NATURE_FARM.bib

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@article{Breiman2001,
abstract = {Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the corre-lation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund {\&} R. Schapire, Machine Learning: Proceedings of the Thirteenth Interna-tional conference, * * * , 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.},
archivePrefix = {arXiv},
arxivId = {http://dx.doi.org/10.1023{\%}2FA{\%}3A1010933404324},
author = {Breiman, Leo},
doi = {10.1023/A:1010933404324},
eprint = {/dx.doi.org/10.1023{\%}2FA{\%}3A1010933404324},
file = {:Users/Ty/Documents/Mendeley Desktop/Breiman{\_}2001{\_}Random forests.pdf:pdf},
isbn = {0885-6125},
issn = {08856125},
journal = {Machine Learning},
keywords = {Classification,Ensemble,Regression},
number = {1},
pages = {5--32},
pmid = {21816105},
primaryClass = {http:},
title = {{Random forests}},
volume = {45},
year = {2001}
}
@article{Nielsen,
author = {Nielsen, Rasmus and Akey, Joshua M and Jakobsson, Mattias and Pritchard, Jonathan K and Tishkoff, Sarah and Willerslev, Eske},
doi = {10.1038/nature21347},
file = {:Users/Ty/Documents/Mendeley Desktop/Nielsen et al.{\_}2017{\_}Tracing the peopling of the world through genomics.pdf:pdf},
issn = {0028-0836},
journal = {Nature},
pages = {302--310},
pmid = {28102248},
title = {{Tracing the peopling of the world through genomics}},
volume = {541},
year = {2017}
}
@article{Cabral2016,
abstract = {Macroecology and biogeography are concerned with understanding biodiversity patterns across space and time. In the past, the two disciplines have addressed this question mainly with correlative approaches, despite frequent calls for more mechanistic explanations. Recent advances in computational power, theoretical understanding, and statistical tools are, however, currently facilitating the development of more system-oriented, mechanistic models. We review these models, identify different model types and theoretical frameworks, compare their processes and properties, and summarize emergent findings. We show that ecological (physiology, demographics, dispersal, biotic interactions) and evolutionary processes, as well as environmental and human-induced drivers, are increasingly modelled mechanistically; and that new insights into biodiversity dynamics emerge from these models. Yet, substantial challenges still lie ahead for this young research field. Among these, we identify scaling, calibration, validation, and balancing complexity as pressing issues. Moreover, particular process combinations are still understudied, and so far models tend to be developed for specific applications. Future work should aim at developing more flexible and modular models that not only allow different ecological theories to be expressed and contrasted, but which are also built for tight integration with all macroecological data sources. Moving the field towards such a ‘systems macroecology' will test and improve our understanding of the causal pathways through which eco-evolutionary processes create diversity patterns across spatial and temporal scales.},
author = {Cabral, Juliano Sarmento and Valente, Luis and Hartig, Florian},
doi = {10.1111/ecog.02480},
file = {:Users/Ty/Documents/Mendeley Desktop/Cabral, Valente, Hartig{\_}2016{\_}Mechanistic simulation models in macroecology and biogeography state-of-art and prospects.pdf:pdf},
isbn = {6503251521},
issn = {09067590},
journal = {Ecography},
keywords = {Diversity patterns,process-based models,systems ecology},
number = {November},
pages = {1--14},
pmid = {26044706},
title = {{Mechanistic simulation models in macroecology and biogeography: state-of-art and prospects}},
url = {http://doi.wiley.com/10.1111/ecog.02480},
year = {2016}
}
@article{Holden2002,
abstract = {Linguistic divergence occurs after speech communities divide, in a process similar to speciation among isolated biological populations. The resulting languages are hierarchically related, like genes or species. Phylogenetic methods developed in evolutionary biology can thus be used to infer language trees, with the caveat that ‘borrowing' of linguistic elements between languages also occurs, to some degree. Maximum–parsimony trees for 75 Bantu and Bantoid African languages were constructed using 92 items of basic vocabulary. The level of character fit on the trees was high (consistency index was 0.65), indicating that a tree model fits Bantu language evolution well, at least for the basic vocabulary. The Bantu language tree reflects the spread of farming across this part of sub–Saharan Africa between ca. 3000 BC and AD 500. Modern Bantu subgroups, defined by clades on parsimony trees, mirror the earliest farming traditions both geographically and temporally. This suggests that the major subgroups of modern Bantu stem from the Neolithic and Early Iron Age, with little subsequent movement by speech communities.},
author = {Holden, Clare Janaki},
doi = {10.1098/rspb.2002.1955},
file = {:Users/Ty/Documents/Mendeley Desktop/Holden{\_}2002{\_}Bantu language trees reflect the spread of farming across sub-Saharan Africa A maximum-parsimony analysis.pdf:pdf},
isbn = {0962-8452},
issn = {0962-8452, 1471-2954},
journal = {Proceedings of the Royal Society of London B: Biological Sciences},
keywords = {bantu,linguistic evolution,maximum parsimony},
number = {1493},
pages = {793--799},
pmid = {11958710},
title = {{Bantu language trees reflect the spread of farming across sub-Saharan Africa: A maximum-parsimony analysis}},
url = {http://rspb.royalsocietypublishing.org/content/269/1493/793{\%}5Cnhttp://rspb.royalsocietypublishing.org/content/269/1493/793?ijkey=f344c092ac2a1ee0f43f5bb0120840b3e93d3c7a{\&}keytype2=tf{\_}ipsecsha{\%}5Cnhttp://rspb.royalsocietypublishing.org/content/royprsb/269/14},
volume = {269},
year = {2002}
}
@article{Bellwood2016,
abstract = {Key Words spread of agriculture, Neolithic/Formative archaeology, farmer-hunter$\backslash$r$\backslash$ninteractions, language family origins and dispersals, population expansions$\backslash$r$\backslash$n■ Abstract The consequences of early agricultural development in several regions$\backslash$r$\backslash$nof the Old and New Worlds included population growth, the spread of new material$\backslash$r$\backslash$ncultures and of food-producing economies, the expansions of language families, and in$\backslash$r$\backslash$nmany cases the geographical expansions of the early farming populations themselves$\backslash$r$\backslash$ninto territories previously occupied by hunters and gatherers. This chapter discusses$\backslash$r$\backslash$nsome of the different outcomes that can be expected according to the differing perspectives$\backslash$r$\backslash$nof archaeology, linguistics, and biological anthropology. I argue that agriculturalist$\backslash$r$\backslash$nexpansion lies at the root of many of the world's major language families, although this$\backslash$r$\backslash$nneed not imply that farmers always replaced hunter-gatherers in the biological sense.$\backslash$r$\backslash$nHistory, enviromental variations, and prior cultural configurations dictated many of the$\backslash$r$\backslash$noutcomes, some of which played a fundamental role in the large-scale genesis of human$\backslash$r$\backslash$ncultural and biological patterning from Neolithic/Formative times into the world$\backslash$r$\backslash$nof today.},
author = {Bellwood, Peter},
doi = {doi:10.1146/annurev.anthro.30.1.181},
file = {:Users/Ty/Documents/Mendeley Desktop/Bellwood{\_}2001{\_}Early Agriculturalist Population Diasporas Farming, Languages, and Genes.pdf:pdf},
isbn = {0084-6570},
issn = {0084-6570},
journal = {Annual Review of Anthropology},
keywords = {abstract the consequences of,dispersals,early agricultural development in,farmer-hunter,formative archaeology,growth,interactions,language family origins and,material,neolithic,new worlds included population,of the old and,population expansions,several regions,spread of agriculture,the spread of new},
number = {May},
pages = {181--207},
pmid = {53},
title = {{Early Agriculturalist Population Diasporas? Farming, Languages, and Genes}},
url = {http://eds.b.ebscohost.com/eds/pdfviewer/pdfviewer?vid=8{\&}sid=9d946a9c-639d-4d42-8b54-7401a0336c3a{\%}40sessionmgr120{\&}hid=126},
volume = {30},
year = {2001}
}
@article{Breiman2002,
abstract = {The V3.1 version of random forests contains some modifications and major additions to Version 3.0. It fixes a bad bug in V3.0. It allows the user to save the trees in the forest and run other data sets through this forest. It also allows the user to save parameters and comments about the run. I apologize in advance for all bugs and would like to hear about them. To find out how this program works, read my paper "Random Forests" Its available on the same web page as this manual. It was recently published in the Machine Learning. Journal The program is written in extended Fortran 77 making use of a number of VAX extensions. It runs on SUN workstations f77 and on Absoft Fortran 77 (available for Windows) and on the free g77 compiler. but may have hang ups on other f77 compilers. If you find such problems and fixes for them, please let me know.},
archivePrefix = {arXiv},
arxivId = {arXiv:1011.1669v3},
author = {Breiman, Leo},
doi = {10.2776/85168},
eprint = {arXiv:1011.1669v3},
file = {:Users/Ty/Documents/Mendeley Desktop/Breiman{\_}2002{\_}Manual on setting up, using, and understanding random forests v3. 1.pdf:pdf},
isbn = {9789279094934},
issn = {1098-6596},
journal = {Technical Report, http://oz.berkeley.edu/users/breiman, Statistics Department University of California Berkeley, {\ldots}},
pages = {29},
pmid = {25246403},
title = {{Manual on setting up, using, and understanding random forests v3. 1}},
url = {http://scholar.google.com/scholar?hl=en{\&}btnG=Search{\&}q=intitle:Manual+On+Setting+Up,+Using,+And+Understanding+Random+Forests+V3.1{\#}0},
year = {2002}
}
@article{Lilley2017,
author = {Lilley, Ian},
doi = {10.1038/s41559-017-0085},
file = {:Users/Ty/Documents/Mendeley Desktop/Lilley{\_}2017{\_}Palaeoecology Agriculture emerges from the calm.pdf:pdf},
issn = {2397-334X},
journal = {Nature Ecology {\&} Evolution},
number = {February},
pages = {0085},
publisher = {Macmillan Publishers Limited},
title = {{Palaeoecology: Agriculture emerges from the calm}},
url = {http://www.nature.com/articles/s41559-017-0085},
volume = {1},
year = {2017}
}
@article{Bellwood1996,
abstract = {Two pure and opposing models existto give historical account of the structure in modern cultural patterns. A phylogenetic account explores divergence from some shared commonality (the word ‘phylogenetic' is from the Greek words for ‘tribal origins'). A reticulate account concentrates on a network of interactions (the word ‘reticulate' comes via French from the Latin for ‘small net'). It follows that neither model may tefl all the story. These continuing issues are explored with particular attention to the relations between histories as they are inferred from archaeological and from linguistic patterns.},
author = {Bellwood, Peter},
file = {:Users/Ty/Documents/Mendeley Desktop/Bellwood{\_}1996{\_}Phylogeny vs reticulation in prehistory.pdf:pdf},
isbn = {0003-598X},
issn = {0003598X},
journal = {Antiquity},
number = {June 1996},
pages = {881--890},
title = {{Phylogeny vs reticulation in prehistory}},
volume = {70},
year = {1996}
}