Process-explicit models reveal the structure and dynamics of biodiversity patterns

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Process-explicit models reveal the structure and dynamics of biodiversity patterns. / Pilowsky, Julia A.; Colwell, Robert K.; Rahbek, Carsten; Fordham, Damien A.

In: Science Advances, Vol. 8, No. 31, eabj2271, 2022.

Research output: Contribution to journal › Review › Research › peer-review

Harvard

Pilowsky, JA, Colwell, RK, Rahbek, C & Fordham, DA 2022, 'Process-explicit models reveal the structure and dynamics of biodiversity patterns', Science Advances, vol. 8, no. 31, eabj2271. https://doi.org/10.1126/sciadv.abj2271

APA

Pilowsky, J. A., Colwell, R. K., Rahbek, C., & Fordham, D. A. (2022). Process-explicit models reveal the structure and dynamics of biodiversity patterns. Science Advances, 8(31), [eabj2271]. https://doi.org/10.1126/sciadv.abj2271

Vancouver

Pilowsky JA, Colwell RK, Rahbek C, Fordham DA. Process-explicit models reveal the structure and dynamics of biodiversity patterns. Science Advances. 2022;8(31). eabj2271. https://doi.org/10.1126/sciadv.abj2271

Author

Pilowsky, Julia A. ; Colwell, Robert K. ; Rahbek, Carsten ; Fordham, Damien A. / Process-explicit models reveal the structure and dynamics of biodiversity patterns. In: Science Advances. 2022 ; Vol. 8, No. 31.

Bibtex

@article{20a2ffa1e9b945988078559085699a6b,

title = "Process-explicit models reveal the structure and dynamics of biodiversity patterns",

abstract = "With ever-growing data availability and computational power at our disposal, we now have the capacity to use process-explicit models more widely to reveal the ecological and evolutionary mechanisms responsible for spatiotemporal patterns of biodiversity. Most research questions focused on the distribution of diversity cannot be answered experimentally, because many important environmental drivers and biological constraints operate at large spatiotemporal scales. However, we can encode proposed mechanisms into models, observe the patterns they produce in virtual environments, and validate these patterns against real-world data or theoretical expectations. This approach can advance understanding of generalizable mechanisms responsible for the distributions of organisms, communities, and ecosystems in space and time, advancing basic and applied science. We review recent developments in process-explicit models and how they have improved knowledge of the distribution and dynamics of life on Earth, enabling biodiversity to be better understood and managed through a deeper recognition of the processes that shape genetic, species, and ecosystem diversity.",

author = "Pilowsky, {Julia A.} and Colwell, {Robert K.} and Carsten Rahbek and Fordham, {Damien A.}",

year = "2022",

doi = "10.1126/sciadv.abj2271",

language = "English",

volume = "8",

journal = "Science advances",

issn = "2375-2548",

publisher = "American Association for the Advancement of Science",

number = "31",

}

RIS

TY - JOUR

T1 - Process-explicit models reveal the structure and dynamics of biodiversity patterns

AU - Pilowsky, Julia A.

AU - Colwell, Robert K.

AU - Rahbek, Carsten

AU - Fordham, Damien A.

PY - 2022

Y1 - 2022

N2 - With ever-growing data availability and computational power at our disposal, we now have the capacity to use process-explicit models more widely to reveal the ecological and evolutionary mechanisms responsible for spatiotemporal patterns of biodiversity. Most research questions focused on the distribution of diversity cannot be answered experimentally, because many important environmental drivers and biological constraints operate at large spatiotemporal scales. However, we can encode proposed mechanisms into models, observe the patterns they produce in virtual environments, and validate these patterns against real-world data or theoretical expectations. This approach can advance understanding of generalizable mechanisms responsible for the distributions of organisms, communities, and ecosystems in space and time, advancing basic and applied science. We review recent developments in process-explicit models and how they have improved knowledge of the distribution and dynamics of life on Earth, enabling biodiversity to be better understood and managed through a deeper recognition of the processes that shape genetic, species, and ecosystem diversity.

AB - With ever-growing data availability and computational power at our disposal, we now have the capacity to use process-explicit models more widely to reveal the ecological and evolutionary mechanisms responsible for spatiotemporal patterns of biodiversity. Most research questions focused on the distribution of diversity cannot be answered experimentally, because many important environmental drivers and biological constraints operate at large spatiotemporal scales. However, we can encode proposed mechanisms into models, observe the patterns they produce in virtual environments, and validate these patterns against real-world data or theoretical expectations. This approach can advance understanding of generalizable mechanisms responsible for the distributions of organisms, communities, and ecosystems in space and time, advancing basic and applied science. We review recent developments in process-explicit models and how they have improved knowledge of the distribution and dynamics of life on Earth, enabling biodiversity to be better understood and managed through a deeper recognition of the processes that shape genetic, species, and ecosystem diversity.

U2 - 10.1126/sciadv.abj2271

DO - 10.1126/sciadv.abj2271

M3 - Review

C2 - 35930641

AN - SCOPUS:85134026329

VL - 8

JO - Science advances

JF - Science advances

SN - 2375-2548

IS - 31

M1 - eabj2271

ER -

ID: 317436083

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