DOI: 10.5061/dryad.63xsj3v7z
title: Neighbor effects on population growth rate differ among populations due to variation in demographic rate sensitivities in Sedum lanceolatum

description: Population growth rates will respond to an environmental driver only if
 the driver impacts demographic rate(s) and the population is sensitive to
 impacted demographic rate(s). If populations vary in the sensitivity of
 population growth rate to demographic rates, the effect of an
 environmental driver on population growth rate could vary across
 populations, even if the effect of the driver on demographic rates does
 not vary across populations. Here, we use five years of demographic data
 of a common alpine plant, including data from a neighbor removal
 experiment and a climate warming experiment, to quantify the relative
 contribution of neighbor effects on demographic rates vs. sensitivity of
 population growth rate to demographic rates to across-population variation
 in neighbor effects on population growth rate. We find neighbor effects on
 population growth rate vary significantly across populations, and this
 effect is driven primarily by variation in sensitivity of population
 growth rate to demographic rates across populations. Further, results from
 our climate warming experiment suggests variation in sensitivity across
 populations is partly driven by temperature differences. Our results
 highlight the importance of considering changes in the sensitivity of
 population growth rate to demographic rates across space, and show how
 changes in sensitivity can contribute to spatial variation in the effects
 of a driver on population growth rate.
description: <strong>Data collection on variation in demography across
 elevations</strong> To quantify variation in demography across
 elevations in <em>S. lanceolatum, </em>we conducted
 demographic censuses in two low-elevation and two high-elevation
 populations over four annual transitions. Hereafter, we call the data
 collected at these four populations, described in this section, the
 “demography” data. These four populations differ systematically in
 temperature, with higher temperatures at the two low-elevation
 populations. In 2011, during peak fruiting in late summer and early fall,
 we marked and mapped 1341 individuals across the four populations,
 measuring size (sum of volumes, height x area, across all rosettes), and
 counting fruits. We returned annually during peak fruiting until 2015 to
 score survival, measure size, and count fruits. Altogether, we collected
 data on 6705 individual x transitions, including data on very small plants
 and seedlings. We used these data to estimate five size-dependent vital
 rates: annual survival, mean size after one year of growth, variance in
 size after one year of growth, probability of fruiting, and number of
 fruits given a plant fruited. Note that while vegetative reproduction is
 common, occurring when individual rosettes take root after separating from
 primary stems, connections between parent and vegetative offspring are
 apparent above ground. Thus, any vegetative reproduction is subsumed into
 our estimates of growth. To
 quantify seedlings per fruit (i.e., the number of seedlings present each
 year per fruits in the year prior), we first estimated the number of seeds
 per fruit at each elevation and then conducted a seed addition experiment
 at each population to estimate the population-specific number of seedlings
 per seed. To estimate seeds per fruit, we collected all fruits from 71
 plants across our four populations in 2010, 2011, and 2012. For a subset
 of these plants (n = 25), we weighed the total seed mass and counted the
 total seed number, using these data to obtain the average seed mass for
 each elevation. In all, we counted 1073 seeds. We then used the
 relationship between seed mass and seed number to create a regression to
 estimate the population-specific number of seeds per fruit from the 72
 plants (by weighing seed mass from individual fruits). To estimate the
 population-specific number of seedlings per seed, we conducted seed
 addition experiments at each population. At each population, we
 established five paired 10 cm x 10 cm plots (10 plots total) that were
 proximate to one another and 30 cm from any marked plants; one of the pair
 was randomly assigned to a seed addition treatment and the other to an
 unmanipulated control treatment. In 2014, we added 50 <em>S.
 lanceolatum</em> seeds to the seed addition treatments. In 2015, we
 counted the number of seedlings in all plots, calculating seedlings per
 seed as: (seedling number in seed addition plots – seedling number in
 control plots)/50. This procedure corrects our seed addition experiment
 for any background germination due to germination from a seedbank or
 natural dispersal into the plot. If seedling number was higher in control
 than in seed addition plots (occurs in 2/17 pairs), we estimated seedlings
 per seed as zero. Due to limited data, these values were averaged across
 plots and elevations rather than population specific values. Finally, we
 multiplied the elevation-specific seedlings per seed by the
 elevation-specific number of seeds per fruit to estimate seedlings per
 fruit for each population. <strong>Data
 collection on neighbor effects across elevations</strong>
 To quantify neighbor effects in <em>S. lanceolatum,
 </em>we conducted a neighbor removal experiment at each of the same
 four populations from 2011-2015. We call the data collected in this
 experiment the “removal experiment” data. In 2011, we marked and mapped
 719 individuals that were &gt;= 30 cm apart, and arrayed roughly
 equally across small, medium, and large size classes and across
 populations. We randomly assigned each individual to either a neighbor
 removal or an unmanipulated control treatment; small, medium, and large
 plants were roughly equally distributed among treatments. Annually,
 starting in 2011, we removed all above-ground biomass from a 15 cm radius
 around neighbor removal treatment plants, taking care not to disturb the
 soil. In 2011, during peak fruiting in late summer and early fall, we
 measured size and counted fruits of all these individuals. Until 2015, we
 returned annually during peak fruiting to score survival, measure size,
 and count fruits, replacing any individuals that died with newly marked
 individuals. Altogether, we collected data on 3595 individual x
 transitions, which we used to estimate the same five size-dependent vital
 rates as we did for our demography data. Note that we did not collect
 separate estimates of seedlings per fruit for neighbor removal
 treatments.
description: # Neighbor effects on population growth rate differ among populations due
 to variation in demographic rate sensitivities in Sedum lanceolatum
 [https://doi.org/10.5061/dryad.63xsj3v7z](https://doi.org/10.5061/dryad.63xsj3v7z) ## Description of the data and file structure This dataset includes three files used for the creation and estimation population growth models for *Sedum lanceolatum*. ### Files and variables #### File: Sedum\_dat.csv **Description:**  The file **Sedum_dat.csv** contains demography data from two data sources: an unmodified 'demography' only dataset and a 'neighbor removal' dataset and are specified in the *trmt* column. while the 'demography' *trmt* level is equivalent to the 'control' *trmt* level, we analyses these levels separately to prevent any confounding results. Only the 'removal' *trmt* level was experimentally modified, where all neighboring plants were removed from the plot. Columns with a numerical suffix indicate the year of data collection (e.g. totalvol11 = total volume of individual in 2011). For all datasets, values of "NA" indicate no value was recorded for that individual/variable, whereas values of "0" indicate the variable was examined, but absent. ##### Variables * site : site of data collection. Four sites are included * transect : transect of individual * TP : color and shape of toothpick used to identify individual * x : x coordinate of individual along transect * y : y coordinate of individual along transect * trmt : treatment of transect (demography, control, removal) * rosnum : number of rosetts * totalvol : total volume of plant (cm^3) * frtno : number of fruits on individual * notes : any notes data collector had regarding individual * sur : survival of individual since last census * NR_done : if neighbor removal treatment was conducted that year * bifrt : binary if a plant fruited in the given year. #### File: seeds\_per\_fruit.csv **Description:**  The file **seeds_per_frt.csv** includes the number and weight of seeds for a given number of fruits collected from an individual. ##### Variables * site : site of data collection. Only 3/4 sites are included (missing Centennial) * fruit : number of fruits collected from an individual * seed_count : number of seeds from *all* collected fruits of an individual. A subset of individuals * seed_weight : weight (g) of total seeds collected from an individual * year : year of fruit collection #### File: seedAddition.csv **Description:**  The file **seedAddition.csv** includes data from a seedling experiment, where 50 seeds were added to plots to examine number of seedlings produced. ##### **Variables** * site: site of data collection. Four sites are included. * pairing: indicates which plots were paired (one plot had seeds added, the other did not), with the same value at a site indicated plots were paired. * treatment: "S" indicating seeds were added or "C" indicating a control plot with no seeds added. (Note that some plots are missing their pair and should likely be removed from analyses) * transect: which monitoring transect plots were located at. * notes: any notes by the data recorder. * date_seedlingcount: date at which seedlings were counted in a plot. * seedlingcount: how many seedlings were observed in a plot. ## Code/software No special software is needed to open these files (.csv). A basic text editor will work, as will Microsoft Excel or most statistical programs.