M
Matthew J. Smith
Researcher at Microsoft
Publications - 78
Citations - 6902
Matthew J. Smith is an academic researcher from Microsoft. The author has contributed to research in topics: Population & Ecology (disciplines). The author has an hindex of 32, co-authored 74 publications receiving 5577 citations. Previous affiliations of Matthew J. Smith include Royal Botanic Gardens & University of Aberdeen.
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A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter
TL;DR: A detailed explanation of how MaxEnt works and a prospectus on modeling options are provided to enable users to make informed decisions when preparing data, choosing settings and interpreting output to highlight the need for making biologically motivated modeling decisions.
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The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models
TL;DR: Correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction.
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What do we gain from simplicity versus complexity in species distribution models
Cory Merow,Cory Merow,Cory Merow,Matthew J. Smith,Thomas C. Edwards,Antoine Guisan,Sean M. McMahon,Signe Normand,Wilfried Thuiller,Wilfried Thuiller,Rafael O. Wüest,Rafael O. Wüest,Niklaus E. Zimmermann,Jane Elith +13 more
TL;DR: It is argued for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes.
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Wildlife diseases: from individuals to ecosystems
TL;DR: The authors' ecological understanding of wildlife infectious diseases from the individual host to the ecosystem scale is reviewed, highlighting where conceptual thinking lacks verification, discussing difficulties and challenges, and offering potential future research directions.
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Toward more realistic projections of soil carbon dynamics by Earth system models
Yiqi Luo,Yiqi Luo,Anders Ahlström,Anders Ahlström,Steven D. Allison,Niels H. Batjes,Victor Brovkin,Nuno Carvalhais,Nuno Carvalhais,Adrian Chappell,Philippe Ciais,Eric A. Davidson,Adien Finzi,Katerina Georgiou,Katerina Georgiou,Bertrand Guenet,Oleksandra Hararuk,Jennifer W. Harden,Yujie He,Francesca M. Hopkins,Lifen Jiang,Charles D. Koven,Robert B. Jackson,Chris D. Jones,Mark J. Lara,Junyi Liang,A. David McGuire,A. David McGuire,William J. Parton,Changhui Peng,James T. Randerson,Alejandro Salazar,Carlos A. Sierra,Matthew J. Smith,Hanqin Tian,Katherine Todd-Brown,Margaret S. Torn,Kees Jan van Groenigen,Ying-Ping Wang,Tristram O. West,Yaxing Wei,William R. Wieder,Jianyang Xia,Xia Xu,Xiaofeng Xu,Tao Zhou +45 more
TL;DR: In this article, the authors suggest that model structures should reflect real-world processes, parameters should be calibrated to match model outputs with observations, and external forcing variables should accurately prescribe the environmental conditions that soils experience.