Climate change likely to reduce orchid bee abundance even in climatic suitable sites

© 2018 John Wiley & Sons Ltd.

Bibliographische Detailangaben
Veröffentlicht in:Global change biology. - 1999. - 24(2018), 6 vom: 02. Juni, Seite 2272-2283
1. Verfasser: Faleiro, Frederico Valtuille (VerfasserIn)
Weitere Verfasser: Nemésio, André, Loyola, Rafael
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:Global change biology
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Atlantic rainforest Euglossini biodiversity loss pollinators species distribution models
LEADER 01000naa a22002652 4500
001 NLM281559724
003 DE-627
005 20231225031918.0
007 cr uuu---uuuuu
008 231225s2018 xx |||||o 00| ||eng c
024 7 |a 10.1111/gcb.14112  |2 doi 
028 5 2 |a pubmed24n0938.xml 
035 |a (DE-627)NLM281559724 
035 |a (NLM)29498787 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Faleiro, Frederico Valtuille  |e verfasserin  |4 aut 
245 1 0 |a Climate change likely to reduce orchid bee abundance even in climatic suitable sites 
264 1 |c 2018 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 12.12.2018 
500 |a Date Revised 12.12.2018 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a © 2018 John Wiley & Sons Ltd. 
520 |a Studies have tested whether model predictions based on species' occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence-absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence-absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability-abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Atlantic rainforest 
650 4 |a Euglossini 
650 4 |a biodiversity loss 
650 4 |a pollinators 
650 4 |a species distribution models 
700 1 |a Nemésio, André  |e verfasserin  |4 aut 
700 1 |a Loyola, Rafael  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Global change biology  |d 1999  |g 24(2018), 6 vom: 02. Juni, Seite 2272-2283  |w (DE-627)NLM098239996  |x 1365-2486  |7 nnns 
773 1 8 |g volume:24  |g year:2018  |g number:6  |g day:02  |g month:06  |g pages:2272-2283 
856 4 0 |u http://dx.doi.org/10.1111/gcb.14112  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 24  |j 2018  |e 6  |b 02  |c 06  |h 2272-2283