Iriondo scape 2016
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Transcript of Iriondo scape 2016
Disintegrating a network: within-season
dynamics of plant-flower visitor interactions
Javier Morente, Carlos Lara-Romero, Concepción Ornosa & José M. Iriondo
30th SCAPE meetingOctober 13-16, 2016, Abisko
Introduction
Plant-flower visitor networks:
Data comprising the whole flowering season
Whole view with a single set of descriptors
Burkle et al. (2013) Science
Introduction
Temporal integration provides a synthetic but limitedview:
Cannot assess within-season structural dynamics(Rasmussen et. al. 2013)
Does not inform if recorded interactions concur in time (Olesen et al. 2008)
Competing or complementary interactions?
Does not inform about missing interactions (Olesen et al. 2011)
Lack of temporal synchrony or morphologicalincompatibilities?
Temporal integration constrains functional assessmentsof the network
Aim
To explore within-season temporal dynamics of plant-
flower visitor interactions.
To assess the effect of phenology on cumulative
network structure
Study system
Mediterranean alpine grasslands
Short summer vegetative period between snow seasons
aggravated by mid-summer droughts.
Baseline reference case to study the temporal dynamics
of plant-flower visitor networks.
Hypotheses
Flowering period in Mediterranean alpine grassland
would be short and the flowering peak of most plant
species would coincide within a short period of time.
Consequently, most interactions of the network would
simultaneously be overlapping in this period
Hypotheses
Temporal replacement of species would be
constrained
The short vegetative period would prevent the
formation of modules of plants and flower visitors
associated to temporal variation in the interactions.
Methods
Study sites
Mediterranean alpine pastures of Sierra de Guadarrama
(Central Spain).
Two mountain peaks: Nevero and Peñalara (>2100m a.s.l.)
Pico del Nevero
Pico Peñalara
Methods
Experimental design
Two 60x100m plots in each mountain
Contacts recorded through walks along line transects
13 June – 28 July: 10-11 censuses per plot
160 hours per site (two teams)
100m
60m
Methods
Cumulativenetwork
Early stage subnetwork
Late stage subnetwork
Mid stage subnetwork
Dynamic perspective of the network
Methods
Data analysis
Three time-aggregated subnetworks
Beta diversity analysis (Baselga, 2010, 2012) for species
activity (plants and flower visitors in separate analysis)
Dissimilarity of interactions (Poisot 2012)
Cumulative quantitative bipartite networks for each
site
Modularity analysis: QuaBiMo (Dormann and Strauss,
2014)
Assessment of activity of each module through time
Cumulative network and temporal
subnetworks
Species richness, number of interactions and total number of interactions obtained in Peñalara (PEN) andNevero (NEV) study sites.
PEN NEV
Metrics Early Mid Late Cumulative Early Mid Late Cumulative
Plant species 11 9 12 17 7 12 11 16
Animal species 65 46 59 103 65 56 66 115
Number of Interactions 138 115 148 315 121 106 160 340
Number of visits 1082 1017 1179 3278 707 616 938 2261
Turnover beta diversity was greater than
expected both in plants and flower visitors
Within-season beta-diversity of plant and flower visitor assemblages at Nevero and Peñalara study sites (Early, Mid and Late stage subnetworks compared).
βSOR βSIM βSNE Z βSOR Z βSIM Z βSNE
Plant species assemblages
Nevero 0.67* 0.39* 0.28* 2.11 2.19 -2.21
Peñalara 0.64* 0.35* 0.29 2.24 1.98 -1.75
Flower visitors assemblages
Nevero 0.73* 0.55* 0.18* 7.47 6.96 -6.39
Peñalara 0.71* 0.48* 0.23* 6.44 5.82 -5.26
ΒSOR: overall beta diversity, βSIM: turnover beta diversity, βNES: nestedness beta diversity. Z prefix
indicates beta diversity values standardized by a null model. *Value departs from null expectations
(Z greater than 1.96 or less than -1.96, α= 0.05)
Shared interactions were greater than
expected through fidelity of interactions
when same species were present
Within-season variation of species interactions at Nevero and Peñalara study sites (Early vs.Mid, Mid vs. Late).
IS INT INP Z IS Z INT Z INP
Early vs. Mid
Nevero 14* 154 48 2.42 -1.36 -1.28
Peñalara 37* 112 60* 3.42 -0.91 -3.60
Mid vs Late
Nevero 33* 123 78* 2.22 0.83 -2.91
Peñalara 39* 94 81* 2.49 0.79 -2.90
IS: number of shared interactions at different times, INT: number of non-shared interactions due to
species turnover, INP: number of non-shared interactions due to changes in species preferences (both
species present in the two sub-networks compared). The Z prefix indicates number of interactions
standardized by a null model. *Value departs from null expectations (Z greater than 1.96 or less than -
1.96, α= 0.05)
Significant modules in cumulative network
Distribution of plants and number of flower-visitors of the modules identified for NEV and PEN study sites.
NEV PEN
Modules Modules
NEV 1 NEV 2 NEV 3 NEV 4 NEV 5 PEN 1 PEN 2 PEN 3
Plant species assemblages
armcae bisint sedbre Solvir linsax genlut gagnev eupwil
adehis jascri sedcan - lentod jascri hiesp senpyr
leualp silcil - - pinvah jurhum leualp solvir
jurhum hiesp - - - cytoro bisint silcil
cytoro - - - - thypra ransp adehis
senpyr - - - - - armcae sedbre
Flower-visitors assemblages
Bombus 1 2 - - - 2 - -
Bees 9 5 - - 2 6 6 2
Small bees 3 3 - 1 2 2 3 -
Wasp 2 - 2 1 - 2 - 3
Hoverflies 5 1 5 3 - 1 3 9
Bee flies 1 - 3 - - 2 - -
Big flies 5 - - 2 - 4 - 5
Flies 8 1 - - 1 1 2 3
Butterflies 17 5 1 - - 19 3 4
Beetles 9 - - 2 - - 9 3
Others 11 2 - - - 1 3 5
Conclusions on hypotheses
The flowering peak of most plant species would coincide within a short period of time. Consequently, most interactions of the network would simultaneously be overlapping in this period.
Temporal replacement of species would be constrained
The short vegetative period would prevent the formation of modules of plants and flower visitors associated to temporal variation in the interactions.
Phenology seems to play an important role in shaping the modular structure of cumulative networks.