Abstract
Rewilding, the restoration of natural processes to create self-sustaining and resilient ecosystems, is an increasingly popular conservation approach. However, outcomes are often unpredictable, and effective ecological monitoring is critical for understanding impacts. Integrating environmental DNA (eDNA) metabarcoding with other non-invasive tools may help provide more comprehensive assessments of taxonomic and functional diversity and trophic complexity.
We applied an integrated monitoring approach at a rewilding site in Scotland, comparing vertebrate diversity detected by metabarcoding four eDNA sample types (water, soil, tree rolling, scat) with passive acoustic monitoring (PAM) and camera trapping. Each method was evaluated for taxonomic richness, community composition, functional diversity using trait-based analyses, and trophic complexity through co-occurrence networks. The comparative effectiveness of these methods is rarely explored beyond basic taxonomic diversity metrics.
In total, 79 vertebrate taxa were detected: PAM captured 52 taxa, eDNA 44, and camera traps 17. Of the eDNA substrates, water and tree-rolling samples had the highest richness. Each method detected unique species, with birds and bats best covered by PAM, and small mammals by eDNA. Community composition varied between methods, with eDNA substrates capturing broader communities. PAM revealed the most pronounced community differences between wooded and open habitats.
Tree rolling and water eDNA captured the greatest functional diversity, while PAM showed higher redundancy, detecting species with similar ecological roles. No single method captured all functional traits. Integrating eDNA methods with PAM produced the most complete trophic network. PAM provided the most complete network but missed key terrestrial interactions that were filled by eDNA.
Synthesis and applications: Our findings highlight the necessity of an integrated multi-method ‘toolkit’ for practitioners to comprehensively capture vertebrate richness, functional diversity, and trophic complexity, particularly in rewilding contexts. We recommend combining PAM with either tree rolling or water eDNA sampling as an optimal monitoring strategy, balancing their complementary strengths in taxonomic and functional coverage.
(This article is a preprint and has not been certified by peer review.)
We applied an integrated monitoring approach at a rewilding site in Scotland, comparing vertebrate diversity detected by metabarcoding four eDNA sample types (water, soil, tree rolling, scat) with passive acoustic monitoring (PAM) and camera trapping. Each method was evaluated for taxonomic richness, community composition, functional diversity using trait-based analyses, and trophic complexity through co-occurrence networks. The comparative effectiveness of these methods is rarely explored beyond basic taxonomic diversity metrics.
In total, 79 vertebrate taxa were detected: PAM captured 52 taxa, eDNA 44, and camera traps 17. Of the eDNA substrates, water and tree-rolling samples had the highest richness. Each method detected unique species, with birds and bats best covered by PAM, and small mammals by eDNA. Community composition varied between methods, with eDNA substrates capturing broader communities. PAM revealed the most pronounced community differences between wooded and open habitats.
Tree rolling and water eDNA captured the greatest functional diversity, while PAM showed higher redundancy, detecting species with similar ecological roles. No single method captured all functional traits. Integrating eDNA methods with PAM produced the most complete trophic network. PAM provided the most complete network but missed key terrestrial interactions that were filled by eDNA.
Synthesis and applications: Our findings highlight the necessity of an integrated multi-method ‘toolkit’ for practitioners to comprehensively capture vertebrate richness, functional diversity, and trophic complexity, particularly in rewilding contexts. We recommend combining PAM with either tree rolling or water eDNA sampling as an optimal monitoring strategy, balancing their complementary strengths in taxonomic and functional coverage.
(This article is a preprint and has not been certified by peer review.)
| Original language | English |
|---|---|
| Number of pages | 31 |
| DOIs | |
| Publication status | Published online - 2 Aug 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
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SDG 15 Life on Land
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