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Lusk2013

Daniel Falster edited this page Nov 25, 2014 · 1 revision

Report for study: Lusk2013

Contact Information

Data contributor: Christopher H. Lusk

Email: [email protected]

Address:

  • School of Science, University of Waikato, Private 3105, Hamilton, New Zealand

Data source

Citation: Lusk CH, Kaneko T, Grierson E and Clearwater M (2013). 'Correlates of tree species sorting along a temperature gradient in New Zealand rain forests: seedling functional traits, growth and shade tolerance.' Journal of Ecology, 101(6), pp. 1531-1541.

DOI: 10.1111/1365-2745.12152

Abstract: * It is widely believed that species sorting on environmental gradients reflects trade-offs between competitive ability and physiological tolerance of stresses such as frost and desiccation. One specific expression of this general idea is the hypothesis that tree species sorting on temperature gradients in temperate regions involves a trade-off between growth rate and frost resistance, because adaptations to frost reduce light interception and carbon gain potential. * We measured seedling growth of 17 New Zealand rain forest angiosperm trees in a glasshouse, as well as biomass partitioning, gas exchange and hydraulic traits. We then related these variables to the mean July (winter) minimum temperatures most frequently experienced throughout the range of each species. * Species associated with mild winters on average had wider vessels and more conductive stems and were leafier (i.e. developed more foliage area per unit sapwood area) than species from frostier sites. Species' positions on the temperature gradient were not significantly correlated with relative growth rates of seedlings; they were, however, negatively correlated with two measures of species light requirements in the field: the light compensation point for growth, and low-light mortality rates obtained from the literature. * Synthesis. Although seedling growth rates of warm- and cool-temperate New Zealand angiosperm trees were similar on average, the former are more shade tolerant. Competitive hierarchies associated with tree species sorting on temperature gradients thus probably involve a shift in the relationship between shade tolerance and growth rate, rather than a simple trade-off of growth with cold tolerance. This shift is associated with variation in light interception potential per unit of seedling biomass, possibly reflecting a trade-off between stem conductivity and resistance to freeze-thaw embolism.

Overview of data provided

The dataset includes records for 134 individuals from 17 species belonging to 13 family(ies), presenting 1 functional type(s), growing in 1 condition(s) within 1 major type(s) of habitat, with data included for the following variables:

Variable Label Units N Min Median Max
latitude Latitude deg 134 -38 -38 -38
longitude Longitude deg 134 175 175 175
a.lf Leaf area m2 134 0.0028 0.045 0.22
a.stba Stem area at base m2 47 0.000011 0.000031 0.00013
a.cp Crown area m2 47 0.021 0.093 0.3
a.cs Crown surface area m2 47 0.061 0.36 1.2
h.t Height m 134 0.16 0.39 1
h.c Height to crown base m 47 0 0.064 0.31
d.ba Basal diameter m 47 0.0038 0.0063 0.013
d.cr Crown width m 47 0.16 0.34 0.62
c.d Crown depth m 47 0.16 0.41 1
m.lf Leaf mass kg 134 0.00031 0.0039 0.013
m.st Total stem mass kg 134 0.00031 0.0027 0.013
m.so Aboveground mass kg 134 0.00087 0.0069 0.026
m.rt Total root mass kg 43 0.00037 0.0011 0.015
m.to Total mass kg 43 0.0013 0.0034 0.04
a.ilf Area of individual leaf m2 47 0.000071 0.00088 0.0038

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And locally within the country:

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The sites sampled are:

Location Longitude Latitude Vegetation
Glasshouse in New Zealand 175.3139 -37.7869

The growing conditions of sampled plants was:

Location growingCondition
Glasshouse in New Zealand glasshouse

Species sampled

Species Family Pft
Beilschmiedia tarairi Lauraceae evergreen angiosperm
Beilschmiedia tawa Lauraceae evergreen angiosperm
Dysoxylum spectabile Meliaceae evergreen angiosperm
Elaeocarpus dentatus Elaeocarpaceae evergreen angiosperm
Griselinia littoralis Cornaceae evergreen angiosperm
Knightia excelsa Proteaceae evergreen angiosperm
Laurelia novaezelandiae Atherospermataceae evergreen angiosperm
Litsea calicaris Lauraceae evergreen angiosperm
Melicytus ramiflorus Violaceae evergreen angiosperm
Metrosideros umbellata Myrtaceae evergreen angiosperm
Nestegis cunninghamii Oleaceae evergreen angiosperm
Nothofagus menziesii Nothofagaceae evergreen angiosperm
Nothofagus solandri var cliffortioides Nothofagaceae evergreen angiosperm
Nothofagus truncata Nothofagaceae evergreen angiosperm
Vitex lucens Verbenaceae evergreen angiosperm
Weinmannia racemosa Cunionaceae evergreen angiosperm
Weinmannia silvicola Cunionaceae evergreen angiosperm

Methods used

Sampling strategy: We obtained 200 - 350 mm tall seedlings from commercial sources and grew them in a glasshouse for 105 days. Crown architecture of each seedling was recorded using a using a FASTRAK 3D-digitizer (Polhemus, Colchester, VT, USA), in conjunction with the software package FLORADIG (CSIRO Entomology, Brisbane, Australia). YPCONVERT, developed by Daniel Falster, was used to convert architecture files to a format compatible with YPLANT.

Leaf area: The total foliage area of each plant was measured using a LI-3100 leaf Area Meter

Stem cross sectional area: Basal stem diameter (immediately above any root flanges) was measured on two orthogonal axis, using electronic callipers.

Height: Height was measured as the length of the longest stem, from the ground to the apex.

Crown area: Crown area was computed from the plant architecture data obtained using the 3D digitizer.

Biomass: Only aboveground biomass was harvested. Plants were divided into stem and leaf fractions and then dried to a constant weight. Petioles of simple leaves were included in total leaf mass. Petioles of compound leaves were included in the stem fraction.

Traits: Note that only aboveground biomass was harvested.

Growth environment: Nursery-sourced plants grown in glasshouse with ~ 20% light.

Other variables: Relative growth rates of stem height and volume were measured. Transverse sections were taken from base of each stem to measure vessel diameters and densities. Theoretical sapwood conductivity was then computed from the xylem anatomy data. Actual measurements of sapwood conductivity were also carried out.

Year collected: 2011-2012

Plots of data

This is how the study Lusk2013 fits in the entire dataset (grey). each colour represents a species. A legend of species names with colours is included at the end for reports with 1 < n < 20 species.

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