Trait-based mapping of forest function
Tohru Nakashizuka
Research Institute for Humanity and Nature• Spatio-temporal resolution and accuracy of ES/NCP assessment including scenario analyses are
required for decision making• Combination of various databases on functional
traits and abundance of key species which relate to
ES are the expected to contribute greatly toquantification of ES1

ESs estimated from biomass and structure of forests
Data base

Model

Forest Plot

Relation ofcommunity
mean of FTsand ESs

Location
Composition
Structure
Dynamics

Functional
traitsCommunity
mean ofecosystem
function

Land coverTypesStructure
Dynamics

ClimateCommunity
distributionand change

ESs

Quantificationof ESs

Mapping ofESs

Functional traits measured
Target species
Japanese trees 300 spp., about 140 FTs
E and SE Asian trees 900 spp. 16 FTS
FTs measured（16 FTs）
• Leaf size, LMA, toughness, thickness, water contents• Leaf nitrogen and carbon (contents/stable isotope）• Leaf total phenol, condensed tannin, lignin, NDF• Leaf vein density• Photosynthetic rate
• Wood density
Literature source（about 120 FTs）
• Defensive Traits（trichomes, chemicals, etc.）• Reproductive Traits（pollen, nectar, flower color, etc.)• Root system（root diameter, mycorrhiza, etc.)• Utilization（timbers, foods, medicines, etc.）

Map of FTs
Max treeheight

Wooddensity

LMA

Total phenol

Aiba et al.

Ecosystem functions estimated by the databases on forest plots and functional traits
Maximum photosynthesis rate
(nmol g-1s-1)

Decomposition coefficient,K (year-1)

Aiba et al.

Probability of soil erosion•••••

Data base on forest resource by Forest Agency（7200 sites）– Tree composition, Basal area, grass cover, shrub cover)– Inclination, Soil erosion (Y/N)
Functional trait data base
– Horizontal distribution, root hair density, root thickness
Climate data base
– Annual precipitation, Max snow depth, water deficit
Models to cause soil erosion
Verifying if functional trait is included in the model or not

Probability of soilerosion (%)

Many tourists enjoy autumn color of forests in Japan

Popular spots for the beauty of autumn color• Data was collectedfrom a special site
for autumn foliage.
• Records for 457
spots are available.

Percentage of
red leaf trees

Distribution ofbeauty spots8ESs estimated from the abundance of key spp.
Data base

ModelESs

Relation of key
speciesabundanceand ESs

Quantificationof ESs

Distribution
Location
Abundance
Dynamics

Land cover
Types
Structure
Dynamics

ClimateHabitat andchange of key
speciesabundance

Mapping ofESs

Seedset of buckwheat

Landscape and seed set of buckwheat

Forests within 3 km

Taki et al

Taki et al.

森林生物による送粉サービス・ローカルマップ
Abundance of other insects

Forested area with in 3km
from the filed（m2）Grassland area within 100
m from the field（m2）

個体数

Honey bee abundance＋Landcover＝Distribution ofsampled individuals

1)Garibaldi at al. (2013)Science2) Kennedy et al. (2013)
Ecology Letters

Estimated habitat of honey bee

Forest potential to provide honey

BA of trees
providing honey

Aiba et al.

Land use change and ESs
Primary f. -> Secondary f.

Primary f. -> Plantation

Change in decayrate (%)

Aiba et al.

Effects of climatic change on ESs
Decay rate (yr-1)

Present

Aiba et al.

Community weighted mean of forest types in SE Asia

Aiba et al.

Mapping functional traits in SE Asia

0.29
0.12-0.04
Log (N contents in leaf)

Photosynthetic rates in Asian forests
Photosynthetic rate (n mol/g/s)
Rate

High:777
Low: 0TheThe effecteffect onon FTs
FTs byby transformationtransformation fromfrom natural
natural toto secondary
secondary forestsforests(relative valure)
Rate

High:777
Low: 0Community weighted means of natural forests were replaced by those of
secondary forests of the same forest types

Biodiversity/ecosystem observationand ES assessment• Quantitative assessment on ES/NCP including scenario
analyses gives critical information on policy and decision
making• Combination of various databases gives great range ofquantification and mapping of ESs• Database on functional traits and abundance of key
species which relate to ES are the expected to contribute
greatly to quantification of ES• Spatio-temporal resolution and accuracy of ES assessment
are depending on information/database, and thus,
observation
19

Thank you!