ORCID Profile
0000-0002-0353-9154
Current Organisation
University of Helsinki
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Publisher: Informa UK Limited
Date: 05-2005
Publisher: Wiley
Date: 30-08-2022
DOI: 10.1111/ECOG.06287
Abstract: The widespread use of species traits in basic and applied ecology, conservation and biogeography has led to an exponential increase in functional ersity analyses, with 10 000 papers published in 2010–2020, and 1800 papers only in 2021. This interest is reflected in the development of a multitude of theoretical and methodological frameworks for calculating functional ersity, making it challenging to navigate the myriads of options and to report detailed accounts of trait‐based analyses. Therefore, the discipline of trait‐based ecology would benefit from the existence of a general guideline for standard reporting and good practices for analyses. We devise an eight‐step protocol to guide researchers in conducting and reporting functional ersity analyses, with the overarching goal of increasing reproducibility, transparency and comparability across studies. The protocol is based on: 1) identification of a research question 2) a s ling scheme and a study design 3–4) assemblage of data matrices 5) data exploration and preprocessing 6) functional ersity computation 7) model fitting, evaluation and interpretation and 8) data, metadata and code provision. Throughout the protocol, we provide information on how to best select research questions, study designs, trait data, compute functional ersity, interpret results and discuss ways to ensure reproducibility in reporting results. To facilitate the implementation of this template, we further develop an interactive web‐based application ( stepFD ) in the form of a checklist workflow, detailing all the steps of the protocol and allowing the user to produce a final ‘reproducibility report' to upload alongside the published paper. A thorough and transparent reporting of functional ersity analyses ensures that ecologists can incorporate others' findings into meta‐analyses, the shared data can be integrated into larger databases for consensus analyses, and available code can be reused by other researchers. All these elements are key to pushing forward this vibrant and fast‐growing field of research.
Publisher: Cold Spring Harbor Laboratory
Date: 19-03-2021
DOI: 10.1101/2021.03.17.435827
Abstract: Understanding the variation in community composition and species abundances, i.e., β- ersity, is at the heart of community ecology. A common approach to examine β- ersity is to evaluate directional turnover in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distances. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 149 datasets comprising different types of organisms and environments. We modelled an exponential distance decay for each dataset using generalized linear models and extracted r 2 and slope to analyse the strength and the rate of the decay. We studied whether taxonomic or functional similarity has stronger decay across the spatial and environmental distances. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm, and organismal features. Taxonomic distance decay was stronger along spatial and environmental distances compared with functional distance decay. The rate of taxonomic spatial distance decay was the fastest in the datasets from mid-latitudes while the rate of functional decay increased with latitude. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distances but a higher rate of decay along environmental distances. Marine ecosystems had the slowest rate of decay. This synthesis is an important step towards a more holistic understanding of patterns and drivers of taxonomic and functional β- ersity.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 23-06-2023
Abstract: Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches h er conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.
Publisher: Wiley
Date: 12-05-2022
DOI: 10.1111/GEB.13513
Abstract: Understanding the variation in community composition and species abundances (i.e., β‐ ersity) is at the heart of community ecology. A common approach to examine β‐ ersity is to evaluate directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments. Global. 1990 to present. From diatoms to mammals. We measured the strength of the decay using ranked Mantel tests (Mantel r ) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features. Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid‐latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances. In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal‐related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost‐effective option for investigating community changes in heterogeneous environments.
No related grants have been discovered for Caio Graco Rodrigues Leandro Roza.