10.5061/DRYAD.BCC2FQZ9P
Jones, Harrison
0000-0003-1402-4778
University of Florida
Robinson, Scott
Florida Museum of Natural History
Data for: Fragmentation and disturbance drive montane mixed-flock species
roles and interaction strength
Dryad
dataset
2020
FOS: Biological sciences
tropical montane forest
nuclear species
Modularity
Animal Behavior Society
https://ror.org/031nh9x49
Tinker Foundation
https://ror.org/01sv5w039
2020-09-16T00:00:00Z
2020-09-16T00:00:00Z
en
119071 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Mixed-species flocks are a key facilitative interaction for tropical
birds. Forest fragmentation leads to species loss and spatial turnover in
these flocks, yet it is unknown how these changes to composition influence
within-flock species interactions. We used network analysis to
characterize flocking interactions along a fragment-size gradient in the
Colombian Western Andes. We asked (1) how patch size, edge density, and
vegetation structure explained network measures indicative of flock
cohesion, (2) whether changes were driven by flocking species turnover or
changes to the frequency of species co-occurrence, and (3) whether nuclear
species, those that maintain flock stability and cohesion, changed in
importance across the gradient. We constructed weighted social networks
from flock compositions observed on 500-meter transects, and then
calculated global network measures and the centrality of six nuclear
species. Patch size and edge density did not correlate with interspecific
co-occurrence patterns, but interaction strength increased with canopy
height. Flocks contained numerous, weak interactions and there were no
flock sub-types, suggesting flock composition was dynamic and
unstructured. Several redundant nuclear species were present and varied in
importance based on ecological conditions. A chlorospingus (Passerellidae)
was most central in old-growth forest, whereas several tanager
(Thraupidae) species became more central in smaller fragments and
disturbed forest. When partitioning network dissimilarity, we found that
66% of dissimilarity resulted from species turnover, whereas only 34%
resulted from changes to species co-occurrence. This finding suggests that
coherence of flocking behavior itself is maintained even as extensive
species turnover occurs from continuous forest to small fragments.
Study system and sites We conducted field work in subtropical humid
montane forests located in the municipality of El Cairo, Valle del Cauca
department in Colombia. The study region is in the Serranía de los
Paraguas mountain range, part of the Western Andes, and a center of avian
threatened species diversity and endemism in Colombia (Ocampo-Peñuela and
Pimm 2014). Andean forests in Colombia are highly fragmented, with only
30% of original forest cover remaining (Etter et al. 2006). Within our
focal landscape, we selected eight fragments representing a gradient in
patch sizes (range 10 to 170 ha). We stratified forest fragments into
large (≥ 100 ha), medium (30-50 ha), and small (≤ 20 ha) size categories
and selected a minimum of two replicates of each (Table 1, Jones and
Robinson 2020). These sites were in the same altitudinal belt (1900-2200
masl) and matrix type (cattle pasture). Fragments were separated by ≥ 100
meters to minimize cross-patch movement of birds, and all transects in
different patches were separated by at least 250 m. We also worked in a
non-fragmented reference site (Reserva Natural Comunitária Cerro El
Inglés) connected to thousands of hectares of continuous forest. We only
selected fragments with primary forest, though vegetation structure and
canopy height varied substantially within and between patches based on
varying intensities of selective logging. To capture these within-patch
effects of disturbance, we therefore established 500-meter transects
through forest interior (N = 14 total transects; Table 1) as our
replicate. Where fragment area allowed, we placed one transect in a more
disturbed (logged) area and another in a relatively undisturbed site
within each fragment. Fragments were privately-owned forests, and we
collaborated with a local NGO (Serraniagua; http://www.serraniagua.org) to
ensure access. Mixed-species flocks in Colombian sub-montane forests are
large and diverse: they contain ~100 participating species and up to 50
individuals per flock (Colorado Zuluaga and Rodewald 2015; Jones and
Robinson, 2020). Transect surveys for mixed-species flocks We adapted
transect surveys for mixed-species flocks from Goodale et al. (2014),
which were conducted within forest fragments from June-August 2017 (boreal
migrants absent) and January-March 2018 (boreal migrants present). Both
sampling periods correspond to a dry season in the Western Andes, which
has a bimodal two dry, two wet seasonality. For each sampling period, we
sampled each transect for 2.5 consecutive field days by continuously
walking back and forth; we alternated visits to continuous forest, large
fragments, and small fragments to avoid a temporal bias in our sampling.
Transects were walked slowly by 2-3 observers familiar with all bird
species by sight and sound (HHJ present for all surveys), with visits
distributed across the morning (7:30-11:30) and evening (15:00-17:30)
hours when flocking behavior is most common in Andean forests. When a
flock was encountered, we spent up to a maximum of 45 minutes
characterizing it with 10x binoculars. We identified flocking species by
sight and sound, as flock members often called and sang conspicuously
while foraging. At least 5 minutes were spent with each flock, following
it if possible. Because detection of bird species in mixed-species flocks
is imperfect, we considered the flock composition ‘complete’ when we did
not detect new species or individuals over the past 5 minutes of
observation; we only used ‘complete’ flock compositions in our analyses.
Avian taxonomy of flocking species follows Handbook of Birds of the World
Alive (del Hoyo et al. 2020) nomenclature. Calculation of Landscape-level
Variables We obtained landscape-level variables for analyses
using geographic information software (GIS) analysis in ArcGIS (ArcMap
10.3.1; Esri; Redlands, CA). We quantified landscape composition and
configuration by buffering each transect (N = 14) by 1 km. We then
calculated measures of landscape composition and configuration using a
land cover use categorization made by the Corporación Autónoma Regional
del Valle del Cauca, converted to a 25m cell-size raster. To quantify
landscape composition, we calculated percentages of forest land use type
within each 1 km buffer using the ‘isectpolyrst’ tool in Geospatial
Modelling Environment (version 0.7.4.0; Beyer 2015). Following Carrara et
al. (2015), we selected percentage of forest cover as a proxy for patch
size because some of our transects were located in continuous forest with
no patch size measurement. Because the matrix in our landscape consisted
of unforested cattle pasture, we feel that this is a good measure of patch
area, since there was no other forested habitat in the buffer area;
percentage forest was highly correlated with patch area (correlation
coefficient = 0.95). We also measured landscape configuration for each
transect at the 1-kilometer buffer scale using edge density, or length of
all forest edges (in meters) divided by total buffer area (in hectares),
as described by Carrara et al. (2015). We did not include other (e.g. 500
m) buffer scales because composition and configuration measures correlated
heavily with the 1 km scale. Vegetation measurements and principal
component analysis To quantify disturbance to local vegetation
at each site, we measured vegetation structure and density along each
transect used to sample for flocks. Vegetation measurements were made
between June and August 2017 and based on our field observations there
appeared to be minimal variation between seasons. We used the methodology
of James and Shugart (1970) following the modifications made by Stratford
and Stouffer (2013), and further modified it to be used with belt
transects. The sampling consisted of two components for each transect: (1)
the quantification of canopy cover, ground cover, canopy height, and
vertical structure of vegetation using point sampling spaced every 10
meters on the transect and (2) the quantification of shrub, vine, fern,
palm, and tree fern and tree density using 3-meter-wide belt transect
sampling. Because transects ran along trails, we measured vegetation at
least three meters from the trail edge on a randomly selected side for
each 100-meter transect segment. For the point sampling, we
measured eight variables at 10-m intervals, for 50 points per transect. As
a measure of vertical vegetation structure along the transect, we noted
the presence or absence of live vegetation at five heights: <0.5 m,
>0.5–3 m, >3–10 m, >10–20 m, and >20 m. Above
3 meters, we used a rangefinder to determine heights and sighted through a
tube with crosshairs while straddling the point. The canopy height at each
point was measured using a laser rangefinder (Raider 600 Digital Laser
Rangefinder, Redfield Inc. Beaverton, OR) pointed at the highest foliage.
Canopy and ground cover were calculated to the nearest 1/8th of the field
of view by sighting through a vertical canopy densiometer (GRS
Densiometer, Geographic Resource Solutions, Arcata, CA). For each
transect, we averaged values for canopy height, canopy cover, and ground
cover, and calculated the proportion of points at which vegetation was
present for each height category. For the belt transect sampling, we
surveyed vegetation along the same transects and calculated densities for
each 100-meter transect interval. We counted all shrubs, vines, ferns,
tree ferns, and palms encountered on 1.5 meters to either side. Secondly,
we counted all trees (woody vegetation > 2 m in height) within 1.5
meters of the transect and measured their diameter at breast height (dbh).
Trees were later categorized into six dbh size classes for analysis: 1-7
cm, 8-15 cm, 16-23 cm, 24-30 cm, 31-50 cm, and > 50 cm. We
additionally recorded the largest tree as a measure of degree of logging
in each fragment. We retained four measures of local
vegetation for our analyses. The average canopy height and canopy cover
for each transect were directly used for the analyses. Canopy height was
strongly correlated with degree of vertical vegetation complexity (i.e.
presence of foliage in different height categories), as calculated using
the Shannon diversity index on the proportion of points with vegetation
present in each of the five height bands for each transect (correlation
coefficient = 0.89). We also used principal component analysis (PCA)
ordinations of understory vegetation density and density of large-diameter
trees, taken from Jones and Robinson (2020), calculated for each transect.
We used the first PC axis from each ordination; more negative values of
the understory vegetation PC axis indicate higher densities of understory
shrubs, vines, palms, ferns, and tree ferns while more positive values of
the tree-size PC axis indicate greater densities of large-diameter trees
(e.g. 20-50 cm DBH) and therefore reduced selective logging. Construction,
measurement, and analysis of social networks We characterized
the flocking interactions of the bird community on each 500-meter transect
by assembling a social network (Croft et al. 2008). Species move and
forage in close association in mixed-species flocks, so we considered two
species observed in the same flock to be interacting ecologically (the
‘gambit of the group’ approach; Whitehead and Dufault 1999). We therefore
defined each node as an individual species and each edge as a
co-occurrence of two species in a flock. All statistical analyses were
performed in R (version 3.5.1; R Core Team 2020). We used
presence-absence, flock-by-species adjacency matrices derived from field
observations to create social networks using the get_network function of
the asnipe package (Farine 2013). We constructed one social network for
each transect in each sampling period using all flock compositions
observed on the transect during that sampling period (range = 7-26 flock
compositions per network). However, we did not construct a network for one
transect during the boreal winter due to insufficient sample size of flock
compositions (N = 27 networks). Because detectability of birds in flocks
is high, and associations were likely rarely missed, we used the simple
ratio index (SRI), an undirected, weighted measure of association, to
calculate an association index for each species pair in the flocking
network (Cairns and Schwager 1987). For each network, we
calculated five global network measures relevant to our questions of
interest. We quantified the frequency and strength of species
co-occurrences in flocking associations using mean normalized degree, mean
weighted degree (hereafter strength), and skewness of strength values for
each network. Mean normalized degree represents the average of the number
of edges for each node, divided by the total number of nodes minus one.
This measure provides an index of network connectedness, the average
number of co-occurrence interactions for participating species
standardized for network size. Network strength is calculated as the
average of all sums of weighted edge lengths for each node in the network,
which represents a measure of the consistency of species co-occurrences
across flock surveys (compositions). Skewness of strength measures the
asymmetry in the distribution of node strength measurements; positive
values of skewness indicate that node strength is skewed right (a greater
abundance of strength values below the mean), and values approaching zero
indicate increasing proportions of high strength nodes (i.e., an
approximately unimodal distribution). Mean normalized degree was
calculated using the degree function of the igraph package (Csárdi 2019),
strength was calculated using the strength function of the igraph package,
and skewness was calculated using the skewness function of the moments
package (Komsta and Novomestky 2015). Following Mokross et al. (2014), we
also used the global clustering coefficient, calculated using the
transitivity function of the igraph package, as a measure of flock
cohesiveness. Lastly, we quantified the extent to which flocks were
divided into sub-types versus homogenous in composition by calculating the
modularity of each flocking network. First, we assigned each node
(species) to a flocking sub-type using the eigenvector modularity method
(Newman 2006) applied through the cluster_leading_eigen function of the
igraph package. We then calculated the modularity of this optimal solution
using the modularity function of the igraph package. In order
to understand how nuclear species importance changed across our patch size
gradient, we also calculated node-based measures of centrality for six a
priori-defined nuclear species. Putative nuclear species were identified
based on field observations and descriptions of Andean flocking systems in
the literature. We chose Chlorospingus canigularis, Tangara labradorides,
T. aurulenta, and Anisognathus somptuosus because they are gregarious
species that often join flocks as social groups, a trait often associated
with nuclear species (Goodale and Beauchamp 2010), while Myioborus
miniatus and Pachysylvia semibrunnea are commonly flocking species that
frequently call and sing in the flock, possibly contributing to cohesion.
We quantified ‘nuclearity’ as the normalized betweenness centrality of a
species in the network, or the number of shortest paths between nodes
passing through the node of interest, standardized by the size of the
network. We selected betweenness centrality because this measure accounts
for not only species with many co-occurrences, but also the ability to
connect flock sub-types (network modules), which could be an important
“information broker” role (Croft et al. 2008). More broadly, centrality is
an appropriate quantification of the importance of the nuclear role
because the number and strength of species co-occurrences in flocking
networks covary (Srinivasan et al. 2010), and the structural importance of
species in flocking social networks is correlated with their functional
importance in the flock itself (Sridhar et al. 2013). On one transect, C.
canigularis was replaced by C. semifuscus, which plays a similar nuclear
role in flocks (Bohórquez 2003) and is ecologically similar (Isler and
Isler 1999). We therefore used the centrality value for C. semifuscus on
that transect. Centrality was calculated using the betweenness function of
the igraph package.
The following dataset contains three data files: one CSV file containing
the presence-absence species composition of each mixed-species flock used
to construct 27 social networks for the analysis, one CSV file containing
the calculated network measures and associated environmental covariates,
and one Word file containing the descriptions of the variables used in the
second CSV.