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Research article - Peer-reviewed, 2017

Evaluating citizen science data for forecasting species responses to national forest management

Mair, Louise; Harrison, Philip J; Jönsson, Mari; Löbel, Swantje; Nordén, Jenni; Siitonen, Juha; Lämås, Tomas; Lundström, Anders; Snäll, Tord;

Abstract

The extensive spatial and temporal coverage of many citizen science datasets (CSD) makes them appealing for use in species distribution modeling and forecasting. However, a frequent limitation is the inability to validate results. Here, we aim to assess the reliability of CSD for forecasting species occurrence in response to national forest management projections (representing 160,366km2) by comparison against forecasts from a model based on systematically collected colonization-extinction data. We fitted species distribution models using citizen science observations of an old-forest indicator fungus Phellinus ferrugineofuscus. We applied five modeling approaches (generalized linear model, Poisson process model, Bayesian occupancy model, and two MaxEnt models). Models were used to forecast changes in occurrence in response to national forest management for 2020-2110. Forecasts of species occurrence from models based on CSD were congruent with forecasts made using the colonization-extinction model based on systematically collected data, although different modeling methods indicated different levels of change. All models projected increased occurrence in set-aside forest from 2020 to 2110: the projected increase varied between 125% and 195% among models based on CSD, in comparison with an increase of 129% according to the colonization-extinction model. All but one model based on CSD projected a decline in production forest, which varied between 11% and 49%, compared to a decline of 41% using the colonization-extinction model. All models thus highlighted the importance of protected old forest for P.ferrugineofuscus persistence. We conclude that models based on CSD can reproduce forecasts from models based on systematically collected colonization-extinction data and so lead to the same forest management conclusions. Our results show that the use of a suite of models allows CSD to be reliably applied to land management and conservation decision making, demonstrating that widely available CSD can be a valuable forecasting resource.

Keywords

deadwood-dependent fungi; forestry; global biodiversity information facility; habitat change; land use change; opportunistic data; volunteer recording

Published in

Ecology and Evolution

2017, volume: 7, number: 1, pages: 368-378

Authors' information

Mair, Louise
Swedish University of Agricultural Sciences, Swedish Species Information Centre
Harrison, Philip J
Swedish University of Agricultural Sciences, Swedish Species Information Centre
Swedish University of Agricultural Sciences, Swedish Species Information Centre
Löbel, Swantje
Swedish University of Agricultural Sciences, Swedish Species Information Centre
Löbel, Swantje
Braunschweig University of Technology
Nordén, Jenni
University of Oslo (UiO)
Siitonen, Juha
Natural Resources Institute Finland (LUKE)
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Swedish Species Information Centre

Associated SLU-program

Forest
SLU Network Plant Protection

UKÄ Subject classification

Forest Science

Publication Identifiers

DOI: https://doi.org/10.1002/ece3.2601

URI (permanent link to this page)

https://res.slu.se/id/publ/78391