Download Protocol INNOVKAR WP2

Work package 2: Adaptation and resilience of shea tree facing climate change and
drought using ecophysiological and modelling approaches
2.1. Objectives
The main objective is to define management recommendations of shea tree parkland
based on their ability to face drought and on the prediction of the distribution of shea tree
under future climatic scenarios.
The specific objectives are:
- To build a climatic index of the sites studied;
- To characterise germplasm adaptation to rainfall gradient by studying the variation of
tree phenology, of tree morphological and ecophysiological traits in the natural
populations of the Sudano-Sahelian zones;
- To model changes in the distribution of the Shea tree under future climate change
scenarios.
2.2. Study of shea populations across its natural range
The aim of this study is to characterise germplasm adaptation to rainfall gradient by
studying the variation of tree phenology, of tree morphological and ecophysiological
traits in the natural populations of the Sudano-Sahelian zone.
2.2.1. Sampling of the populations of shea
The sampling of shea populations across its range will be conducted in Burkina Faso,
Ghana, Mali, Senegal and Uganda. Three sites will be selected in each of the above
mentioned countries for both WP1 and WP2 following a north-south gradient using
climatic index, .i.e one site in the northern limit of shea tree distribution, one in the
middle and one in the southern part of its distribution. For each site, 3 fallows (1-5 years;
6-10 years and more than 10 years) representative of the area and 3 fields of different
ages (1-5 years; 6-10 years and more than 10 years) replicated 3 times, giving a total of
18 plots will be selected. In total 54 plots will be selected in each country for phenology
(see WP1 for more details), morphological parameters and regeneration studies.
2.2.2. Data collection
Stand Characteristics
Once at the beginning of the study stand description, area number of shoots, diameter and
height classes for every species (Karite or not), understorey, current cultivation, past
cultivation, etc. will be assessed.
Soil and climate
Only once at the beginning of the study soil texture, dry bulk density and pH will be
measured on soil samples taken according to the observed rooting depth of shea trees,
and to visual interpretation of soil sub-layers. The samples will be air dried for physical
and chemical analyses to determine texture, pH, total C, total nitrogen, total and available
phosphorus, total and available potassium, and CEC. Soil layers will also be described for
each plot using soil profile. Soil slope will also be recorded
Periodically soil cores will be taken according to major/watering/drying events to obtain
gravimetric soil water content and the maximum reserves of water in the soil (rainy
season) will also be estimated in order to compute the fraction of extractable water for
any period. All sites should be equipped with a set of manual rain gauges (at least one per
plot) and weather stations (at least one per site: $800 company name Davis Meteo).
These later data are needed to work out climatic index, Vapour Pressure Deficit (VPD),
and drought index. Potential evapotranspiration will be estimated according to potential
evapotranspiration (FAO, Penman, Priestley-Taylor) models to provide a climatic index.
All these parameters will be measured in Burkina Faso, Mali, Ghana, Senegal and
Uganda.
Morphological traits of natural populations
The plots for morphological traits will have two sizes (2500 m2 for mature trees and
781.25 m2 for the regeneration). For details, please see the WP1 protocol.
The individuals of the regeneration will be grouped in 4 classes of height: 0-50 cm, 51100 cm, 101-150 cm and “young adult trees” with a height>150 cm and DBH<10 cm.
Number of individuals, height classes, distribution, above and below ground architecture
will be the variables to be collected for the regeneration study (monitored twice a year: in
October at end of rainy season and in May at the end of the dry season). WP1 protocol
gives more details.
For mature trees the following parameters will be assessed: tree density, tree height,
crown volume and gap-fractions (hemispherical photography), diameter at breast height
and at crown base, and height at crown base (monitored twice a year: in October at end of
rainy season and in May at the end of the dry season).
Tree phenology in natural stands
Phenology includes here: periods of leafing, flowering, fruiting and growth (height,
diameter). Phenology study will be conducted in Burkina Faso, Mali, Ghana, Senegal and
Uganda for which 10 individuals per type of field and fallow will be selected based on
their fruit production using local knowledge of farmers. In total, 60 individuals for each
site and 180 individuals for each country will be monitored at various time intervals
(weekly, bi-weekly or monthly) to study the phenology (leaves, flowers, fruits): the
sample trees will be representative of the variation in tree size (basal area) among the
mature trees within each stand. Different variables will be measured: beginning of
leafing, flowering, fruiting, and length of the different phases as followed (see WP1 for
more details):
- Flower/grid: 7 to 15 days, Number of flowers on 8 shoots, amount of litter using
litter traps;
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-
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Fruit: all production, collection every day;
Leaves: 7 to 15 days, Number of leaves on 8 shoots, it is recommended to use
hemispherical photography to monitor the fraction of gaps in the crowns of the
selected trees: 4 photos under each tree (N, S, E, W) for each date, photos only in
conditions of diffuse solar radiation (one hour before sunrise and one hour after
sunset). Leaf size, specific leaf area, and leaf N concentration will be measured at
specific periods of the phenology phases.
8 shoots (east-west-south-north and, below and higher compartments) on 12 trees
in each site,.i.e.1 young fruiting tree and 1 old fruiting in each the 3 age classes
(1-5 years, 6-10 years, >10 years) of the two land use types (fallow and field):
counting of the number of flowers, leaves and fruit and, measuring the diameter,
growth of shoots;
Trunk diameter and tree height measured twice a year (at the end of the rainy
season and at the end of the dry season);
2.3. Nursery experiment
The main objective of the present experiment is to delineate provenances on the basis of
their strategy and their ability to face drought by determining their water use efficiency at
different soil water regimes and its relationship with carbon isotope discrimination
(δ13C). We also will examine the changes in morphological traits as well in
ecophysiological parameters, i.e. nutrient uptake, photosynthesis and dry matter
accumulation.
2.3.1. Experiment design
This experiment will be conducted in Burkina Faso using 7 provenances, i.e. 1 from Mali,
1 from Senegal, 1 from Ghana, 1 from Uganda and 3 from Burkina Faso. A factorial
experiment in nursery will be conducted with the following factors:
• 3 water regimes: 50%, 75% and 100% of field capacity;
• 7 provenances following a gradient of aridity;
• 3 lifespans (duration of growth before harvest).
Each treatment will be replicated 10 times, giving a total of 630 plants (3 water
regimes*7 provenances*3 lifespans*10 replicates). Three times during the experiment
one third of the 630 plants (3 lifespans) will be uprooted to study the allocation of the
resources to different components (roots, leaves and stems). The plants will be raised in
pots of 10 kg. The quantity of water worked out based on soil physical properties as
following:
pF 2.5 (% volume) = pF 2.5 (% weight) * BD (soil bulk density)
Quantity of water at FC = PV% * (Pot volume filled with mixture)
Five pots for each water regime will be kept as unplanted controls and the amount of
water required for each plot to maintain the respective soil water regime will be estimated
by weighing the pots every 2 days. In addition, 5 plants of each water regime will be
installed in sub-vertical transparent rhizotrons, in order to assess the productivity and
turnover of the fine root compartment.
2.3.2. Data collection
The following data will be collected: climate, PET, soil water availability (water
potentials), fluorescence, sapflow, leaf water potential, leaf area index (direct estimation),
growth per compartment, instant water use efficiency, annual and plant-integrated wateruse efficiency, root:shoot allocation, net primary productivity, photosynthesis and d13C.
The measurements will be done as followed:
•
Tree growth parameters will be measured weekly;
•
Three times 10 plants will be harvested for each water regime and the biomass of
all the components (stems, branches, leaves, and roots) will be measured;
•
Sub-samples of leaves will be used to estimate leaf size and specific leaf area;
•
Fine root dynamics will be assessed using rhizotron technique;
•
The different components of plant materiel will be analyzed for C, N, P, K, Ca,
Mg, and ash.
2.4. Parkland experiment: carbon budget
The goal is to estimate the carbon budget (incoming C by photosynthesis, use of this C
for growth, autotrophic respiration and for reserve dynamics) of the trees at least on one
site with detailed investigations and equipments. This experiment will be conducted only
in Burkina Faso. All basic measurements will be conducted in an identical manner, as
compared with the other sites (see point 2.2.2).
2.4.1. Experimental design
Ten trees of different size and levels of fruit production will be selected in farmed fields.
The design will be centered on tree trunk and measurements equipments installed at
various distances from each tree trunk.
2.4.2. Data collection
In addition to point 2.2.2 , fluorescence, sapflow using TDP sensors, leaf area index (HP),
growth per compartment, instant water use efficiency, annual and plant-integrated wateruse efficiency, root:shoot allocation, net primary productivity, estimated autotrophic
respiration, estimated plant canopy photosynthesis, δ13C, reserve dynamics will be
monitored. Access tubes of TDR will also be installed at various distances from tree
trunk to monitored soil water content. The sample-trees, leaf size, specific leaf area, and
leaf N concentration will be measured.
Leaf and above ground biomass will be estimated. Root biomass and productivity < 2mm
(fine roots) and > 2 mm (coarse roots): A set of trees, representative of the age structure
will be excavated in every plot, concurrently with soil profile description, down to the
maximum rooting depth. The root biomass will be estimated by classes of root diameter
(> or < 2mm at least). Rooting depth and fine root biomass will be estimated during the
rainy season and dry season by root sampling (auger) in order to build a root/shoot index
and evaluate the above and below ground biomasses. This work will be done on 3 trees of
different sizes, i.e. 9 trees in total. Fine root turnover will be assessed at least in the fully
equipped site with the help of rhizotrons installed under each tree at various distances
from tree trunk.
Litter traps: litter traps (dry mass of each organ measured in litter for each sampling date)
will be installed under these trees to collect the litter of leaves, flowers and branches.
Tree growth reserves will be measured in collaboration with Fabrice Davrieux and the
carbon balance will be worked out as follows: NPP+Ra = GPP, where NPP is the net
primary productivity, Ra is the autotrophic respiration, GPP is the gross primary
productivity. Photosynthesis will be modelled at the scale of the leaf and of the canopy
using a combination of models (Farquhar et al., 1981; De Pury and Farquar, 1997; Jarvis,
1976). Ra will be modelled from de Wit (1976) and Penning de Vries et al. (1989). Water
use will be modelled after inverting the Penman-Monteith model.
2.5 Distribution of the Shea tree under future climate change scenarios
The main objective is to ascertain the potential movement (i.e., change in distribution) of
Shea trees under global warming conditions.
2.5.1 Data
Shea distribution data available from the School of Environment and Natural Resources
at University of Wales, Bangor (from John Hall & others) will be used as the base dataset
in this analysis. Any newer datasets that become available during the course of the study
will be used to update the existing datasets, and also to analyse the changes in shea
distribution.
The future climate scenarios developed by the IPCC, based on the climate predictions
from the Hadley Centre’s third generation coupled ocean-atmosphere General Circulation
Model will be used to model shea distribution under different climate scenarios.
The elevation data from the USGS digital elevation model for the globe will be used for
the analysis.
2.5.2 Method
Bayes-based genetic algorithm model (McClean et al 2005) will be used to model shea
distribution under present and future climate scenarios. This model calculates the
probability of occurrence for a species (Shea in this case) given a set of climatic variable
thresholds using a Bayesian classifier and a genetic algorithm.
Based on the present distribution of shea and the present climatic conditions, a
bioclimatic envelope for shea distribution will be created. Similar bioclimatic envelopes
will be created for future climatic scenarios based on the predicted changes in future
climate. The differences in present and future bioclimatic envelopes for shea distribution
will be analysed to predict the changes in shea distribution in the future.
2.5.3 Potential Extensions
Once the base bioclimatic models for shea distribution under present and future climate
scenarios have been developed, ways to extend the models by incorporating other factors,
such as species competition, fire, anthropic selection etc., will be explored. However,
incorporating these factors in the models is entirely dependent upon the availability of
suitable data across the distribution range of shea.
The potential to incorporate physiological data (on shea) in the bioclimatic models will
also be explored (as discussed with Olivier Roupsard during the first meeting in Mali).
Researchers involved in the work-package
Country
Burkina
Faso
France
Name
Bayala Jules
Email
[email protected]
Institute
CNRST/INERA
[email protected]
CIRAD
Danmark
Roupsard
Olivier
Ræbild Anders
[email protected]
Centre for Forest,
Landscape and Planning,
Faculty of Life Sciences,
University of Copenhagen
Senegal
Ghana
UK
UK
Kaire Maguette
Dr. Yidana
Colin McClean
Rob Marchant
[email protected]
[email protected]
[email protected]
[email protected]
ISRA
UDS
University of York
University of York
UK
UK
Uganda
Uganda
Burkina
Faso
Mali
Mahesh Poudyal
John Lovett
JBL Okullo
Gerald Eilu
Bastide Brigitte
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
University of York
University of York
Makerere University
Makerere University
CNRST/INERA
Yossi Harouna
[email protected],
EIR