process. Detailed molecular analyses, com- the current island biodiversity crisis could be: bined with geographically representative sampling “how will human activities (agriculture, forestry, within closely related species complexes on is- fisheries and touristic activities) plus climate lands, would appear to be a promising line of in- change interact with invasive species and affect vestigation for a fine-scale understanding of role the distributions of endemic species, native habi- of dispersal in the speciation process. The increas- tats and ecosystem services?”. Policy-based con- ing accessibility and rigour of restriction site- servation biogeography should include the human associated DNA sequencing for genotyping-by- socio-economic dimension for a more complete sequencing (GBS) (e.g. Mastretta-Yanes et al. understand of how the drivers of taxonomic 2015) should facilitate this. By yielding potentially (species), functional (ecosystems) and phyloge- thousands of loci for analysis, GBS can provide netic (evolutionary) diversity at all spatial and greater statistical power for the discrimination of temporal scales interact with socio-economic dispersal and admixture, while also relaxing the needs. By performing applied biogeographical re- need for large sample sizes that are typically asso- search, biogeographers may achieve a more ciated with population genetic analyses. This may meaningful integrative research programme. We be particularly attractive for island-based studies, suggest that more research effort should be di- where sample sizes are often limited by species rected toward: (i) the spatial and temporal dy- being rare or difficult to collect. Recent advances namics of human socio-economic needs and land using hybrid capture techniques (Suchan et al. use on islands; (ii) the spatial distribution of eco- 2016) also open the door for the use of museum system services relevant for human populations; or collection material, potentially allowing re- (iii) the impacts of local-scale processes, both so- searchers to investigate temporal trends in disper- cial and ecological, on large-scale island ecosys- sal history, and other population genetic phenom- tem dynamics; (iv) the role and importance of cur- ena of interest in island settings, such as the popu- rent protected areas for the spatial distribution lation genetic consequences of disturbance and population dynamics of native (and in particu- effects. lar endemic), exotic and invasive species; and (v) the impacts of invasive species and climate Conservation biogeography on islands change on the distribution of already restricted Island native habitats have great conservation and island endemic species. heritage value, but are facing rapidly increasing human pressure and the negative effects of global New methods for island biogeography change (invasive species, land-use changes and Although islands are in many ways simpler model climatic changes). The recent Declaration of Gua- settings for biogeography and conservation stud- deloupe (IUCN – International Conference on Bio- ies, they are still complex systems. Therefore, diversity and Climate Change, 21–25 October commonly used statistical modelling techniques 2014 at Guadeloupe) defined actions to counter are often unable to reflect patterns and processes biodiversity loss and climate change impacts in EU at multiple spatial and temporal scales. Incorpo- Outermost Regions and Overseas Countries and rating the temporal component, which adds an Territories (ORs and OCTs). This identified climate extra layer of complexity, has recently led to great change and invasive species as two of the most advances through the use of phylogenetic meth- important threats to Islands. Thus, it is also re- ods (see above), the development of the General sponsibility of biogeographers to adopt conserva- Dynamic Model (Whittaker et al. 2008) and the tion biogeography (Whittaker et al. 2005, Richard- development of methods that are capable of mod- son and Whittaker 2010) as a priority in their re- elling directional spatio-temporal processes deter- search agendas. mined by island emergence (Carvalho et al. 2015).

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However, this is just the beginning. field, symbolic regression (SR; Koza 1992), which Ecological systems have been studied using searches for both the formal structure of func- two complementary modelling approaches. The tions and the fitting of parameters simultaneously, classical top-down approach primarily studies was recently proposed as a possible way to evolve emergent patterns through correlations of varying free-form equations purely from data, often with- complexity. Mechanistic bottom-up models (e.g. out prior human inference or hypotheses agent-based mModels, ABMs, also known in biolo- (Cardoso et al. 2015). Nature is usually not linear gy as individual-based models, IBMs) directly sim- and yet, except when some theoretical models are ulate processes, providing biological explanations available (e.g. island species–area relationships of how components (biotic or abiotic) work caus- [ISARs] and GDM), we are still mostly using linear ally together to produce a given pattern. In ABMs, models (GLMs and related techniques). Compared the objects of study are the individuals them- with linear approaches, symbolic regressions (SR) selves. Intrinsic to each individual are a number of are fully flexible in the shape of the relationships characteristics modelled by different rules or between predictor and dependent variables, al- equations. A given explanatory variable, either lowing a much better fit of data. SR also has sever- intrinsic (e.g. energy accumulated) or extrinsic al advantages over other, commonly used, highly (e.g. temperature), is used to model the depend- flexible regression (e.g. GAMs) or machine- ent variable (e.g. movement propensity), not only learning (e.g. neural networks) techniques. Most to make predictions but also to find direct causali- importantly, the evolved equations are human- ty between variables. From scales as small as a readable and interpretable. Interpretability allows petri dish to the entire globe, ABMs are now ex- new ideas to formulate general models and theo- tensively used to find mechanistic relations be- retical principles. SR was used with success, tween individuals and the environment, including among other applications, to find new models for within island biogeographical studies (e.g. Rosin- the ISARs and the GDM (Cardoso et al. 2015, Vujić dell and Phillimore 2011), being an ideal way to et al. 2016). directly study colonization, speciation and extinc- The application of ABM, SR and other inno- tion processes. Making them spatially explicit fur- vative solutions should be explored for their po- ther enhances their power. Several multi-agent tential to reveal patterns of diversity across multi- programmable modelling environment platforms ple taxa and regions and the processes that may are available, of which NetLogo7 is probably the explain these. Ideally the data used should be the most used, but there are many other possibilities result of standardized sampling to generate local (Nikolai and Madey 2008). diversity metrics (alpha diversity) to understand Models, either classical or mechanistic, are (a) replacement and loss or gain of species in usually found and parametrized based on theo- space and time (i.e. true turnover and richness retical reasoning. Finding hidden relationships, differences in beta diversity; Carvalho et al. 2012), models and even principles in a collaborative hu- (b) how these influence large-scale patterns in man–machine effort is now possible through the regional pools (gamma diversity), and (c) how to use of massive computational power (Schmidt and make best use of increasingly available high- Lipson 2009, Cardoso et al. 2015). A particularly quality remote sensing, genetic and functional interesting approach to island biogeography is the data. use of artificial intelligence (AI) methods that are able to cope with a range of data form and size, to Conclusions find both classical and mechanistic models. AI in- Integrative biogeographical studies on islands are cludes the field of evolutionary computation, a lacking. Limitations are sometimes severe and in- large set of methods of which the better studied novative approaches are needed. Here we have are genetic algorithms (Holland 1975). Within this identified the need to downscale island biogeog-

7 https://ccl.northwestern.edu/netlogo/, last accessed 30th June 2016

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raphy to local scale, creating opportunities for sampling of soil epigean arthropods. Biodiversity and long-term ecological and biogeographical re- Conservation, 14, 2029–2060. Borges, P.A.V., Cardoso, P., Guerreiro, O., Rigal, F., Florencio, search. There is a need for population-level sam- M., Amorim, I.R., Borda-de-Água, L., Cascalho, J. & pling of species or species complexes distributed Ferreira, M. (2013) Perspectives and progress of ecol- across multiple islands to investigate dispersal ogy and conservation science in the Azores: the possible contribution of Artificial Intelligence. In: Correia, over recent timescales, both among and within L., Reis, L.P., Cascalho, J., Gomes, L., Guerra, H. & islands. The integration of agent-based models Cardoso, P. (Eds.) Advances in artificial intelligence and symbolic regression techniques will help bio- local proceedings, EPIA2013 CMATI, pp. 41–44. Uni- versidade dos Açores, Portugal. geographers to explore local- to large-scale eco- Borges, P.A.V., Gaspar, C.S., Santos, A.M.C, Ribeiro, S.P., Car- logical patterns and processes within and across doso, P., Triantis, K. & Amorim, I.R. (2011) Patterns of islands and archipelagos, eventually leading to colonization and species distribution for Azorean arthropods: evolution, diversity, rarity and extinction. better conservation and policy decisions. Açoreana, Supl. 7, 93–123. Borges, P.A.V., Lobo, J.M., Azevedo, E.B., Gaspar, C., Melo, C. & Nunes, L.V. (2006) Invasibility and species richness Acknowledgments of island endemic arthropods: a general model of This work was mainly supported by the research endemic vs. exotic species. Journal of Biogeography, project MOVECLIM (M2.1.2/F/04/2011/NET), IS- 33, 169–187. Borregaard, M.K., Amorim, I.R., Borges, P.A.V. et al. 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