Feedback loops between <scp>3D</scp> vegetation structure and ecological functions of animals

Russo, Nicholas J.; Davies, Andrew B.; Blakey, Rachel V.; Ordway, Elsa M.; Smith, Thomas B.

doi:10.1111/ele.14272

Cited by 4 publications

(3 citation statements)

References 176 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further studies could also inform about how species interact with plants architecture based on their specific traits (e.g. : body plan, mobility type, size, behavior), allowing for finer discrimination of animal strategies (Hao et al, 2021;Johnston & Smith, 2018;Killion et al, 2023b;Randlkofer et al, 2010;Russo et al, 2023).…”

Section: Architecturementioning

confidence: 99%

“…Simulating all these factors is challenging and observations which could support such integration are still sparse. However, recent studies (Killion et al, 2023b;Russo et al, 2023) are informing us about such ecological processes and works such as Hansen et al, (2024) are paving the way forward. Integration in a mechanistic ecological model do not exist yet, to our knowledge, but should be achievable in the near future.…”

Section: Scale Simplificationmentioning

confidence: 99%

“…It has been identified as the main driver of overall ecosystem productivity (Migliavacca et al, 2021), and linked to numerous ecological dynamics. It has been linked to biophysical processes, such as fire regime (Just et al, 2016;Veenendaal et al, 2018) or hydrology (Wu et al, 2022;Zhu et al, 2012), as well as ecosystem functional traits and energetics (Campos-Silva & Piratelli, 2020;Migliavacca et al, 2021;Russo et al, 2023;Stark et al, 2015;West et al, 2009), and particularly shaping biodiversity through biotic dynamics (Srivastava, 2006;Tilman et al, 2014), from plant interactions (Dohn et al, 2017;Franklin et al, 2020;Martínez Cano et al, 2020) to habitat and niche partitioning for animal species (Gámez & Harris, 2022;MacArthur & MacArthur, 1961;Salas-López et al, 2022;Ye et al, 2021). Yet, there is no comprehensive consensus about the overall importance of vegetation structure in ecosystem states and dynamics, as its role is complex (Coverdale & Davies, 2023;Russo et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

MECHANISTIC MODEL OF VEGETATION STRUCTURE AND ANIMAL COMMUNITY INTERACTIONS-INTEGRATING GEDI & TLS DATA IN THE MADINGLEY MODEL

Gaillard,

Doughty,

Abraham

et al. 2024

Preprint

View full text Add to dashboard Cite

Background Vegetation structure is increasingly recognized as a key variable to explain ecosystems states and dynamics. New Remote Sensing tools are available to complement labor intensive field investigations and consider the global biogeography of this parameter. Objectives We propose to model the processes explaining the interaction between vegetation structure and animal community assembly globally, while requiring minimal computing power, based on the most fundamentals assumptions. Methods We integrate spaceborne (GEDI: Global Ecosystem Dynamics Investigation) and ground based (TLS: Terrestrial Laser Scanning) Lidar data in the Madingley general ecosystem model. We compare the outcome of this integration to previous version and to the TetraDensity estimate of animal biomass and Elton traits database for arboreality. Results Animal biomass density simulated by Madingley is closer to global estimates when integrating vegetation structure. The strength of this effect increases with higher cohort body mass and varies with local environmental conditions and stochastic processes. Simulated proportion of arboreality across cohorts is consistently higher than observations. This is consistent with the divergence of biases between model and database. Conclusions Our results concur with our hypotheses about the role of vegetation structure on animal community assembly, as it reduces total animal biomass abundance. However, assessing the accuracy of its relative weight is challenging. While we have global products about arboreality and animal biomass density, they represent modern day ecosystem state, including anthropogenic activity, while Madingley simulates potential ecosystem optimum. Therefore, we call for further research in this field and for challenging modelling attempts to compare with.

show abstract

Section: Architecturementioning

confidence: 99%

Section: Scale Simplificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

MECHANISTIC MODEL OF VEGETATION STRUCTURE AND ANIMAL COMMUNITY INTERACTIONS-INTEGRATING GEDI & TLS DATA IN THE MADINGLEY MODEL

Gaillard,

Doughty,

Abraham

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Divergent seed dispersal outcomes: Interactions between seed, disperser, and forest traits

Dehaudt,

Bruce,

Deblauwe

et al. 2024

Ecology

View full text Add to dashboard Cite

Animals disperse seeds in various ways that affect seed deposition sites and seed survival, ultimately shaping plant species distribution, community composition, and ecosystem structure. Some animal species can disperse seeds through multiple pathways (e.g., defecation, regurgitation, epizoochory), each likely producing distinct seed dispersal outcomes. We studied how seed traits (size and toughness) interact with disperser species to influence seed dispersal pathway and how this ultimately shapes the proportion of seeds deposited in various habitat types. We focused on three frugivorous species of duikers (African forest antelopes) in the Dja Faunal Reserve, a tropical rainforest in southern Cameroon. Duikers can both defecate and regurgitate seeds, the latter predominantly occurring during rumination at their bedding sites (or “nests”). We located duiker nests and dungs along 18 linear 1‐km‐transects to assess: (1) how seed traits affect the likelihood of dispersal via defecation versus regurgitation, (2) if defecated versus regurgitated seeds are deposited at different rates in different forest types (assessed by indigenous Baka), microhabitats, and forest structural attributes (measured by drone lidar), and (3) if these differ between three duiker species that vary in size and diel activity patterns. We found that duikers predominantly defecated small seeds (<3 mm length) and regurgitated larger and tougher seeds (>10 mm length), the latter including 25 different plant species. The three duiker species varied in their nesting habits, with nocturnal bay duikers (Cephalophus dorsalis) nesting in dense understory vegetation at proportions 3–4 times higher than Peter's and yellow‐backed duikers (Cephalophus callipygus and Cephalophus silvicultor). As a result, bay duikers deposited larger regurgitated seeds at a higher rate in habitats with denser understory where lianas and palms predominate and near fallen trees. This directed regurgitation seed deposition likely plays an important and unique role in forest succession and structure. This study highlights the importance of ungulate seed dispersal by regurgitation, a vastly understudied process that could impact many ecosystems given the prevalence of ruminating ungulates worldwide.

show abstract

Close-range underwater photogrammetry for coral reef ecology: a systematic literature review

Remmers,

Grech,

Roelfsema

et al. 2023

Coral Reefs

View full text Add to dashboard Cite

Feedback loops between 3D vegetation structure and ecological functions of animals

Cited by 4 publications

References 176 publications

MECHANISTIC MODEL OF VEGETATION STRUCTURE AND ANIMAL COMMUNITY INTERACTIONS-INTEGRATING GEDI & TLS DATA IN THE MADINGLEY MODEL

MECHANISTIC MODEL OF VEGETATION STRUCTURE AND ANIMAL COMMUNITY INTERACTIONS-INTEGRATING GEDI & TLS DATA IN THE MADINGLEY MODEL

Divergent seed dispersal outcomes: Interactions between seed, disperser, and forest traits

Close-range underwater photogrammetry for coral reef ecology: a systematic literature review

Contact Info

Product

Resources

About