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iForest - Biogeosciences and Forestry

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Effect of imperfect detection on the estimation of niche overlap between two forest dormice

Chiara Paniccia (1), Mirko Di Febbraro (1)   , Ludovico Frate (1), Lorenzo Sallustio (2-3), Giovanni Santopuoli (2), Tiziana Altea (4), Mario Posillico (5-6), Marco Marchetti (2), Anna Loy (1)

iForest - Biogeosciences and Forestry, Volume 11, Issue 4, Pages 482-490 (2018)
doi: https://doi.org/10.3832/ifor2738-011
Published: Jul 18, 2018 - Copyright © 2018 SISEF

Research Articles


Quantification of niche overlap represents an important topic in several aspects of ecology and conservation biology, although it could be potentially affected by imperfect detection, i.e., failure to detect a species at occupied sites. We investigate the effect of imperfect detection on niche overlap quantification in two arboreal rodents, the edible dormouse (Glis glis) and the hazel dormouse (Muscardinus avellanarius). For both species, we used Generalized Linear Mixed Models (GLMM) to estimate the occurrence probability and Occupancy Models (OM) to calculate occurrence and detection probabilities. By comparing these predictions through niche equivalency and similarity tests, we first hypothesised that methods correcting for imperfect detection (OM) provide a more reliable estimate of niche overlap than traditional presence/ absence methods (GLMM). Furthermore, we hypothesised that GLMM mainly estimate species detectability rather than actual occurrence, and that a low number of sampling replicates provokes an underestimation of species niche by GLMM. Our results highlighted that GLMM-based niche overlap yielded significant outcomes only for the equivalency test, while OM-based niche overlap reported significant outcomes for both niche equivalency and similarity tests. Moreover, GLMM occurrence probabilities and OM detectabilities were not statistically different. Lastly, GLMM predictions based on single sampling replicates were statistically different from the average occurrence probability predicted by GLMM over all replicates. We emphasized how accounting for imperfect detection can improve the statistical significance and interpretability of niche overlap estimates based on occurrence data. Under a habitat management perspective, an accurate quantification of niche overlap may provide useful information to assess the effects of different management practices on species occurrence.

  Keywords


Occupancy Models, Generalized Linear Mixed Models, Forest Management, Niche Overlap

Authors’ address

(1)
Chiara Paniccia
Mirko Di Febbraro
Ludovico Frate
Anna Loy
Envix-Lab, Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, c.da Fonte Lappone, I-86090 Pesche, IS (Italy)
(2)
Lorenzo Sallustio
Giovanni Santopuoli
Marco Marchetti
Centro di Ricerca per le Aree Interne e gli Appennini (ArIA), Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, c.da Fonte Lappone, I-86090 Pesche, IS (Italy)
(3)
Lorenzo Sallustio
CREA Research Centre for Forestry and Wood, v.le Santa Margherita 80, I-52100 Arezzo (Italy)
(4)
Tiziana Altea
Coordinamento Territoriale Carabinieri per l’Ambiente, Parco Nazionale “Abruzzo-Lazio-Molise”, Pescasseroli, AQ (Italy)
(5)
Mario Posillico
Reparto Carabinieri Biodiversità Castel di Sangro, Centro Ricerche Ambienti Montani, v. Sangro, 45-67031. Castel di Sangro, AQ (Italy)
(6)
Mario Posillico
Consiglio Nazionale delle Ricerche, Istituto di Biologia Agroambientale e Forestale, v. Salaria km 29.300, I-00015 Montelibretti, RM (Italy)

Corresponding author

 
Mirko Di Febbraro
mirkodifebbraro@gmail.com

Citation

Paniccia C, Di Febbraro M, Frate L, Sallustio L, Santopuoli G, Altea T, Posillico M, Marchetti M, Loy A (2018). Effect of imperfect detection on the estimation of niche overlap between two forest dormice. iForest 11: 482-490. - doi: 10.3832/ifor2738-011

Academic Editor

Massimo Faccoli

Paper history

Received: Jan 24, 2018
Accepted: May 01, 2018

First online: Jul 18, 2018
Publication Date: Aug 31, 2018
Publication Time: 2.60 months

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