Evaluating baselines for long‐term ecological monitoring of biodiversity trends: insights from the US National Ecological Observatory Network carabid data

Evidence is mounting that rapid environmental change threatens global insect biodiversity, underscoring the need for informed conservation strategies that protect both species and the ecosystem services they provide. Armed with accurate baseline community data, long‐term continental‐scale monitoring projects are invaluable for detecting and predicting responses to ecological change. However, high species diversity and temporal variability in population sizes can hinder our ability to establish baselines, and, thus, obscure, exaggerate, or reverse temporal trends in long‐term insect data. With its scale and consistent protocol, the US National Ecological Observatory Network (NEON) carabid pitfall trapping data provides an excellent case study for evaluating sampling effort. We use species incidence‐frequencies calculated from more than 200 000 identified carabids across up to 10 years of sampling and 46 field sites to extrapolate asymptotic richness and Shannon diversity. We find that the completeness of observed species richness and diversity is negatively related to year‐to‐year species turnover and diversity metrics themselves, but improves with increasing sampling duration. While observed Shannon diversity converges to asymptotic estimates within a few years, we find that NEON's intensive sampling is unlikely to capture all species, even if no biodiversity loss occurs over its 30‐year span. If the mechanisms driving these patterns can be understood, they hold important implications for optimizing sampling designs in studies focused on ecological change detection, particularly for diverse and temporally variable taxa. Our findings underscore the critical importance of long‐term monitoring and prompt reconsideration of how we interpret trends in existing biodiversity data, given the complexity of establishing robust baselines.

Authors

Institutions

Publication Details

Journal
Oikos
Published
2026-02-16
DOI
https://doi.org/10.1002/oik.11943
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating baselines for long‐term ecological monitoring of biodiversity trends: insights from the US National Ecological Observatory Network carabid data

Kelsey M. Yule, Ava Claus, M. Andrew Johnston
Oikos
Species Distribution and Climate Change
article

Evaluating baselines for long‐term ecological monitoring of biodiversity trends: insights from the US National Ecological Observatory Network carabid data

Kelsey M. Yule, Ava Claus, M. Andrew Johnston
article en

Abstract

Evidence is mounting that rapid environmental change threatens global insect biodiversity, underscoring the need for informed conservation strategies that protect both species and the ecosystem services they provide. Armed with accurate baseline community data, long‐term continental‐scale monitoring projects are invaluable for detecting and predicting responses to ecological change. However, high species diversity and temporal variability in population sizes can hinder our ability to establish baselines, and, thus, obscure, exaggerate, or reverse temporal trends in long‐term insect data. With its scale and consistent protocol, the US National Ecological Observatory Network (NEON) carabid pitfall trapping data provides an excellent case study for evaluating sampling effort. We use species incidence‐frequencies calculated from more than 200 000 identified carabids across up to 10 years of sampling and 46 field sites to extrapolate asymptotic richness and Shannon diversity. We find that the completeness of observed species richness and diversity is negatively related to year‐to‐year species turnover and diversity metrics themselves, but improves with increasing sampling duration. While observed Shannon diversity converges to asymptotic estimates within a few years, we find that NEON's intensive sampling is unlikely to capture all species, even if no biodiversity loss occurs over its 30‐year span. If the mechanisms driving these patterns can be understood, they hold important implications for optimizing sampling designs in studies focused on ecological change detection, particularly for diverse and temporally variable taxa. Our findings underscore the critical importance of long‐term monitoring and prompt reconsideration of how we interpret trends in existing biodiversity data, given the complexity of establishing robust baselines.

Oikos
Purdue University West Lafayette (US), Knowledge Integration (United Kingdom) (GB)
Life in Land
Openalex Percentile: Top 54%
Species Distribution and Climate Change
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.