An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines

Ema Biscaia; Joana Bernardino; Regina Bispo

doi:10.1007/978-3-031-68949-9_13

An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines

Ema Biscaia^*, Joana Bernardino, Regina Bispo

^*Corresponding author for this work

School of Mathematics and Statistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

One of the objectives of the environmental monitoring programs of transmission power lines is to quantify bird mortality. To account for carcass removal, these programs typically include field experiments which allow to obtain data on the persistence time of the carcass in the field until removal. In this study, we aim to estimate the removal bias correction factor, considering the carcass size, the season, and the location of power line projects, eliminating the need for field trials in every new project. To achieve this goal, we used the Integrated Nested Laplace Approximation (INLA) method combined with the Stochastic Partial Differential Equations (SPDE) approach to model the probability of persistence considering both fixed (carcass size and season) and random (geographic location and project) effects. The results allowed to analyze the variation in space of bird carcass persistence and to create a tool for common users to estimate the removal correction factor for a specific location as a function of the covariates considered, in mainland Portugal. However, further improvement is required as model predictions are still unreliable in large portions of the national territory. We discuss the model limitations and offer directions for future work.

Original language	English
Title of host publication	New Frontiers in Statistics and Data Science
Subtitle of host publication	SPE2023, Guimarães, Portugal, October 11-14
Editors	Lígia Henriques-Rodrigues, Raquel Menezes, Luís Meira Machado, Susana Faria, Miguel de Carvalho
Place of Publication	Cham, Switzerland
Publisher	Springer Nature Switzerland AG
Pages	169-181
Number of pages	13
ISBN (Electronic)	9783031689499
ISBN (Print)	9783031689482
DOIs	https://doi.org/10.1007/978-3-031-68949-9_13
Publication status	Published - 11 Jan 2025
Event	XXVI Congress of the Portuguese Statistical Society - Centro Cultural de Vila Flor, Guimarães, Portugal Duration: 11 Oct 2021 → 14 Oct 2021 https://w3.math.uminho.pt/~web/SPE2023/

Publication series

Name	Springer Proceedings in Mathematics and Statistics
Volume	469
ISSN (Print)	2194-1009
ISSN (Electronic)	2194-1017

Conference

Conference	XXVI Congress of the Portuguese Statistical Society
Abbreviated title	SPE 2023
Country/Territory	Portugal
City	Guimarães
Period	11/10/21 → 14/10/21
Internet address	https://w3.math.uminho.pt/~web/SPE2023/

Keywords

INLA
Persistence probability
Spatial data
Survival analysis

Access to Document

10.1007/978-3-031-68949-9_13

Cite this

Biscaia, E., Bernardino, J., & Bispo, R. (2025). An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines. In L. Henriques-Rodrigues, R. Menezes, L. M. Machado, S. Faria, & M. de Carvalho (Eds.), New Frontiers in Statistics and Data Science: SPE2023, Guimarães, Portugal, October 11-14 (pp. 169-181). (Springer Proceedings in Mathematics and Statistics; Vol. 469). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-68949-9_13

Biscaia, Ema ; Bernardino, Joana ; Bispo, Regina. / An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines. New Frontiers in Statistics and Data Science: SPE2023, Guimarães, Portugal, October 11-14. editor / Lígia Henriques-Rodrigues ; Raquel Menezes ; Luís Meira Machado ; Susana Faria ; Miguel de Carvalho. Cham, Switzerland : Springer Nature Switzerland AG, 2025. pp. 169-181 (Springer Proceedings in Mathematics and Statistics).

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title = "An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines",

abstract = "One of the objectives of the environmental monitoring programs of transmission power lines is to quantify bird mortality. To account for carcass removal, these programs typically include field experiments which allow to obtain data on the persistence time of the carcass in the field until removal. In this study, we aim to estimate the removal bias correction factor, considering the carcass size, the season, and the location of power line projects, eliminating the need for field trials in every new project. To achieve this goal, we used the Integrated Nested Laplace Approximation (INLA) method combined with the Stochastic Partial Differential Equations (SPDE) approach to model the probability of persistence considering both fixed (carcass size and season) and random (geographic location and project) effects. The results allowed to analyze the variation in space of bird carcass persistence and to create a tool for common users to estimate the removal correction factor for a specific location as a function of the covariates considered, in mainland Portugal. However, further improvement is required as model predictions are still unreliable in large portions of the national territory. We discuss the model limitations and offer directions for future work.",

keywords = "INLA, Persistence probability, Spatial data, Survival analysis",

author = "Ema Biscaia and Joana Bernardino and Regina Bispo",

note = "Funding: This work was carried out in the framework of REN Biodiversity Chair, funded by REN—Redes Energ{\'e}ticas Nacionais and Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia (FCT). JB work was co-funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). RB work was funded by national funds through FCT—Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 and UIDP/00297/2020 (Center for Mathematics and Applications).; XXVI Congress of the Portuguese Statistical Society, SPE 2023 ; Conference date: 11-10-2021 Through 14-10-2021",

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Biscaia, E, Bernardino, J & Bispo, R 2025, An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines. in L Henriques-Rodrigues, R Menezes, LM Machado, S Faria & M de Carvalho (eds), New Frontiers in Statistics and Data Science: SPE2023, Guimarães, Portugal, October 11-14. Springer Proceedings in Mathematics and Statistics, vol. 469, Springer Nature Switzerland AG, Cham, Switzerland, pp. 169-181, XXVI Congress of the Portuguese Statistical Society, Guimarães, Portugal, 11/10/21. https://doi.org/10.1007/978-3-031-68949-9_13

An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines. / Biscaia, Ema; Bernardino, Joana; Bispo, Regina.
New Frontiers in Statistics and Data Science: SPE2023, Guimarães, Portugal, October 11-14. ed. / Lígia Henriques-Rodrigues; Raquel Menezes; Luís Meira Machado; Susana Faria; Miguel de Carvalho. Cham, Switzerland: Springer Nature Switzerland AG, 2025. p. 169-181 (Springer Proceedings in Mathematics and Statistics; Vol. 469).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines

AU - Biscaia, Ema

AU - Bernardino, Joana

AU - Bispo, Regina

N1 - Funding: This work was carried out in the framework of REN Biodiversity Chair, funded by REN—Redes Energéticas Nacionais and Fundação para a Ciência e a Tecnologia (FCT). JB work was co-funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). RB work was funded by national funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., under the scope of the projects UIDB/00297/2020 and UIDP/00297/2020 (Center for Mathematics and Applications).

PY - 2025/1/11

Y1 - 2025/1/11

N2 - One of the objectives of the environmental monitoring programs of transmission power lines is to quantify bird mortality. To account for carcass removal, these programs typically include field experiments which allow to obtain data on the persistence time of the carcass in the field until removal. In this study, we aim to estimate the removal bias correction factor, considering the carcass size, the season, and the location of power line projects, eliminating the need for field trials in every new project. To achieve this goal, we used the Integrated Nested Laplace Approximation (INLA) method combined with the Stochastic Partial Differential Equations (SPDE) approach to model the probability of persistence considering both fixed (carcass size and season) and random (geographic location and project) effects. The results allowed to analyze the variation in space of bird carcass persistence and to create a tool for common users to estimate the removal correction factor for a specific location as a function of the covariates considered, in mainland Portugal. However, further improvement is required as model predictions are still unreliable in large portions of the national territory. We discuss the model limitations and offer directions for future work.

AB - One of the objectives of the environmental monitoring programs of transmission power lines is to quantify bird mortality. To account for carcass removal, these programs typically include field experiments which allow to obtain data on the persistence time of the carcass in the field until removal. In this study, we aim to estimate the removal bias correction factor, considering the carcass size, the season, and the location of power line projects, eliminating the need for field trials in every new project. To achieve this goal, we used the Integrated Nested Laplace Approximation (INLA) method combined with the Stochastic Partial Differential Equations (SPDE) approach to model the probability of persistence considering both fixed (carcass size and season) and random (geographic location and project) effects. The results allowed to analyze the variation in space of bird carcass persistence and to create a tool for common users to estimate the removal correction factor for a specific location as a function of the covariates considered, in mainland Portugal. However, further improvement is required as model predictions are still unreliable in large portions of the national territory. We discuss the model limitations and offer directions for future work.

KW - INLA

KW - Persistence probability

KW - Spatial data

KW - Survival analysis

U2 - 10.1007/978-3-031-68949-9_13

DO - 10.1007/978-3-031-68949-9_13

M3 - Conference contribution

AN - SCOPUS:85218152674

SN - 9783031689482

T3 - Springer Proceedings in Mathematics and Statistics

SP - 169

EP - 181

BT - New Frontiers in Statistics and Data Science

A2 - Henriques-Rodrigues, Lígia

A2 - Menezes, Raquel

A2 - Machado, Luís Meira

A2 - Faria, Susana

A2 - de Carvalho, Miguel

PB - Springer Nature Switzerland AG

CY - Cham, Switzerland

T2 - XXVI Congress of the Portuguese Statistical Society

Y2 - 11 October 2021 through 14 October 2021

ER -

Biscaia E, Bernardino J, Bispo R. An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines. In Henriques-Rodrigues L, Menezes R, Machado LM, Faria S, de Carvalho M, editors, New Frontiers in Statistics and Data Science: SPE2023, Guimarães, Portugal, October 11-14. Cham, Switzerland: Springer Nature Switzerland AG. 2025. p. 169-181. (Springer Proceedings in Mathematics and Statistics). doi: 10.1007/978-3-031-68949-9_13

An approach for predicting spatially indexed carcass persistence probability to estimate bird mortality at power lines

Abstract

Publication series

Conference

Keywords

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