Journal ArticleDOI
Life-history traits predict species responses to habitat area and isolation: a cross-continental synthesis
Erik Öckinger,Oliver Schweiger,Thomas O. Crist,Diane M. Debinski,Jochen Krauss,Mikko Kuussaari,Jessica D. Petersen,Juha Pöyry,Josef Settele,Keith S. Summerville,Riccardo Bommarco +10 more
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TLDR
Overall, species richness increased with habitat patch area and connectivity and implies that both species richness and composition change in a predictable manner with habitat loss and fragmentation.Abstract:
There is a lack of quantitative syntheses of fragmentation effects across species and biogeographic regions, especially with respect to species life-history traits. We used data from 24 independent studies of butterflies and moths from a wide range of habitats and landscapes in Europe and North America to test whether traits associated with dispersal capacity, niche breadth and reproductive rate modify the effect of habitat fragmentation on species richness. Overall, species richness increased with habitat patch area and connectivity. Life-history traits improved the explanatory power of the statistical models considerably and modified the butterfly species-area relationship. Species with low mobility, a narrow feeding niche and low reproduction were most strongly affected by habitat loss. This demonstrates the importance of considering life-history traits in fragmentation studies and implies that both species richness and composition change in a predictable manner with habitat loss and fragmentation.read more
Citations
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The Theory of Island Biogeography
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Journal ArticleDOI
Defaunation in the Anthropocene
TL;DR: Defaunation is both a pervasive component of the planet’s sixth mass extinction and also a major driver of global ecological change.
Journal ArticleDOI
Native Pollinators in Anthropogenic Habitats
TL;DR: There is a need for studies of pollinator species composition and relative abundance, rather than simply species richness and aggregate abundance, to identify the species that are lost and gained with increasing land-use change.
Journal ArticleDOI
Historical changes in northeastern US bee pollinators related to shared ecological traits
Ignasi Bartomeus,John S. Ascher,John S. Ascher,Jason Gibbs,Bryan N. Danforth,David L. Wagner,Shannon M. Hedtke,Rachael Winfree +7 more
TL;DR: A long-term study of relative rates of change for an entire regional bee fauna in the northeastern United States, based on >30,000 museum records representing 438 species shows that despite marked increases in human population density and large changes in anthropogenic land use, aggregate native species richness declines were modest outside of the genus Bombus.
References
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Journal ArticleDOI
The Theory of Island Biogeography
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Book
The Theory of Island Biogeography
TL;DR: 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
Book
Mixed-Effects Models in S and S-PLUS
TL;DR: Linear Mixed-Effects and Nonlinear Mixed-effects (NLME) models have been studied in the literature as mentioned in this paper, where the structure of grouped data has been used for fitting LME models.
Book
Data Analysis Using Regression and Multilevel/Hierarchical Models
Andrew Gelman,Yu-Sung Su +1 more
TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.
Journal ArticleDOI
Generalized linear mixed models: a practical guide for ecology and evolution
Benjamin M. Bolker,Mollie Elizabeth Brooks,Connie J. Clark,Shane W. Geange,John R. Poulsen,M. Henry H. Stevens,Jada-Simone S. White +6 more
TL;DR: The use (and misuse) of GLMMs in ecology and evolution are reviewed, estimation and inference are discussed, and 'best-practice' data analysis procedures for scientists facing this challenge are summarized.