
Trends in Ecology & Evolution, Год журнала: 2015, Номер 30(12), С. 714 - 724
Опубликована: Окт. 23, 2015
Язык: Английский
Trends in Ecology & Evolution, Год журнала: 2015, Номер 30(12), С. 714 - 724
Опубликована: Окт. 23, 2015
Язык: Английский
Journal of Ecology, Год журнала: 2014, Номер 102(2), С. 275 - 301
Опубликована: Фев. 19, 2014
Summary The leaf economics spectrum (LES) provides a useful framework for examining species strategies as shaped by their evolutionary history. However, that spectrum, originally described, involved only two key resources (carbon and nutrients) one of three economically important plant organs. Herein, I evaluate whether the idea can be broadly extended to water – third resource –stems, roots entire plants individual, community ecosystem scales. My overarching hypothesis is strong selection along trait trade‐off axes, in tandem with biophysical constraints, results convergence any taxon on uniformly fast, medium or slow strategy (i.e. rates acquisition processing) all organs resources. Evidence economic spectra exists stems well leaves, traits related carbon nutrients. These apply generally within across scales (within communities, climate zones, biomes lineages). There are linkages coupling among resources, resulting an integrated whole‐plant spectrum. Species capable moving rapidly have low tissue density, short life span high flux at organ individual reverse true strategy. Different may different conditions, but being fast respect requires others, general feature species. Economic influence performance fitness consistent trait‐based theory about underlying adaptive mechanisms. Traits help explain differences growth survival gradients thus distribution assembly communities light, nutrient gradients. scale up associated faster processes such decomposition primary productivity, process rates. Synthesis . matter. A single ‘fast–slow’ integrates universe helps ecological strategies, functioning ecosystems.
Язык: Английский
Процитировано
3233Global Change Biology, Год журнала: 2019, Номер 26(1), С. 119 - 188
Опубликована: Дек. 31, 2019
Abstract Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, influence ecosystem properties their benefits detriments people. trait data thus represent the basis for a vast area research spanning from evolutionary biology, community functional ecology, biodiversity conservation, landscape management, restoration, biogeography earth system modelling. Since its foundation in 2007, TRY database plant traits has grown continuously. It now provides unprecedented coverage under an open access policy is main used by worldwide. Increasingly, also supports new frontiers trait‐based research, including identification gaps subsequent mobilization or measurement data. To support this development, article we evaluate extent compiled analyse emerging patterns representativeness. Best species achieved categorical traits—almost complete ‘plant growth form’. However, most relevant ecology vegetation modelling are characterized continuous intraspecific variation trait–environmental relationships. These have be measured on individual respective environment. Despite coverage, observe humbling lack completeness representativeness these many aspects. We, therefore, conclude that reducing biases remains key challenge requires coordinated approach measurements. This can only collaboration with initiatives.
Язык: Английский
Процитировано
1580Annual Review of Ecology Evolution and Systematics, Год журнала: 2015, Номер 46(1), С. 523 - 549
Опубликована: Окт. 30, 2015
Ecologists and evolutionary biologists are increasingly using big-data approaches to tackle questions at large spatial, taxonomic, temporal scales. However, despite recent efforts gather two centuries of biodiversity inventories into comprehensive databases, many crucial research remain unanswered. Here, we update the concept knowledge shortfalls review tradeoffs between generality uncertainty. We present seven key current data. Four previously proposed pinpoint gaps for species taxonomy (Linnean), distribution (Wallacean), abundance (Prestonian), patterns (Darwinian). also redefine Hutchinsonian shortfall apply abiotic tolerances propose new relating limited traits (Raunkiæran) biotic interactions (Eltonian). conclude with a general framework combined impacts consequences large-scale ecological consider ways overcoming dealing uncertainty they generate.
Язык: Английский
Процитировано
1321Biological reviews/Biological reviews of the Cambridge Philosophical Society, Год журнала: 2016, Номер 92(2), С. 1156 - 1173
Опубликована: Апрель 22, 2016
ABSTRACT One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding predicting ecological processes from species' traits has been considered a ‘ H oly G rail’ in ecology. Plant functional are increasingly being used develop mechanistic models that can how communities will respond abiotic biotic perturbations species affect ecosystem function services rapidly changing world; however, significant remain. In this review, we highlight recent work outstanding questions three areas: ( i ) selecting relevant traits; ii describing intraspecific trait variation incorporating into models; iii scaling data community‐ ecosystem‐level processes. Over the past decade, there have advances characterization plant strategies based on relationships, integration multivariate indices community function. However, utility trait‐based approaches ecology benefit efforts demonstrate these influence organismal, community, across vegetation types, which may be achieved through meta‐analysis enhancement databases. Additionally, interactions need incorporated predictive using tools such as Bayesian hierarchical modelling. Finally, existing linking empirically tested for their applicability realized.
Язык: Английский
Процитировано
722Proceedings of the National Academy of Sciences, Год журнала: 2014, Номер 111(38), С. 13690 - 13696
Опубликована: Сен. 15, 2014
Understanding, modeling, and predicting the impact of global change on ecosystem functioning across biogeographical gradients can benefit from enhanced capacity to represent biota as a continuous distribution traits. However, this is challenge for field biogeography historically grounded species concept. Here we focus newly emergent functional biogeography: study geographic trait diversity organizational levels. We show how bridges species-based earth science provide ideas tools help explain in multifaceted (including species, functional, phylogenetic diversities), predict services worldwide, infuse regional conservation programs with basis. Although much recent progress has been made possible because rising multiple data streams, new developments ecoinformatics, methodological advances, future directions should theoretical comprehensive framework scaling biotic interactions trophic levels its ecological implications.
Язык: Английский
Процитировано
655Nature Ecology & Evolution, Год журнала: 2018, Номер 2(12), С. 1906 - 1917
Опубликована: Окт. 31, 2018
Язык: Английский
Процитировано
593Oecologia, Год журнала: 2016, Номер 180(4), С. 923 - 931
Опубликована: Янв. 21, 2016
Язык: Английский
Процитировано
453Proceedings of the National Academy of Sciences, Год журнала: 2015, Номер 113(1), С. 230 - 235
Опубликована: Дек. 22, 2015
Significance Schedules of survival, growth, and reproduction define life-history strategies across species. Understanding how are structured is fundamental to our understanding the evolution, abundance, distribution We found that 418 plant species worldwide explained by an axis representing pace life another wide range reproductive strategies. This framework predicts responses perturbations long-term population performance, showing great promise as a predictive tool for environmental change.
Язык: Английский
Процитировано
401Trends in Ecology & Evolution, Год журнала: 2016, Номер 31(5), С. 382 - 394
Опубликована: Апрель 25, 2016
Язык: Английский
Процитировано
386Trends in Ecology & Evolution, Год журнала: 2015, Номер 30(9), С. 531 - 539
Опубликована: Июль 17, 2015
Язык: Английский
Процитировано
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