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

The Theory of Island Biogeography

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

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Experimental Design and Data Analysis for Biologists

Statistics for Spatial Data.

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Modern Applied Statistics With S

Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use.” Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty.

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Species Distribution Models: Ecological Explanation and Prediction Across Space and Time

1. Given the prevalence of missing data on species′ traits − Raunkiaeran shorfall − and its importance for theoretical and empirical investigations, several methods have been proposed to fill sparse databases. Despite its advantages, imputation of missing data can introduce biases. Here, we evaluate the bias in descriptive statistics, model parameters, and phylogenetic signal estimation from imputed databases under different missing and imputing scenarios. 2. We simulated coalescent phylogenies and traits under Brownian Motion and different Ornstein Uhlenbeck evolutionary models. Missing values were created using three scenarios: missing completely at random, missing at random but phylogenetically structured and missing at random but correlated with some other variable. We considered four methods for handling missing data: delete missing values, imputation based on observed mean trait value, Phylogenetic Eigenvectors Maps and Multiple Imputation by Chained Equations. Finally, we assessed estimation errors of descriptive statistics (mean, variance), regression coefficient, Moran′s correlogram and Blomberg′s K of imputed traits. 3. We found that percentage of missing data, missing mechanisms, Ornstein Uhlenbeck strength and handling methods were important to define estimation errors. When data were missing completely at random, descriptive statistics were well estimated but Moran′s correlogram and Blomberg′s K were not well estimated, depending on handling methods. We also found that handling methods performed worse when data were missing at random, but phylogenetically structured. In this case adding phylogenetic information provided better estimates. Although the error caused by imputation was correlated with estimation errors, we found that such relationship is not linear with estimation errors getting larger as the imputation error increases. 4.	Imputed trait databases could bias ecological and evolutionary analyses. We advise researchers to share their raw data along with their imputed database, flagging imputed data and providing information on the imputation process. Thus, users can and should consider the pattern of missing data and then look for the best method to overcome this problem. In addition, we suggest the development of phylogenetic methods that consider imputation uncertainty, phylogenetic autocorrelation and preserve the level of phylogenetic signal of the original data.

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Challenging the Raunkiaeran shortfall and the consequences of using imputed databases

Inequality in aquatic ecosystem services

Catchment scale deforestation increases the uniqueness of subtropical stream communities

Spatial synchrony occurs when the abundance of populations in different locations rise and fall together. This pattern is caused mainly by dispersal and spatially correlated environmental stochasticity. The levels of spatial synchrony can vary between species, yet little is known about which species traits can explain this interspecific variation. In addition, traits may have different degrees of influence on spatial synchrony levels because of their differences in plasticity. We hypothesized that conservative traits—reproductive and morphological—will best explain interspecific variation in synchrony, while those that may vary according to the environment—feeding and habitat preference—will be weakly related to this interspecific variation. We evaluated the spatial synchrony of freshwater fish species in a highly fragmented river in the Neotropical region and related the levels of synchrony to seven predictors: diet, reproductive traits (migration, fecundation, parental care and spawning), position in the water column, niche breadth, body size, body shape and average temporal occurrence of each species. The fish species showed low levels of spatial synchrony but a high interspecific variation (correlation values ranging from −0.11 to 0.41). We found that this variation was mainly related to species' reproductive traits, that is, sedentary species with partial spawning and without parental care had higher mean spatial synchrony than species with the opposite characteristics. In contrast, more plastic traits (diet and habitat preferences) were poor predictors of mean spatial synchrony. We speculate that, despite the low spatial synchrony found, if extreme impacts continue to occur in the basin at the regional scale, it may negatively affect local fish populations in a synchronous manner, resulting in increased risk of simultaneous declines. A sincronia espacial ocorre quando a abundância de populações em diferentes locais aumenta e diminui ao mesmo tempo. Esse padrão é causado principalmente pela dispersão e pela estocasticidade ambiental espacialmente correlacionada. Os níveis de sincronia espacial podem variar entre as espécies, mas pouco se sabe sobre quais atributos das espécies podem explicar essa variação interespecífica. Além disso, esses atributos podem ter diferentes graus de influência nos níveis de sincronia espacial devido às diferenças no seu nível de plasticidade. Nós hipotetizamos que atributos conservadores – reprodutivos e morfológicos – explicam melhor a variação interespecífica na sincronia, enquanto aqueles que podem variar de acordo com o ambiente – alimentação e preferência de habitat – estão fracamente relacionados a essa variação interespecífica. Nós avaliamos a sincronia espacial de espécies de peixes de água doce em um rio altamente fragmentado na região Neotropical e relacionamos os níveis de sincronia com sete preditores: dieta, características reprodutivas (migração, fecundação, cuidado parental e desova), posição na coluna d'água, amplitude de nicho, tamanho do corpo, forma do corpo e ocorrência temporal média de cada espécie. As espécies de peixes apresentaram baixos níveis de sincronia espacial, mas uma alta variação interespecífica (valores de correlação variando de −0,11 a 0,41). Essa variação esteve relacionada principalmente às características reprodutivas das espécies, ou seja, espécies sedentárias com desova parcial e sem cuidado parental apresentaram maior sincronia espacial média do que espécies com características opostas. Em contraste, características mais plásticas (dieta e preferências de habitat) foram preditores ruins da sincronia espacial média. Também especulamos que, apesar da baixa sincronia espacial encontrada, se impactos extremos continuarem a ocorrer na bacia em escala regional, eles podem afetar negativamente as populações locais de peixes de forma síncrona, resultando em aumento do risco de declínios simultâneos. The authors declare no conflict of interest. Data is available upon reasonable request. Appendix S1. Appendix S2. Appendix S3. Appendix S4. Appendix S5. Appendix S6. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. 

Interspecific variation in fish spatial synchrony relates to reproductive traits in a highly fragmented river

RESUMO. Estudos previos no Pantanal brasileiro sugerem que heterogeneidade fisiografica poderia ser usada para delimitar diferentes sub-regioes. Todavia, a magnitude na qual essas regionalizacoes refletem padroes espaciais de variacao na diversidade beta para diferentes grupos taxonomicos nao foi testada ate o momento. O objetivo deste trabalho foi avaliar se os esquemas de regionalizacao propostos para o Pantanal brasileiro descrevem adequadamente a diversidade beta para aves e mamiferos. A presenca e ausencia de cada especie de mamiferos e aves foram registradas em cada uma das 80 celulas de 0.5x0.5 graus em um mapa de grade quadriculada. O indice de similaridade de Jaccard foi usado para estimar a similaridade em cada par de celulas. Um metodo de classificacao nao hierarquico (k-means) foi aplicado para obter classificacao “a posteriori” das celulas dentro de sub-regioes. As forcas de classificacoes (CS) de cada classificacao fisiografica e “a posteriori” foi a diferenca entre similaridade media dentro (W) e entre (B) subdivisoes (CS=W-B). Ambas as classificacoes (“a priori” e “a posteriori”) apresentaram baixos valores de CS, o que indica que elas nao sao aptas a representar os padroes de diversidade beta de mamiferos e aves dentro do Pantanal brasileiro. Os resultados sugerem que, provavelmente por causa da ampla distribuicao geografica e os baixos niveis de endemismo destes taxons, classificacoes fisiograficas do Pantanal brasileiro nao sao atalhos confiaveis para representar os padroes de diversidade beta de aves e mamiferos. Deste modo, inventarios biologicos detalhados sao necessarios para a proposicao de planos de conservacao locais consistentes para esta regiao altamente diversa e ameacada. [Palavras-chave: regionalizacao; areas umidas; biodiversidade animal; k-means; taxons como substituto; forcas de classificacao ]

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Luis Mauricio Bini

Papers

Challenging the Raunkiaeran shortfall and the consequences of using imputed databases

Inequality in aquatic ecosystem services

Catchment scale deforestation increases the uniqueness of subtropical stream communities

Interspecific variation in fish spatial synchrony relates to reproductive traits in a highly fragmented river

Correspondências entre classificações fisiográficas e padrões espaciais de assembleias de aves e mamíferos no Pantanal Brasileiro