Trait-based approaches to paleoenvironmental reconstructions: What is in the community-weighted trait mean?

Trait-based approaches to paleoenvironmental reconstructions offer a powerful framework for inferring past climates and environments. While analytical methods have advanced empirically, their evolutionary-theoretical basis is rarely explicitly incorporated into methodological developments. Here, we integrate trait-based palaeoecological modelling with the Law of Energy Equivalence that follows from the Red Queen's hypothesis to refine how community-weighted trait means are computed. Using traits from present-day large herbivorous mammalian communities, we test four methods of weighting community trait means – by species, relative abundance, biomass, and energy intake to predict annual precipitation, mean annual temperature, and terrestrial net primary productivity at the continental scale. Our results show that energy intake-weighted traits provide the most accurate predictions in most environments in line with theoretical expectations, closely followed by species-weighted mean traits, while relative abundance-weighted traits perform best in climatically extreme sites. Refining trait-based methodologies for paleoenvironmental reconstructions contributes to a broader understanding of ecosystem dynamics across time. • Weighing community-level trait means by energy intake improves the accuracy of trait-based palaeocliomate reconstructions. • Weighing community-level trait means by energy intake is consistent with macroevolutionary theory of Energy Equivalence. • Refining trait-based methodologies for paleoenvironmental reconstructions contributes to a broader understanding of ecosystem dynamics across time.

Authors

Institutions

Publication Details

Journal
Palaeogeography Palaeoclimatology Palaeoecology
Published
2025-05-01
DOI
https://doi.org/10.1016/j.palaeo.2025.112982
Citations
1
Primary Topic
Pleistocene-Era Hominins and Archaeology
Type
article
Field-Weighted Citation Impact
11.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trait-based approaches to paleoenvironmental reconstructions: What is in the community-weighted trait mean?

Indrė Žliobaitė, A. Michelle Lawing
1 citations
Palaeogeography Palaeoclimatology Palaeoecology
Pleistocene-Era Hominins and Archaeology
11.35
article

Trait-based approaches to paleoenvironmental reconstructions: What is in the community-weighted trait mean?

Indrė Žliobaitė, A. Michelle Lawing
article en
1 citations

Abstract

Trait-based approaches to paleoenvironmental reconstructions offer a powerful framework for inferring past climates and environments. While analytical methods have advanced empirically, their evolutionary-theoretical basis is rarely explicitly incorporated into methodological developments. Here, we integrate trait-based palaeoecological modelling with the Law of Energy Equivalence that follows from the Red Queen's hypothesis to refine how community-weighted trait means are computed. Using traits from present-day large herbivorous mammalian communities, we test four methods of weighting community trait means – by species, relative abundance, biomass, and energy intake to predict annual precipitation, mean annual temperature, and terrestrial net primary productivity at the continental scale. Our results show that energy intake-weighted traits provide the most accurate predictions in most environments in line with theoretical expectations, closely followed by species-weighted mean traits, while relative abundance-weighted traits perform best in climatically extreme sites. Refining trait-based methodologies for paleoenvironmental reconstructions contributes to a broader understanding of ecosystem dynamics across time. • Weighing community-level trait means by energy intake improves the accuracy of trait-based palaeocliomate reconstructions. • Weighing community-level trait means by energy intake is consistent with macroevolutionary theory of Energy Equivalence. • Refining trait-based methodologies for paleoenvironmental reconstructions contributes to a broader understanding of ecosystem dynamics across time.

Palaeogeography Palaeoclimatology PalaeoecologyVol. 672
University of Helsinki (FI), Helsinki Institute of Physics (FI), Texas A&M University (US)
Academy of Finland, Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta
Openalex Percentile: Top 3%
Pleistocene-Era Hominins and Archaeology
11.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.