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A systematic review of the statistical scope used in the study of pollinator facilitation
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STATISTICAL TESTS USED IN PLANT-POLLINATOR FACILITATION STUDIES Ally Ruttan
description
3 Fig/fig wasp, yucca/yucca moth, orchid/orchid bee: co-evolutionary relationship, Reciprocal mutualism (Eltz et al. 2011) 4 Indirect facilitative pathway b/w plants and pollinators = neighbour-mediated pollinator facil.(magnet hypothesis) (Laverty 1992). Competition b/w plants for resources incl. pollinators. Diverse floral displays = net increase in pollinator frequency/diversity (Wirth et al. 2011) 5 Data includes observational counts/abundance data, est. of pollen lim., seed/fruit set, visitation rates & diversity measures. Would benefit highly from synthesis to determine most effective methodologies for dealing with this data 6 Way of understanding the level of complexity of stats approaches used in pollinator facil. lit. and allows for ID of stats methods that have potential for increased citations 7 Thomson Reuters web of science used to conduct search using the term “plant AND pollinat* AND facilitate*”. Refined by research areas: environmental sciences, ecology, plant sciences. 8 Studies without primary data (notes, reviews, meta-analyses) and studies on non-pollinating insects were excluded 10 Fig1. Multiple polynomial regressions of the change in the use of tests over time. (n=245, ANOVA: R2=0.46308, mean (SD/SE): R2=0.32680, regression/correlation: R2=0.50553, t-test: R2=0.16791, mixed effects model: R2=0.41467, chi-square R2=0.34096, re-sampling: R2=0.22495, ordination: R2=0.38394, none: R2=0.15419, other: R2=0.16871). P facilitation primarily used only mean/SE/SD. ANOVAs used most frequently from 2000-14. Regression= steepest increase in use and along w/ means (SD/SE) were second most highly used test after ANOVAs. Mixed effects models, ordinations &chi-square tests also highly cited. Studies that used no/other statistics were low frequency. 11 Fig2. Breakdown of the tests used in sub-disciplines of pollinator facilitation: neighbour-effect, pollination biology, invasion biology, agriculture and other (herbivory, behaviour, trophic cascades and evolution). A) Total frequency of studies that utilized these statistical test groups in each sub-discipline (N=245). B) Relative proportion of studies that utilized these statistical test groups in each sub-discipline. The number of studies in each category (n) is shown (N=245). 12 Fig3. Frequency and average number of total citations for each group of statistical tests used in pollinator facilitation studies (n=95). Tests are grouped according to having A) relatively high citations compared to publication frequency, B) relatively equal citations compared to publication frequency, C) Relatively low citations cf. to publication frequency. 13 Fig4. A linear regression for the relationship between the diversity of statistical tests used (the number of unique statistical tests used per study) and the average citations per year in the discipline of pollinator facilitation (n=95, R= 0.11517) 14 ANOVAs, regressions/correlations and ordinations increasing quickly. St
Transcript of A systematic review of the statistical scope used in the study of pollinator facilitation
STATISTICAL TESTS USED IN
PLANT-POLLINATOR
FACILITATION STUDIES
Ally Ruttan
Introduction
Many plants rely on insects for pollination and co-evolution is common
Facilitation between plants and pollinators = shared access to resources
Introduction – obligate pollinator
mutualisms
Rely exclusively on each other for
pollination/reproduction
E.g. fig & fig wasp, yucca & yucca moth, orchids &
orchid bees
Introduction – pollinator
facilitation
+ =
Target Co-flowering
speciesPollinators
+ =
Purpose
Data in this field takes on many forms…
This review examines the statistical scope of the
literature to date on the study of pollinator
facilitation.
Objectives
1) Determine the change in use of statistical tests over time
2) Compare use of statistical tests for various sub-disciplines of pollinator facilitation
3) Compare publication frequency and average citations per publication for different test groups
4) Contrast the relationship between diversity of statistical tests and citation rate
Search technique
plant AND pollinat* AND
facilitat*
Refined by: Environmental science, ecology,
plant science, English-only
496
Search technique
plant AND pollinat* AND
facilitat*
Refined by: Environmental science, ecology,
plant science, English-only
95
How often do we use stats?
Yes97%
No3%
Test usage over time…
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ANOVA mean (SD/SE) regression/Correlation t-test
mixed effects model chi-square re-sampling ordination
none other
Test usage by topic/discipline
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neighbour-effect pollination biology invasion biology agriculture other
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Publications vs. citations by test
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Publications Average citations
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Test diversity vs. citation rate
R² = 0.1152
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Key Results
ANOVAs, means, and regressions/correlations
used most frequently
Neighbour-effect and invasion biology studies
used more extensive tests compared to pollination
biology
Ordinations, re-sampling techniques and t-tests
received the most citations
Novel pathways…
Effect size estimates rarely used;
useful for teasing apart facilitative vs.
competitive effects
Network analyses to highlight
important pathways and
unanticipated interactions
Rarefaction curves/ordinations should be implemented
But…
Must still take experimental design into account
Not all tests can be applied in every scenario
Test assumptions must be met
