Evidence map›Paper›PMID 26811797›Full record

ArticleEcology and evolution2016

On the selection of thresholds for predicting species occurrence with presence-only data.

Canran Liu, Graeme Newell, Matt White

Abstract read
In one paragraph

Article in Ecology and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers.

0numbers the graph read from it
0cells of the map it votes in
190citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

190 citing papers in PubMed.

  1. Integrating fossil data in ecological niche models to improve predictions of future habitat of Caribbean corals.Conservation biology : the journal of the Society for Conservation Biology · 2026
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  7. Uncovering correlates of decline and critical refuges for a threatened terrestrial mammal.Conservation biology : the journal of the Society for Conservation Biology · 2026
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  11. Severe Climate-Driven Range Contraction ofEcology and evolution · 2026
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  13. Spatiotemporal Dynamics of Suitable Habitat forPlants (Basel, Switzerland) · 2026
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  19. Conservation-Oriented Analysis ofPlants (Basel, Switzerland) · 2026
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130 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Canran LiuArthur Rylah Institute for Environmental Research Department of Environment, Land, Water and Planning Heidelberg Victoria 3084 Australia.
Graeme NewellArthur Rylah Institute for Environmental Research Department of Environment, Land, Water and Planning Heidelberg Victoria 3084 Australia.
Matt WhiteArthur Rylah Institute for Environmental Research Department of Environment, Land, Water and Planning Heidelberg Victoria 3084 Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Presence-only data present challenges for selecting thresholds to transform species distribution modeling results into binary outputs. In this article, we compare two recently published threshold selection methods (maxSSS and maxF pb) and examine the effectiveness of the threshold-based prevalence estimation approach. Six virtual species with varying prevalence were simulated within a real landscape in southeastern Australia. Presence-only models were built with DOMAIN, generalized linear model, Maxent, and Random Forest. Thresholds were selected with two methods maxSSS and maxF pb with four presence-only datasets with different ratios of the number of known presences to the number of random points (KP-RP ratio). Sensitivity, specificity, true skill statistic, and F measure were used to evaluate the performance of the results. Species prevalence was estimated as the ratio of the number of predicted presences to the total number of points in the evaluation dataset. Thresholds selected with maxF pb varied as the KP-RP ratio of the threshold selection datasets changed. Datasets with the KP-RP ratio around 1 generally produced better results than scores distant from 1. Results produced by We conclude that maxFpb had specificity too low for very common species using Random Forest and Maxent models. In contrast, maxSSS produced consistent results whichever dataset was used. The estimation of prevalence was almost always biased, and the bias was very large for DOMAIN and Random Forest predictions. We conclude that maxF pb is affected by the KP-RP ratio of the threshold selection datasets, but maxSSS is almost unaffected by this ratio. Unbiased estimations of prevalence are difficult to be determined using the threshold-based approach.

Indexed as

F measurepresence‐onlyprevalencespecies distribution modelingspecificitythreshold

Identifiers

PMID26811797
PMCPMC4716501

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.