Home About Browse Search
Svenska


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

Mair, Louise and Harrison, Philip J and Jönsson, Mari and Löbel, Swantje and Nordén, Jenni and Siitonen, Juha and Lämås, Tomas and Lundström, Anders and Snäll, Tord (2017). Evaluating citizen science data for forecasting species responses to national forest management. Ecology and evolution. 7:1, 368-378
[Journal article]

[img]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

894kB

Official URL: http://dx.doi.org/10.1002/ece3.2601

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.

Authors/Creators:Mair, Louise and Harrison, Philip J and Jönsson, Mari and Löbel, Swantje and Nordén, Jenni and Siitonen, Juha and Lämås, Tomas and Lundström, Anders and Snäll, Tord
Title:Evaluating citizen science data for forecasting species responses to national forest management
Series/Journal:Ecology and evolution (2045-7758)
Year of publishing :2017
Volume:7
Number:1
Page range:368-378
Number of Pages:11
Publisher:Wiley
Associated Programs and Other Stakeholders:SLU - Environmental assessment > Programme Forest
ISSN:2045-7758
Language:English
Publication Type:Journal article
Refereed:Yes
Article category:Scientific peer reviewed
Version:Published version
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Agrovoc terms:forestry, citizen participation, biodiversity
Keywords:deadwood-dependent fungi, forestry, global biodiversity information facility, habitat change, land use change, opportunistic data, volunteer recording
URN:NBN:urn:nbn:se:slu:epsilon-e-4098
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-4098
Additional ID:
Type of IDID
Web of Science (WoS)000392069500030
DOI10.1002/ece3.2601
ID Code:14221
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Swedish Species Information Centre
(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:11 Apr 2017 07:03
Metadata Last Modified:11 Apr 2017 07:03

Repository Staff Only: item control page

Downloads

Downloads per year (since September 2012)

View more statistics

Downloads
Hits