Protecting the global ocean for biodiversity, food and climate

Nature, Год журнала: 2021, Номер 592(7854), С. 397 - 402

Опубликована: Март 17, 2021

Язык: Английский

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Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs

New Phytologist, Год журнала: 2020, Номер 232(3), С. 1123 - 1158

Опубликована: Ноя. 7, 2020

Summary The effects of plants on the biosphere, atmosphere and geosphere are key determinants terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we still only beginning to explore complex relationships between root traits functions. Drawing literature in physiology, ecophysiology, ecology, agronomy soil science, reviewed 24 aspects functioning their with a number system traits, including architecture, morphology, anatomy, chemistry, biomechanics biotic interactions. Based this assessment, critically evaluated current strengths gaps our knowledge, identify future research challenges field ecology. Most importantly, found that broadest importance not those most commonly measured. Also, estimation trait relative for requires us consider more comprehensive range functionally relevant from diverse species, across environments over time series. We also advocate establishing causal hierarchical links among will provide hypothesis‐based framework parsimonious sets strongest functions, link genotypes

Язык: Английский

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A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

New Phytologist, Год журнала: 2021, Номер 232(3), С. 973 - 1122

Опубликована: Окт. 5, 2021

Summary In the context of a recent massive increase in research on plant root functions and their impact environment, ecologists currently face many important challenges to keep generating cutting‐edge, meaningful integrated knowledge. Consideration below‐ground components ecosystem studies has been consistently called for decades, but methodology is disparate sometimes inappropriate. This handbook, based collective effort large team experts, will improve trait comparisons across integration information databases by providing standardised methods controlled vocabularies. It meant be used not only as starting point students scientists who desire working ecosystems, also experts consolidating broadening views multiple aspects ecology. Beyond classical compilation measurement protocols, we have synthesised recommendations from literature provide key background knowledge useful for: (1) defining entities giving keys dissection, classification naming beyond fine‐root vs coarse‐root approach; (2) considering specificity produce sound laboratory field data; (3) describing typical, overlooked steps studying roots (e.g. handling, cleaning storage); (4) gathering metadata necessary interpretation results reuse. Most importantly, all traits introduced with some degree ecological that foundation understanding meaning, typical use uncertainties, methodological conceptual perspectives future research. Considering this, urge readers solely extract protocol measurements this work, take moment read reflect extensive contained broader guide ecology, including sections I–VII introductions each section description. Finally, it critical understand major aim help break down barriers between subdisciplines ecology ecophysiology, broaden researchers’ study create favourable conditions inception comprehensive experiments role functioning.

Язык: Английский

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New approaches for delineating n ‐dimensional hypervolumes

Methods in Ecology and Evolution, Год журнала: 2017, Номер 9(2), С. 305 - 319

Опубликована: Авг. 10, 2017

Abstract Hutchinson's n ‐dimensional hypervolume concept underlies many applications in contemporary ecology and evolutionary biology. Estimating hypervolumes from sampled data has been an ongoing challenge due to conceptual computational issues. We present new algorithms for delineating the boundaries probability density within hypervolumes. The methods produce smooth that can fit either more loosely (Gaussian kernel estimation) or tightly (one‐classification via support vector machine). Further, accept abundance‐weighted data, resulting be given a probabilistic interpretation projected into geographic space. demonstrate properties of these on large dataset characterises functional traits distribution thousands plants. are available version ≥2.0.7 r package. These provide: (i) robust approach shape hypervolumes; (ii) efficient performance high‐dimensional datasets; (iii) improved measures diversity environmental niche breadth.

Язык: Английский

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Areas of global importance for conserving terrestrial biodiversity, carbon and water

Nature Ecology & Evolution, Год журнала: 2021, Номер 5(11), С. 1499 - 1509

Опубликована: Авг. 23, 2021

Язык: Английский

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Fine-root traits in the global spectrum of plant form and function

Nature, Год журнала: 2021, Номер 597(7878), С. 683 - 687

Опубликована: Сен. 29, 2021

Язык: Английский

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Concepts and applications in functional diversity

Functional Ecology, Год журнала: 2021, Номер 35(9), С. 1869 - 1885

Опубликована: Июль 16, 2021

Abstract The use of functional diversity analyses in ecology has grown exponentially over the past two decades, broadening our understanding biological and its change across space time. Virtually all ecological sub‐disciplines recognise critical value looking at species communities from a perspective, this led to proliferation methods for estimating contrasting dimensions diversity. Differences between these their development generated terminological inconsistencies confusion about selection most appropriate approach addressing any particular question, hampering potential comparative studies, simulation exercises meta‐analyses. Two general mathematical frameworks are prevailing: those based on dissimilarity matrices (e.g. Rao entropy, dendrograms) relying multidimensional spaces, constructed as either convex hulls or probabilistic hypervolumes. We review frameworks, discuss strengths weaknesses provide an overview main R packages performing calculations. In parallel, we propose way organising metrics unified scheme quantify richness, divergence regularity individuals under each framework. This offers roadmap confidently approaching both theoretically practically. A free Plain Language Summary can be found within Supporting Information article.

Язык: Английский

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mFD: an R package to compute and illustrate the multiple facets of functional diversity

Ecography, Год журнала: 2021, Номер 2022(1)

Опубликована: Дек. 13, 2021

Functional diversity (FD), the of organism attributes that relates to their interactions with abiotic and biotic environment, has been increasingly used for last two decades in ecology, biogeography conservation. Yet, FD many facets estimations are not standardized nor embedded a single tool. mFD (multifaceted functional diversity) is an R package uses matrices species assemblages trait values as building blocks compute most indices. firstly based on functions allowing user summarize assemblage data. Then it calculates trait‐based distances between pairs, informs whether have be clustered into entities finally computes multidimensional space. To let choose appropriate space computing indices, allow assessing illustrating quality each Next, provides 6 core calculate 16 existing indices distances, or position The also graphical ggplot library illustrate through customizable high‐resolution plots distribution among All include internal validation processes check errors data formatting which return detailed error messages. facilitate use framework, we built associated website hosting five tutorials all step by step.

Язык: Английский

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When Do Ecosystem Services Depend on Rare Species?

Trends in Ecology & Evolution, Год журнала: 2019, Номер 34(8), С. 746 - 758

Опубликована: Май 16, 2019

Язык: Английский

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Towards a more balanced combination of multiple traits when computing functional differences between species

Methods in Ecology and Evolution, Год журнала: 2020, Номер 12(3), С. 443 - 448

Опубликована: Дек. 3, 2020

Abstract Functional trait differences between species are key drivers of community assembly and ecosystem functioning. Quantifying these routinely requires using approaches like the Gower distance to combine various types traits into a multi‐trait dissimilarity. Without special care, can however produce dissimilarity with disproportional contribution certain traits, particularly categorical bundle correlated reflecting similar ecological functions. These effects persist even after applying multivariate analyses traditionally used reduce dimensionality. We propose ‘gawdis’ R function, corresponding package, more uniform contributions different including fuzzy coded ones. The approach is based on minimizing in correlation each trait, or groups This done either an analytical numerical solution, both available function. Properly taking account multiple for interpreting complex differences. gawdis r package CRAN be further applied improve equitability distance‐based measures other field research, such as social sciences marketing surveys, which analyse mixed type data.

Язык: Английский

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