Diversity of response and effect traits provides complementary information about avian community dynamics linked to ecological function

Hordley, Lisbeth A.; Gillings, Simon; Petchey, Owen L.; Tobias, Joe; Oliver, Thomas H.

doi:10.1111/1365-2435.13865

Cited by 16 publications

(32 citation statements)

References 126 publications

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“…Given their effect on ecosystem processes and functions, such traits are now termed effect traits, while response traits aim to capture information about how a species responds to environmental change (Suding et al 2008;Oliver et al 2015), though such information is not always well captured by putative functional traits (Bartomeus et al 2017). Examples of response traits include life-form and seed mass in plants (Sasaki et al 2019), aquatic stage and reproductive strategy in freshwater macroinvertebrates (Thornhill et al 2018), and clutch size and thermal maximum in birds (Hordley et al 2021). Response trait diversity is then typically measured as the functional dispersion (FDis) of the response trait space (Laliberté et al 2010;Rader et al 2013), or sometimes using the closely related Rao's Quadratic Entropy (RaoQ) index (Chillo et al 2011;Correia et al 2018).…”

Section: Range (Derivatives) H)mentioning

confidence: 99%

“…2008)—represents response diversity, measured using the functional dispersion [FDis] index ( e.g ., Spasojevic et al . 2016; Hordley et al . 2021; Schnabel et al .…”

Section: Existing Response Diversity Studiesmentioning

confidence: 99%

“…2019), aquatic stage and reproductive strategy in freshwater macroinvertebrates (Thornhill et al . 2018), and clutch size and thermal maximum in birds (Hordley et al . 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The majority (n = 28 studies, ~60%) measured response diversity using functional traits (see Box 1 for discussion), where the diversity of response traits-that is, those traits that predict some aspect of how a species responds to the environment (Suding et al 2008)-represents response diversity, measured using the functional dispersion [FDis] index (e.g., Spasojevic et al 2016;Hordley et al 2021;Schnabel et al 2021). Some studies measuring the dispersion of functional response traits explicitly do so after defining functional effect groups (Laliberté et al 2010;Thornhill et al 2018;Sasaki et al 2019;Morel et al 2020), producing a response diversity measure closely aligned to the Elmqvist et al (2003) definition, which specifies that response diversity should be measured among species contributing to the same ecosystem function (though subsequent definitions relax this requirement; e.g., Mori et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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How to measure response diversity

Ross

Petchey

Sasaki

et al. 2022

Preprint

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Taxonomic diversity metrics are, at best, proxies for the inter- and intraspecific trait differences that mechanistically underlie the insurance effect of biodiversity—that diversity enhances and stabilises aggregate ecosystem properties. In theory, variation in functional (e.g., biomass) responses to environmental change can buffer and maintain ecosystem functioning. This variation, termed response diversity, is therefore a potentially critical determinant of ecological stability. However, response diversity has yet to be widely quantified, possibly due to difficulties in its measurement. Even when it has been measured, approaches have varied. Here, we review methods for measuring response diversity and propose a methodological framework for quantifying response diversity from experimental or observational data, which can be practically applied in lab and field settings across a range of taxa. Our approach, which is based on environment-dependent functional responses to any biotic or abiotic environmental variable, is conceptually simple and robust to any form of environmental response, including nonlinear responses. By capturing even subtle inter- or intraspecific variation in environmental responses, and environment-dependencies in response diversity, we hope this framework will motivate tests of the diversity-stability relationship from a new perspective, and provide an approach for mapping, monitoring, and protecting this critical element of biodiversity.

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Section: Range (Derivatives) H)mentioning

confidence: 99%

“…2008)—represents response diversity, measured using the functional dispersion [FDis] index ( e.g ., Spasojevic et al . 2016; Hordley et al . 2021; Schnabel et al .…”

Section: Existing Response Diversity Studiesmentioning

confidence: 99%

“…2019), aquatic stage and reproductive strategy in freshwater macroinvertebrates (Thornhill et al . 2018), and clutch size and thermal maximum in birds (Hordley et al . 2021).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How to measure response diversity

Ross

Petchey

Sasaki

et al. 2022

Preprint

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“…Although the role of agroforestry systems in maintaining avian diversity in tea plantations has been demonstrated (Chetana & Ganesh, 2012 ; Sidhu et al, 2010 ), the basis of assessment has largely been the taxonomic diversity of the bird communities, a relatively simplistic metric that provides limited information about how ecosystems function and respond to environmental disturbances compared to other components of avian diversity. For example, components of avian diversity, such as functional and phylogenetic diversity, are expected to more closely reflect ecosystem function and resilience (Cadotte et al, 2011 ; Hordley et al, 2021 ; Sheard et al, 2020 ). Previous studies focusing on the impacts of tropical agriculture on functional and phylogenetic diversity have mainly focused on the impact of pasture, palm oil, and coffee (e.g., Cannon et al, 2019 ; Chapman et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Functional and phylogenetic diversity of an agricultural matrix avifauna: The role of habitat heterogeneity in Afrotropical farmland

Rurangwa

Niyigaba

Tobias

et al. 2022

Ecology and Evolution

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Varied strategies to alleviate the loss of farmland biodiversity have been tested, yet there is still insufficient evidence supporting their effectiveness, especially when considering phylogenetic and functional diversity alongside traditional taxonomic diversity metrics. This conservation challenge is accentuated in the Afrotropics by the rapid agricultural expansion and intensification for the production of cash crops and by a comparative lack of research. In this study, we assessed how farming practices influence avian phylogenetic and functional diversity. We conducted point‐count surveys to assess avian diversity in monocultures of tea and mixed crop farming systems surrounding the Nyungwe rainforest in south‐west Rwanda, allowing us to investigate the drivers of avian diversity at farm level. Species composition was found to be moderately different between farm types, with mixed crop farms supporting higher phylogenetic diversity than tea plantations. There were no significant seasonal differences in species composition, functional or phylogenetic diversity. Overall, functional diversity did not differ between farm types, but the dispersion of trophic‐related traits was significantly higher in mixed crop farms. Both functional and phylogenetic diversity were influenced by floristic diversity, vegetation height, tree number, and elevation to varying degrees. Our results also (i) highlight the role of farmland heterogeneity (e.g., crop species composition, height, and tree cover extent) in encouraging avian functional and phylogenetic diversity in the Afrotropics and (ii) indicate that the generally negative biodiversity impacts of monoculture agriculture can be partially alleviated by extensive agroforestry with an emphasis on indigenous tree species.

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Local and regional‐scale effects of hedgerows on grassland‐ and forest‐associated bird populations within agroecosystems

de Zwaan,

Hannah,

Alavi

et al. 2024

Ecological Applications

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Linear woody features (LWFs), like hedgerows along field edges, provide wildlife habitat and support biodiversity in agroecosystems. Assessments of LWFs usually focus on community‐level indices, such as species richness. However, effective conservation actions need to balance the contrasting habitat preferences of different wildlife species, necessitating a focus on population‐level effects in working landscapes. We assessed associations between LWFs and abundance for 45 bird species within an intensive agroecosystem in eastern Ontario, Canada. We used distance‐ and removal‐sampling methods across 4 years (2016–2019) to estimate local bird abundance in habitats representing a range of LWF densities. We also predicted abundance across a subset of the study region with and without LWFs to understand their contribution to regional population density. Associations between local bird abundance and LWFs were variable among species, but overall community effects were clearly positive, particularly for forest and shrubland species. At the site level, 20/45 species (44%) had higher densities associated with greater LWF presence on average, compared to 5/45 (11%) with negative associations. At the regional scale, LWFs had predicted benefits on total abundance for 31 species (69%), contributing to an estimated 20% increase on average. Positive effects were most pronounced in areas with greater agricultural land use (primarily field crops), suggesting LWFs may provide crucial habitat in heavily modified landscapes but have little to no additional benefit for the avian community in areas with greater existing heterogeneity and habitat retention. Species that responded negatively tended to be at risk with strong habitat preferences for intact forests or large, open grasslands and, thus, greater sensitivity to potential edge effects. With rapidly declining songbird populations and a global need for food security, conservation strategies that amplify biodiversity and enhance agricultural productivity through ecosystem services such as pest control, pollination, and water regulation are vital. We demonstrate the benefits of habitat heterogeneity in agroecosystems on songbird densities and highlight the need to integrate local and landscape‐level assessments in conservation planning. An effective, balanced strategy includes concentrating LWFs in areas of extensive arable crops, with habitat retention patches where possible, while maintaining heterogeneity through mixtures of natural habitats and pastoral farming in less intensive regions.

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Diversity of response and effect traits provides complementary information about avian community dynamics linked to ecological function

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 16 publications

References 126 publications

How to measure response diversity

How to measure response diversity

Functional and phylogenetic diversity of an agricultural matrix avifauna: The role of habitat heterogeneity in Afrotropical farmland

Local and regional‐scale effects of hedgerows on grassland‐ and forest‐associated bird populations within agroecosystems

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