Evidence map›Paper›PMID 38025689›Full record

ArticlePeerJ2023

Predicting carrying capacity of a large carnivore from prey densities: a new approach.

Nilanjan Chatterjee, Indranil Mukhopadhyay, Parag Nigam, Bilal Habib

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Nilanjan ChatterjeeWildlife Institute of India, Dehradun, India.
Indranil MukhopadhyayHuman Genetics Unit, Indian Statistical Institute, Kolkata, India.
Parag NigamWildlife Institute of India, Dehradun, India.
Bilal HabibWildlife Institute of India, Dehradun, India.
Wildlife Institute of India · INIndian Statistical Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Large carnivores play a crucial role in maintaining the balance of the ecosystem. Successful conservation initiatives have often led to a huge increase in predators which has often led to negative interactions with humans. Without the knowledge of the carrying capacity of the top predator, such decisions become challenging. Here, we have derived a new equation to estimate the carrying capacity of tigers based on the individual prey species density. Methods: We used tiger densities and respective prey densities of different protected areas. Relative prey abundance was used instead of absolute prey density as this could be a better surrogate of the prey preference. We used a regression approach to derive the species-wise equation. We have also scaled these coefficients accordingly to control the variation in the standard error (heteroscedasticity) of the tiger density. Furthermore, we have extended this regression equation for different species to different weight classes for more generalized application of the method. Results: The new equations performed considerably better compared to the earlier existing carrying capacity equations. Incorporating the species-wise approach in the equation also reflected the preference of the prey species for the tiger. This is the first carrying capacity equation where the individual prey densities are used to estimate the carnivore population density. The coefficient estimates of the model with the comparison with prey-predator power laws also reflect the differential effect of tigers on different prey species. The carrying capacity estimates will aid in a better understanding of the predator-prey interaction and will advance better management of the top predator.

Indexed as

CarnivoraTigersAnimalsConservation of Natural ResourcesEcosystemHumansPopulation DensityCarnivore densityCarrying capacityPrey densityScalingTiger

Identifiers

PMID38025689
PMCPMC10676078
OpenAlexW4388906530

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.