Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago

This research aims to provide guidelines using probabilistic methods to understand better the dominant characteristics of the 824 under-pressure wetlands on 75 islands within Greece and to inform future conservation efforts. Identifying the characteristics and types of anthropogenic pressures is cru...

Full description

Saved in:
Bibliographic Details
Main Authors: Cleo M. Gaganis, Andreas Y. Troumbis
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Diversity
Subjects:
Online Access:https://www.mdpi.com/1424-2818/17/1/54
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832588605148626944
author Cleo M. Gaganis
Andreas Y. Troumbis
author_facet Cleo M. Gaganis
Andreas Y. Troumbis
author_sort Cleo M. Gaganis
collection DOAJ
description This research aims to provide guidelines using probabilistic methods to understand better the dominant characteristics of the 824 under-pressure wetlands on 75 islands within Greece and to inform future conservation efforts. Identifying the characteristics and types of anthropogenic pressures is crucial for developing effective conservation strategies. The study employs power-law modeling to validate the natural size distribution of wetlands, naïve Bayesian inference to model human impacts, and the epsilon statistic to assess wetland sensitivity to specific pressures, addressing potential sampling biases. Power-law modeling reveals a natural heavy-tailed distribution of wetland sizes, highlighting the ecological significance of larger, rarer systems. Naïve Bayesian inference indicates that agriculture and transportation are the predominant pressures affecting natural coastal wetlands. The epsilon statistic further differentiates wetland sensitivity, identifying estuaries, lagoons, and marshes as particularly vulnerable. By profiling the most vulnerable wetlands using these methods, the research provides a framework for assessing anthropogenic impacts and informing targeted conservation and management strategies to protect these vital ecosystems.
format Article
id doaj-art-12fd6f72b82d43e8bf9a79156a41a546
institution Kabale University
issn 1424-2818
language English
publishDate 2025-01-01
publisher MDPI AG
record_format Article
series Diversity
spelling doaj-art-12fd6f72b82d43e8bf9a79156a41a5462025-01-24T13:29:30ZengMDPI AGDiversity1424-28182025-01-011715410.3390/d17010054Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean ArchipelagoCleo M. Gaganis0Andreas Y. Troumbis1Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81100 Mytilene, Lesvos, GreeceBiodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81100 Mytilene, Lesvos, GreeceThis research aims to provide guidelines using probabilistic methods to understand better the dominant characteristics of the 824 under-pressure wetlands on 75 islands within Greece and to inform future conservation efforts. Identifying the characteristics and types of anthropogenic pressures is crucial for developing effective conservation strategies. The study employs power-law modeling to validate the natural size distribution of wetlands, naïve Bayesian inference to model human impacts, and the epsilon statistic to assess wetland sensitivity to specific pressures, addressing potential sampling biases. Power-law modeling reveals a natural heavy-tailed distribution of wetland sizes, highlighting the ecological significance of larger, rarer systems. Naïve Bayesian inference indicates that agriculture and transportation are the predominant pressures affecting natural coastal wetlands. The epsilon statistic further differentiates wetland sensitivity, identifying estuaries, lagoons, and marshes as particularly vulnerable. By profiling the most vulnerable wetlands using these methods, the research provides a framework for assessing anthropogenic impacts and informing targeted conservation and management strategies to protect these vital ecosystems.https://www.mdpi.com/1424-2818/17/1/54anthropogenic pressureepsilon statisticpower law
spellingShingle Cleo M. Gaganis
Andreas Y. Troumbis
Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
Diversity
anthropogenic pressure
epsilon statistic
power law
title Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
title_full Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
title_fullStr Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
title_full_unstemmed Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
title_short Bayesian Inference of Human-Made Hazards in Networks of Island Wetlands: The Case of the Aegean Archipelago
title_sort bayesian inference of human made hazards in networks of island wetlands the case of the aegean archipelago
topic anthropogenic pressure
epsilon statistic
power law
url https://www.mdpi.com/1424-2818/17/1/54
work_keys_str_mv AT cleomgaganis bayesianinferenceofhumanmadehazardsinnetworksofislandwetlandsthecaseoftheaegeanarchipelago
AT andreasytroumbis bayesianinferenceofhumanmadehazardsinnetworksofislandwetlandsthecaseoftheaegeanarchipelago