DOI: 10.5061/dryad.6m905qg1v
title: Data from: Planting design influences green infrastructure performance: Plant species identity and complementarity in rain gardens

description: Green infrastructure’s capacity to mitigate urban environmental problems,
 like heat island effects and excessive stormwater runoff, is partially
 governed by its plant community. Traditionally, green infrastructure
 design has focused on engineered aspects, such as substrate and drainage,
 rather than on the properties of its living components. Since the
 functioning of these plant assemblages is controlled by ecophysiological
 processes which differ by species, the identity and relative abundance of
 the species used will influence green infrastructure performance. We used
 trait-based modeling to derive principles for the effective composition of
 green infrastructure plant assemblages, parameterizing our model using the
 vegetation and ecophysiological traits of the species within New York City
 rain gardens. Focusing on two plant traits that influence rain garden
 performance, leaf surface temperature and stomatal conductance, we
 simulated the cumulative temperature and transpiration for plant
 communities of differing species composition and diversity. The outcomes
 of the model demonstrate that plant species composition, species identity,
 selection effects, and interspecific complementarity increase green
 infrastructure performance much the way biodiversity affects ecosystem
 functioning in natural systems. More diverse assemblages resulted in more
 consistent transpiration and surface temperatures, with the former showing
 a positive, saturating curve as diversity increased. While the dominant
 factors governing individual species' leaf temperature were abiotic,
 transpiration was more influential at the community level, suggesting that
 plants within diverse communities may be cooler in aggregate than any
 individual species on its own. This implies green infrastructure should
 employ a variety of vegetation; particularly plants with different
 statures and physical attributes, such as low-growing ground covers, erect
 herbaceous perennials, and shrubs.
description: Ecophysiological measurements on New York City rain
 gardens<strong><br></strong> 
 Ecophysiological measurements were collected on the vegetation
 from six New York City Department of Environmental Protection (NYC DEP)
 rain gardens in Rego Park, Queens, New York, NY. The plant
 ecophysiological traits of surface temperature and stomatal conductance
 were measured on a total of six species, using four individuals of each
 species. The six species consisted of: two shrubs (<em>Aronia
 melanocarpa</em> and <em>Spiraea nipponica)</em>, two
 non-leguminous forbs (<em>Eupatorium dubium</em> and
 <em>Nepeta faassenii</em>), a C4 grass (<em>Panicum
 virgatum</em>) and a C3 grass (<em>Calamagrostis x
 acutiflora)</em>. The first five of these species occurred in three
 rain gardens, while <em>Calamagrostis</em> was present as a
 monoculture in three others, as specified by NYC DEP planting design.
 These species encompassed all intentionally planted non-tree vegetation
 within their respective rain garden; volunteer species occupied less than
 2% of total cover.  Data were collected between 10am
 and 2pm over ten days from July to September 2016. For each species within
 each rain garden for each sampling day, two thermal images and a stomatal
 conductance measurement were taken on the second fully expanded leaf of
 four individual plants. The same plants, but different leaves, were used
 during the ten study days. The thermal images were taken prior to
 measuring stomatal conductance. For the first image, the leaf was
 undisturbed. In the second image, a plastic tray with a piece of white
 filter paper half wet (wet reference) and half dry (dry reference, Whatman
 1443-125) was held behind and at the same angle as the leaf. A weather
 station (HOBO U30 Data Logger, Onset Computer Corporation) measuring wind
 speed, photosynthetically active radiation (PAR), barometric pressure,
 relative humidity, and temperature was mounted to a hand truck and
 positioned immediately adjacent to the rain garden where measurements were
 being taken to collect local climate information. The weather station
 recorded environmental variables every second and logged the mean of these
 data each minute and was wheeled to each rain garden over the course of
 the day. At the beginning of each study day, the thermal camera (FLIR
 T650sc, FLIR Systems, Inc.) was calibrated with temperature and humidity
 readings from the portable weather station. Emissivity was assumed to be
 95% (Jones, 2004). Time was synchronized between the thermal camera,
 weather station, and porometer (SC-1 Leaf Porometer, Decagon
 Devices), Thermograms were converted to comma-separated
 value (CSV) files (FLIR ExaminIR Pro software) and read into ImageJ
 (Schneider et al. 2012) where the leaf and, if applicable, dry and wet
 references were manually outlined to extract temperature information. Mean
 temperature of these areas was used for later analyses; all references to
 leaf and reference temperatures refer to these
 thermographically-determined means. Since the leaf included both areas in
 shade and those in sun, a mean of the minimum temperatures was used as a
 “shade” temperature for later analyses. A paired t-test on a 17-leaf
 subset of the data was used to compare the temperature of leaves with
 references behind them to those without. Time of stomatal conductance
 readings was rounded to the nearest minute and matched with the weather
 station data from the same time to calculate transpiration (E) according
 to Lambers, Chapin, and Pons (2008) as: <em>(VPleaf -
 VPair)/barometric pressure</em>*<em>gw. gw</em> is
 stomatal conductance, <em>VPleaf</em> is the saturation vapor
 pressure of the leaf, using the temperature from the porometer, and
 <em>VPair</em> is the vapor pressure of the air (saturation
 vapor pressure of the air, using temperature from the weather station,
 multiplied by relative humidity). Transpiration data were associated to
 corresponding thermal images taken on the same day for each individual
 leaf.  Simulations All simulations
 and statistical analyses were performed in R version 3.2.3 (2015-12-10).
 Simulated assemblages, parameterized from the NYC rain gardens, ranged
 from one to six species. These assemblages consisted of randomly drawn
 species from the pool of six, without replacement. Each species was
 assumed to occupy an equal portion of the rain garden; e.g., if an
 assemblage consisted of three species, each covered a third of the rain
 garden, if four species, each filled a quarter, etc. Total rain garden
 size was considered to be 9.3 m<sup>2</sup>, the most common
 area for the NYC rain gardens. As the species differ in physical
 structure, rather than using vegetation cover, the volume of leaves in
 each portion was calculated as follows: height was binned into five levels
 and, at each of these levels, both total coverage (woody and leaf) and
 percent coverage transpiring/temperature regulating (leaves only) were
 determined based on personal observation. Whole rain garden transpiration
 and surface temperature were assumed to be the mean calculated from
 stomatal conductance and thermography measurements, respectively, both
 scaled up using the area of the rain garden occupied by a species and
 percent leaf coverage at each level. Whole rain garden coverage can exceed
 100% since it was calculated as the sum of coverage at each of the five
 levels. Total transpiration was additive, whereas surface temperature was
 calculated as a weighted mean based on proportion of leaf cover at each
 level. To allow for structural complementarity between
 species, if a species did not fully cover its rain garden portion at the
 ground level, the other species in the community were sequentially allowed
 to “fill in” its portion until either the ground level was fully occupied
 or there were no new species left. The pool and order of species were
 determined by the initial random draw. For example, a spreading shrub with
 a woody base might have 100% leaf coverage at its top, but only 10% stem
 coverage at ground level. Here, creeping ground vegetation could enter
 into the remaining 90% unoccupied by the stem, if this species occurred
 subsequently within the species draw. If coverage of this creeping
 vegetation was 100% at ground level, no further species could fill in; if
 not, another species from the community was allowed to occupy the
 remaining portion, until no new species were available. In the model for
 transpiration, structural complementarity added species-specific
 transpiration in the amount of the additional percent cover provided by
 the new species; in the model for temperature, a weighted average based on
 additional percent cover was used. To simulate competition for light,
 inter-specific shading was simulated by using a shade temperature,
 calculated from the mean shade temperature (by species) from the
 thermography measurements and the relative heights of the species within
 the communities. If any of the species filling in the unoccupied ground
 level was shorter than the original plant (e.g., the creeping ground
 vegetation in the above example), a shade temperature was used. If the
 filling-in species was taller, the model assigned a shade temperature to
 the original plant in proportion to the percentage occupied by the new
 species. For example, if a flowering herbaceous species occupied 90% of
 the ground and a taller spreading shrub filled in the remaining 10%, the
 entire rain garden temperature would be a weighted average of 10% of the
 herbaceous shade temperature, 80% if its regular temperature, and 10% of
 the shrub’s regular temperature. Since the order in which species fill in
 each other’s portions matters, each community of two through six species
 was iterated 100,000 times.
description: Weather station data and ecophysiological measurements for plant
 species within New York City rain gardens are provided as a .csv. These
 data were used to simulate communities of one to six species. These
 simulations are provided as two separate .rds files: one for transpiration
 and one for temperature.