10.6086/D18Q3X
Larios, Loralee
0000-0002-9740-8111
University of California, Riverside
Larios, Loralee
University of California, Riverside
Maron, John
University of Montana
Voles mediate functional trait diversity along a resource gradient
Dryad
dataset
2020
bottom-up
context-dependency
Top-down
National Science Foundation
https://ror.org/021nxhr62
1309014
National Science Foundation
https://ror.org/021nxhr62
DEB-1553518
2020-09-09T00:00:00Z
2020-09-09T00:00:00Z
en
74362 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Disentangling the effect of multiple ecological processes on plant trait
composition is complicated by the fact that both top-down and bottom-up
processes may affect similar traits. We examined the interacting role of
resource variation and vole herbivory on functional trait patterns in an
annual California grassland. We manipulated vole herbivory via exclosures
at eight grassland sites along a steep resource gradient and measured
plant composition and functional traits over three years. Plants with
resource acquisitive functional traits were favored at sites with
increasing resources. Vole herbivory influenced community-weighted mean
(CWM) leaf nitrogen (N) and seed mass, suggesting these traits may mediate
plant susceptibility to vole herbivory. After three years, CWM leaf N
increased in the absence of the voles, as did CWM seed mass, although this
increase in CWM seed mass only occurred at higher resource sites. Vole
exclusion at high resources sites also increased the functional diversity
of leaf N and seed mass by the end of the experiment. Overall,
environmental filtering primarily structured the dominant plant trait
strategies, but vole herbivory also influenced the functional diversity of
traits that influence herbivore susceptibility, particularly at resource
rich sites. Thus, habitat filtering and herbivory can operate on different
dimensions of plant functional composition to influence the species and
functional composition of communities.
Study Site. We conducted our experiment in the annual grasslands at the
University of California Sierra Foothill Research Extension Center
(SFREC), located in Browns Valley, California, USA (39º 15' N, 121º
17' W). These communities are dominated by non-native annuals with
low abundances of native species. The most abundant species included Avena
barbata, Elymus caput-medusae, Festuca perennis, Bromus hordeaceus, and
Erodium botrys (nomenclature follows Baldwin et al. 2012). The climate is
Mediterranean with cool wet growing seasons (Sept-May) and hot dry summers
(June-Aug). Growing season rainfall increased over the course of our
study more than doubled from 454mm to 625mm to 978mm for the 2014-2015,
2015-2016, and 2016-2017 growing seasons, respectively. The dominant small
mammal consumer is Microtus californicus, a small meadow vole that prefers
habitat with a standing litter layer (Batzli & Pitelka, 1970;
Ostfeld et al., 1985). Other small mammal species at our study site
predominantly reside in the more heavily cattle grazed pastures (Block
& Morrison, 1990). Therefore, our design below reflects
predominantly the effects of voles. Sites. We conducted our experiment at
eight experimental sites that spanned a steep resource gradient. We
described this gradient (hereafter resource gradient) using a principal
component analysis (PC1 which described 47.6% of the variation in
environmental variables; Supporting Information Appendix S1, Figure S1).
At one end of the gradient were low productivity sites (as characterized
by aboveground primary productivity) with low soil nitrogen (N), but high
micronutrients (i.e., magnesium, sodium, and calcium). At the other end of
the gradient, sites had high productivity and soil N. Experimental
Design. To evaluate the effects of voles on plant trait composition, in
the summer of 2014, we initiated a field experiment where we manipulated
the presence of voles. At each site, we established a set of paired plots
(9x9m), one fenced to exclude small mammals and one unfenced control to
allow small mammal access. The exclosures were constructed of 0.64cm
welded wire dug 60cm into the ground around the perimeter of the plot. The
fence extended about 90cm aboveground and was topped with galvanized sheet
metal with a 20cm face to prevent voles from climbing over the fence.
Within each of the paired plots, we randomly established a set of six 0.5m
x 0.5m subplots to assess the effects of voles on plant trait composition.
We additionally set up an electric fence around the 14m x25m experimental
area at each site to exclude cattle. Plant traits. To examine the
distribution of functional traits in communities we sampled 5-10
individuals of the dominant and subdominant resident species across the
sites for plant functional traits (following Pérez-Harguindeguy et al.
2013). The samples were collected from within the non-cattle grazed
experimental area but not from within any experimental plots. Samples were
collected at peak biomass from April-May in 2015 and 2016. We measured
maximum plant vegetative height, specific leaf area (SLA; leaf area/dry
leaf mass), leaf water content (LWC; 1- leaf dry weight/leaf fresh weight)
and seed mass. The sampled leaves were additionally processed for tissue
carbon and nitrogen content to estimate leaf N content and carbon to
nitrogen ratios. These traits are strong indicators of resource use and
plant growth. SLA is positively correlated with a species relative growth
rate and tissue N (P B Reich, Walters, & Ellsworth, 1997; Westoby,
Falster, Moles, Vesk, & Wright, 2002); leaf water content is
negatively correlated to water stress (Farooq, Wahid, Kobayashi, Fujita,
& Basra, 2009); plant height is often indicative of competitive
interactions for light (Westoby, 1998); and greater leaf N and lower
carbon to nitrogen ratios can be linked to higher food quality (Westoby,
1999). To account for potential trait differences in species that occurred
across the environmental gradient, we sampled individuals for as many
species as possible at both the low and high end of the gradient. To
estimate a species’ seed mass, we first took 10 samples with the same
number of seeds (i.e. the number of seeds was either 50 or 75 seeds for a
species, depending on seed availability). For each sample, we calculated
the average seed weight by dividing the total weight of the sample by the
number of seeds. The species level average was then the average of those
10 estimates. (All species trait data are available in Table S1.) In
total, we sampled traits on 54 different grassland species (24 of these in
both habitat types), which made up on average 98% of the species
composition in a given plot (mean, range of species cover: 2015: 99.25
(89-100), 2016: 98.9 (93.5-100), 2017: 98.75 (84-100). Community sampling.
From 2015-2017, at peak biomass (Apr-May) we sampled the plant species
composition within each subplot. To estimate vole activity, in 2016 and
2017, we recorded the frequency of vole activity (i.e. runways, burrows,
and droppings), along 8 10m long transects within each larger control plot
at each site. For each subplot, we then calculated the community weighted
mean (CWM) for each individual plant trait and the functional dispersion
of each trait. CWM is measured as the mean of species trait values present
in the community, weighted by the relative abundance of each species
(Lavorel et al., 2008). Functional richness (FRic) estimates the
dispersion of species in trait spaces without accounting for species
abundance and is estimated as the convex hull volume (Villeger, Mason,
& Mouillot, 2008). Functional dispersion (FDis) is the average
distance to the centroid in multivariate trait space that is weighted by
species relative abundances (Laliberte & Legendre, 2010). For
those species that occurred across the environmental gradient we used the
species level trait data for a plot that best matched its position along
the environmental gradient for these calculations.
There are four files for this data set: 1) Site environmental data, 2)
Plot community species cover data 3) Plant species trait data and 4) Vole
runway activity data. Site Environmental Data: Three soils samples up to
10cm in depth were collected from each large 9mx9m plot (n=16) and
processed for soil resources. These data are reported here. Additionally,
the mean live aboveground biomass and mean litter from six 10cmx50cm
subplots are reported. These data were included in a principal components
analysis that generated two PCA axis. The first, PCA1 was used as the
resource gradient described in the manuscript. Plot Community Species
Cover Data: With each block, 12 0.5m 0.5m plots were sample in each of
three years (2015, 2016, 2017). For this sampling the visual cover of each
observed species was recorded, with cover adding over 100 to allow for
multiple canopy layers. These data are the cover estimates for each plant
species in each plot over time. The Site.Prod column indicates the how
these data were stratified to match up with species trait that were
collected at the low or high end of the resource gradient. Plant species
trait data: These data are species-level trait data for species observed
at the field site. Specific Leaf Area (SLA), leaf water content (LWC),
leaf area (Area.cm2), leaf dry matter content (LDMC), maximum vegetative
height (Height.max.cm) were sampled on 5-10 different individuals in the
field. These plant leaves were used for leaf nitrogen (Leaf.N), leaf
carbon (Leaf.C), and carbon to nitrogen ratios (C.N.Ratio). Seed mass was
extracted from the Kew database, Baker seed collection at the Jepson
Herbarium, site collected samples, or purchased seed. Vole Runway data:
These data are the average runways observed in 8 transects sampled in the
presence of voles (i.e. open plots).