On Theory in Ecology

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11620%2F14%3A10286098" target="_blank" >RIV/00216208:11620/14:10286098 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1093/biosci/biu098" target="_blank" >http://dx.doi.org/10.1093/biosci/biu098</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/biosci/biu098" target="_blank" >10.1093/biosci/biu098</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Theory in Ecology

Popis výsledku v původním jazyce

We argue for expanding the role of theory in ecology to accelerate scientific progress, enhance the ability to address environmental challenges, foster the development of synthesis and unification, and improve the design of experiments and large-scale environmental-monitoring programs. To achieve these goals, it is essential to foster the development of what we call efficient theories, which have several key attributes. Efficient theories are grounded in first principles, are usually expressed in the language of mathematics, make few assumptions and generate a large number of predictions per free parameter, are approximate, and entail predictions that provide well-understood standards for comparison with empirical data. We contend that the developmentand successive refinement of efficient theories provide a solid foundation for advancing environmental science in the era of big data.

Název v anglickém jazyce

On Theory in Ecology

Popis výsledku anglicky

We argue for expanding the role of theory in ecology to accelerate scientific progress, enhance the ability to address environmental challenges, foster the development of synthesis and unification, and improve the design of experiments and large-scale environmental-monitoring programs. To achieve these goals, it is essential to foster the development of what we call efficient theories, which have several key attributes. Efficient theories are grounded in first principles, are usually expressed in the language of mathematics, make few assumptions and generate a large number of predictions per free parameter, are approximate, and entail predictions that provide well-understood standards for comparison with empirical data. We contend that the developmentand successive refinement of efficient theories provide a solid foundation for advancing environmental science in the era of big data.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

EH - Ekologie – společenstva

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

BioScience

ISSN

0006-3568

e-ISSN

—

Svazek periodika

64

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

701-710

Kód UT WoS článku

000339988000008

EID výsledku v databázi Scopus

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