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Sökning: (WFRF:(Potts K)) srt2:(2020-2024) > Reliably predicting...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00005678naa a2200601 4500
001oai:lup.lub.lu.se:a8361172-f040-43b8-a80e-dcc88c272d43
003SwePub
008201102s2020 | |||||||||||000 ||eng|
0247 a https://lup.lub.lu.se/record/a8361172-f040-43b8-a80e-dcc88c272d432 URI
0247 a https://doi.org/10.1111/2041-210X.134832 DOI
040 a (SwePub)lu
041 a engb eng
042 9 SwePub
072 7a art2 swepub-publicationtype
072 7a ref2 swepub-contenttype
1001 a Gardner, Emmau University of Reading4 aut
2451 0a Reliably predicting pollinator abundance : Challenges of calibrating process-based ecological models
264 1c 2020
300 a 17 s.
520 a Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores. Our results highlight a key universal challenge of calibrating spatially explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that are often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data.
650 7a NATURVETENSKAPx Biologix Ekologi0 (SwePub)106112 hsv//swe
650 7a NATURAL SCIENCESx Biological Sciencesx Ecology0 (SwePub)106112 hsv//eng
650 7a LANTBRUKSVETENSKAPERx Annan lantbruksvetenskapx Miljö- och naturvårdsvetenskap0 (SwePub)405042 hsv//swe
650 7a AGRICULTURAL SCIENCESx Other Agricultural Sciencesx Environmental Sciences related to Agriculture and Land-use0 (SwePub)405042 hsv//eng
653 a calibration
653 a credibility assessment
653 a Delphi panels
653 a ecosystem services
653 a pollinators
653 a process-based models
653 a validation
7001 a Breeze, Tom D.u University of Reading4 aut
7001 a Clough, Yannu Lund University,Lunds universitet,BECC: Biodiversity and Ecosystem services in a Changing Climate,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Centre for Environmental and Climate Science (CEC),Faculty of Science4 aut0 (Swepub:lu)cec-ycu
7001 a Smith, Henrik G.u Lund University,Lunds universitet,BECC: Biodiversity and Ecosystem services in a Changing Climate,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Centre for Environmental and Climate Science (CEC),Faculty of Science4 aut0 (Swepub:lu)ekol-hsm
7001 a Baldock, Katherine C.R.u University of Bristol,Northumbria University4 aut
7001 a Campbell, Alistairu Brazilian Agricultural Research Corporation4 aut
7001 a Garratt, Michael P.D.u University of Reading4 aut
7001 a Gillespie, Mark A.K.u Western Norway University of Applied Sciences,University of Leeds4 aut
7001 a Kunin, William E.u University of Leeds4 aut
7001 a McKerchar, Meganu University of Worcester4 aut
7001 a Memmott, Janeu University of Bristol4 aut
7001 a Potts, Simon G.u University of Reading4 aut
7001 a Senapathi, Deepau University of Reading4 aut
7001 a Stone, Graham N.u University of Edinburgh4 aut
7001 a Wäckers, Felixu Lancaster University4 aut
7001 a Westbury, Duncan B.u University of Worcester4 aut
7001 a Wilby, Andrewu Lancaster University4 aut
7001 a Oliver, Tom H.u University of Reading4 aut
7102 a University of Readingb BECC: Biodiversity and Ecosystem services in a Changing Climate4 org
7730 t Methods in Ecology and Evolutiong 11:12, s. 1673-1689q 11:12<1673-1689x 2041-210X
8564 u http://dx.doi.org/10.1111/2041-210X.13483x freey FULLTEXT
8564 8u https://lup.lub.lu.se/record/a8361172-f040-43b8-a80e-dcc88c272d43
8564 8u https://doi.org/10.1111/2041-210X.13483

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