Sebastien Elis

Yingjie Wu

Hayden-William Courtland

Hui Sun

Valerie Williams

Karl Jepsen

Shoshana Yakar

IGF-1 Bioavailability in Tissues Determines Body Size

IGF-1 is an important regulator of somatic growth and body size. IGF-1 forms complexes with a family of high affinity IGF-binding proteins (IGFBPs) that protect it from proteolytic degradation in serum and regulate its bioavailability. The IGF-1 analog des-IGF-1 has a three amino acid truncation at its N-terminus, which significantly decreases its binding affinity to the IGFBPs, but does not affect its affinity for the IGF-1 receptor. The Long R IGF-1 analog (LR3) has one amino acid substitution at position 3 (glu>arg), which significantly reduces its affinity to IGFBPs.

BACKGROUND AIM

Determine whether IGF-1 binding to IGFBPs is both necessary and sufficient for regulation of somatic growth

Knock-In Mouse Models

  lean mass and decreases fat mass

1 leads to increased uteral size and complexity

	Model	Gonadal fat	Pancreas	Uterus and Ovaries
	KID	0.73	0.95	1.17
	KIK	0.66	0.82	1.14
	Control	1.31	0.61	0.78
	Model	Gonadal fat	Pancreas
	KID	0.78	0.89
	KIK	0.89	0.77
	Control	1.41	0.59
	Control	KID		KIK
	Free IGF-Loss of IGFBP binding increases body size and organ size in both
	males and females, likely through increased IGF-1 bioavailability.
	Further studies are needed to determine how changes in IGF-1
	bioavailability affect skeletal growth, carbohydrate metabolism and
	tumor susceptibility.


H Duval

M Millan

EMERGENCE DATES OF EURYTOMA AMYGDALI ENDERLEIN ADULTS IN THE SOUTH-EAST OF FRANCE AND CONTROL STRATEGY

Keywords: Eurytoma amygdali, almond, Prunus dulcis, chemical control Eurytoma amygdali, amandier, Prunus dulcis, lutte chimique

Eurytoma amygdali Enderlein was discovered in France in 1981 and is now present in the South-east area of France, but is absent in Pyrénées-Orientales and Corsica. In this study, the adult emergence dates in 2005, 2006 and 2007 have been observed in three different places. Some chemical control tests in insectarium have showed that the "Karate® Zeon" insecticide, with active ingredient the Pyrethroids 'Lambda cyhalothrine', has a high efficiency and retentiveness of more 23 days. These tests were confirmed in field orchards. With one single chemical spray applied at the beginning of the adult emergence, only 1 to 4 % of fruits were infested, when more than 60% of fruits were infested in the control almond orchard without insecticide. With these results, the Karate® Zeon has been legally authorized in France to be used against Eurytoma amygdali.

INTRODUCTION

The almond seed wasp, Eurytoma amygdali was detected in France for the first time in 1981 (Arambourg and all, 1983) in the Var and Bouches-du Rhone departments. The progression towards adjacent departments was regular and Eurytoma amygdali is It is a new pest in France, and almond growers do not yet know how to manage this insect. Up to 80% of the crop of some orchards can be destroyed. The biology of this insect has been well described by different authors (Mentjelos, 1970;[START_REF] Plaut | On the biology of the adults of the almond wasp, Eurytoma amygdali End[END_REF][START_REF] Plaut | On the biology of the immature stages of the almond wasp, Eurytoma amygdali. End. In Israel[END_REF][START_REF] Plaut | Studies of the behaviour, dispersal, and damage potential of the almond wasp, Eurytoma amygdali[END_REF][START_REF] Talhouk | Contributions to the knowledge of almond pests in East Mediterranean countries. V. The fruit-feeding insects, Eurytoma amygdali End, and Anarsia lineatella Z[END_REF][START_REF] Duval | Ravageur de l'amandier : mieux connaître « E. amygdali[END_REF] but there is no known phenological data of Eurytoma in the French climatic conditions. From 2005 to 2007, we have observed the adult emergence dates in three different places with the perspective of applying a reasoned chemical control. We tested a new insecticide in alternative to the Zolone which was the authorized product in France in 2005 against Eurytoma amygdali. This insecticide did not give the expected results and resulted in multiple insecticide sprayings by growers at inappropriate times.

MATERIEL AND METHODS

Emergence from cages.

The studies were conducted during the years 2005, 2006 and 2007. We put in wooden cages (fig 2) infested fruits from the previous year that had been picked the first week of March, from almond trees of three different almond orchards: Montfavet-Avignon (Vaucluse), St Didier (Vaucluse), Valensole (Alpes de Haute-Provence). The varieties in these orchards are Ferragnès, Lauranne and Ferraduel. The wooden cages were placed in an insectarium room opened to exterior. A hole was made in the cage in order adults are attracted by the light of the hole connected to a transparent plastic bottle. The emerged male and female adults in the bottle were counted every day and were removed.

Chemical control experiments. :

Insectarium tests: Two contact insecticides were experimented: the Zolone (Phosalone), the authorized insecticide and the Karate® Zeon that contains as active ingredient, a synthesized Pyrethroids lambda-cyhalothrine. A treatment of the two Field tests: Bottles with glass tube (Fig 3) with infested almond fruits were placed in the orchards for detecting the first adult emergences in the field. One or two days after the the first emerged male, Karate ® Zeon treatments were applied in the orchard. In a part of every orchard, a second treatment with the same insecticide was applied two weeks after the first treatment. At the harvest, the number of infested fruits was counted.

RESULTS AND DISCUSSION

Emergence dates

In Montfavet, the first emergence began on April 13 th in 2005, April 18 th in 2006, April 2 nd in 2007 (Table 1). The flowering date was also the earlier in this place because it is the warmer place. In Valensole, the first emergence was more one week later like the flowering date. The length of the emergence in every site was comprised beetwen 21 and 27 days excepting for one case, St didier in 2006 with 12 days. The figure 4 shows the typical distribution of the adult emergence observed in Saint Didier in 2005. The male emergence preceded the female emergence of 2 to 4 days and the ratio male:female was about one male for two females and was similar to the observed ratio in the other countries. The table 2 shows that the two insecticides have a good action against Eurytoma. The mortality rate was 100% the first day after the treatment. The contact of the insect on the treated leaves is sufficient to eliminate it. However, the Zolone was fully efficient only four days after the treatment and the Karate® Zeon was efficient still after more 23 days. We stopped the test because we did not have new emerged Eurytoma adults anymore. These results showed that a single treatment with the Karate® Zeon could cover the total emergence period of Eurytoma female which was observed between 20 and 26 days in the three years. It was necessary to check this hypothesis with chemical control experiments in the field.

Chemical control experiments in fields

The results of the experiments in fields are presented in the table 3. The two strategies, one single treatment applied just at the beginning of the emergence and the second strategy with a second treatment applied two weeks after the first, had a very good effectiveness with a low rate of infestation. The chemical control with a single treatment is cheaper and more advisable, but the optimal time for spraying at the first emergence has to be right.

  Comment citer ce document : Duval, H., Millan, M. (2010). Emergence dates of Eurytoma amygdali enderlein adults in the south-east of France and control strategy. In: XIV GREMPA meeting on pistachios and almonds (p. 175-180). Options Méditerranéennes. Série A : Séminaires Méditerranéens, 94. Presented at 14. Grempa Meeting on Pistachios and Almonds, Athens, GRC (2008-03-30 -2008-03-04). Paris, ESP : CIHEAM. Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript found now after Montpellier, but is not yet in the Roussillon area near Spain, neither in Corsica (fig 1).

Fig 1 :

 1 Fig 1: Distribution of Eurytoma amygdali in France.

  ., Millan, M. (2010). Emergence dates of Eurytoma amygdali enderlein adults in the south-east of France and control strategy. In: XIV GREMPA meeting on pistachios and almonds (p. 175-180). Options Méditerranéennes. Série A : Séminaires Méditerranéens, 94. Presented at 14. Grempa Meeting on Pistachios and Almonds, Athens, GRC (2008-03-30 -2008-03-04). Paris, ESP : CIHEAM. Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript insecticides was applied with a hand-sprayer on two almond trees of the INRA almond orchard in Montfavet on April22nd, 2006. Every day after this treatment, some almond leaves of these trees were picked up and placed in a new plastic box with Eurytoma adults newly emerged the same day from the wooden cages. 24h after the introduction of the Eurytoma adults and the treated almond leaves in the box, the mortality rate was recorded.

Fig 2 :

 2 Fig 2 : Wooden cages with bottle Fig 3 : Bottle with glass tube

  Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript Manuscrit d'auteur / Author manuscript

Fig. 4 .

 4 Fig. 4. Male and Female adult emergence Date, Saint Didier 2005

Table 1 .

 1 Emergence Dates in 2005, 2006 and 2007 in 3 localities.

			First
	Years and	Flowering	Emergence Date	Emergence
						length
	Localities	Date	Beginning	End	(days)
	2005
					09-
	Montfavet (84)	16-march	13-april	may	26
	Saint	Didier			12-
	(84)		19-march	18-april	may	24
					18-
	Valensole (04)	30-march	22-april	may	26
	2006
					09-
	Montfavet (84)	17-march	18-april	may	21
	Saint	Didier	18-march	23-april	05-	12
	(84)				may
	Valensole (04)	01-april	26-april	20-	24
					may
	2007
	Montfavet (84)	27-feb.	02-april	29-
					april

Comment citer ce document : Duval, H., Millan, M. (2010). Emergence dates of Eurytoma amygdali enderlein adults in the south-east of France and control strategy. In: XIV GREMPA meeting on pistachios and almonds (p. 175-180). Options Méditerranéennes. Série A : Séminaires Méditerranéens, 94. Presented at 14. Grempa Meeting on Pistachios and Almonds, Athens, GRC (2008-03-30 -2008-03-04). Paris, ESP : CIHEAM.

Table 2 .

 2 Retentiveness of the Karate® Zeon and the Zolone; (Chemical treatment applied on April 22nd).

			Eurytoma death rate
			after 24h contact with treated
	Observation Days after	leaves
	Date	chemical spray	Karate® Zeon	Zolone
	22-april	J	100%	100%
	23-april	J+1	100%	100%
	24-april	J+2	100%	100%
	25-april	J+3	100%	100%
	27-april	J+5	100%	85%
	29-april	J+7	100%	90%
	30-april	J+8	100%	30%
	04-may	J+12	80%
	08-may	J+16	100%
	12-may	J+20	100%
	15-may	J+23	100%

CONCLUSIONS

Our data show that a protection of the almond orchards against Eurytoma amygdali with a single treatment of the contact insecticide Karate® Zeon is possible. However almond growers have to be trained to detect the first adult emergence with field cages or field bottles, in order to apply the treatment at the optimal time at the first adult emergence.

The use of sex pheromone traps would be easier to detect the first male flights [START_REF] Katsoyannos | Monitoring populations of the almond seed wasp, Eurytoma amygdali, with sex pheromone traps and other means, and optimal timing of chemical control[END_REF][START_REF] Mazomenos | Evaluation of the major female Eurytoma amygdali sex pheromone components, (Z,Z)-6,9-tricosadiene and (Z,Z)-6-9-pentacosadiene for male attraction in field tests[END_REF]. In 2005, the two compounds, cited as sex pheromone by [START_REF] Krokos | Alkadienes and alkenes, sex pheromone components of the almond seed wasp Eurytoma amygdali[END_REF] were tested in our three experimental almond orchards with delta traps. No male were trapped, on the contrary of results of Mazomenos. We thought our compounds were not purified enough, but we have to go on these studies on sex pheromone traps.

To hope decreasing the populations of Eurytoma amygdali in the areas of almond growing, it is also important to remove the abandoned orchards and the infested wild almond trees. In France, it is a challenge to prevent the invasion of Eurytoma in the Corsica and Roussillon areas.


Impact of genotype, fruit ripening and UV-B radiations on phenolic profile of cherry tomato fruits

Michèle Loonis 1 , Nathalie Mora 1 , Marie-Noëlle Corre 2 , Hélène Gautier 3 , Jean-Luc Poëssel 2 and Claire Dufour Tomato or Solanum lycopersicum is one of the most widely grown fruits for consumption either as raw or cooked. Beneficial health effects have been attributed to its high content in micronutrients such as carotenoids, mainly lycopene and β-carotene, and vitamin C. Phenolic compounds, which constitute the most diversified class of tomato micronutrients, participate to the fruit quality by their contribution to the colour, taste and aroma, and, owing to their antioxidant properties, could also contribute to healthpromoting effects of tomato consumption. Different studies have shown that total phenolic content of tomato fruit is greatly affected by the genotype, stage of ripening and environmental factors. There is an increasing interest to study the variations of individual compounds according to these factors, especially in cherry tomatoes which are often used in genetic improvement for their high organoleptic quality.

The objectives of our study were to assess the impact of genotype on the phenolic profile of cherry tomato at two different stages of ripening (green vs red) and to examine tissue distribution of these compounds. The impact of UV-B on the content of phenolic compounds was also investigated.

Two cherry tomato genotypes, Wva 106 and Cervil, were grown in tunnels covered either with a film transmitting the whole solar radiations (+ UV-B) or with a film absorbing UV-B radiations (-UV-B). Fifteen fruits were sampled for each different condition. For the red stage, composition of the different tissues of the fruit was also studied. Epidermis, pericarp, both columella and placenta, jelly and seeds were separately collected. Fruit or tissue samples were frozen using liquid N2 before storage at -20°C. Samples were then freeze-dried before grinding to a fine powder, freeze-dried again, stored at -20°C before extraction by 70% aqueous EtOH. Contents of phenolic compounds in the extract were determined by HPLC and structural determination was achieved by HPLC/MS.

More than 70 phenolic compounds were detected in both genotypes in agreement with Moco et al. [1]. Chemically synthesized standards such as caffeic acid 4-Glc, coumaric acid 4-Glc and ferulic acid 4-Glc [2] allowed the quantitative determination of these compounds. Level of caffeoylquinic acids at the red stage was very different in the two genotypes where the content in chlorogenic acid for Wva 106 was found to be 20 times higher than in Cervil. In contrast, red fruits of Cervil exhibited di-and tri caffeoylquinic acid derivatives which were however not present at the green stage. In both genotypes, the chlorogenic acid content was very high compared to the content of large-fruited varieties given in the literature. Flavonoids, mainly represented as quercetin and naringenin glycosides, were only identified in the epidermis of Cervil. In the presence of UV-B, their content was statistically higher highlighting their screening role in fruit skin.

These results show that cherry tomato could be used in breeding program to create varieties with enhanced levels of potentially health-promoting phenolic compounds.


domain: sdv sde

text:
Sophie Moulin
email: moulin@laon.inra.fr

Martine Guerif

Frédéric Baret

Jean-Marie Machet

Physical measurements and signatures in remote sensing

Keywords: inversion, spatial heterogeneity, radiative transfer model, precision farming

Existing decision support system could be improved in terms of N fertilizer recommendations by taking into account the spatial and temporal variability in the soil and crop, especially at the within field scale. Remote sensing represents a great opportunity to consider the within field heterogeneity. One of the aspects is the characterization of the spatial heterogeneity in terms of soil and plant characteristics or state variables. In the frame of an experiment devoted to precision farming and more specifically to N fertilization, a methodology to estimate some crop biophysical variables from remote sensing information is proposed. We are especially interested in estimating the green leaf area index (GLAI), which characterizes the crop growth, and the chlorophyll content of the green foliage (Cab), which characterizes the crop nitrogen (N) status. The method consists in estimating these biophysical variables from spectral radiometric measurements, by inverting a radiative transfer model. The methodology was developed at local scale, for 6 levels of nitrogen fertilization, and upscaled at the field scale.

The study was conducted on a winter wheat field. Six test-sites (20 m x 10 m) were supplied with different fertiliser N rates : 0, 60, 120, 180, 240 and 300 kg/ha. The rest of the field (10 ha) received 240 kg N/ha, in 4 applications. Biological and radiometric measurements were performed both over the testsites and the whole field. An airborne spectro-radiometer (CASI) was used to measure spectral reflectances of the whole field with a 2 m spatial resolution and a 3 nm spectral resolution, in optical domain (350-1050 nm). The GLAI was estimated using a LAI 2000 and the crop N status with a N-tester equipment on 22 points spatially distributed on a grid over the whole field. A hand-held radiometer having the same technical characteristics than the airborne sensor was used to measure ground-based canopy spectral reflectances in the 6 test sites. The GLAI and the crop N status were also measured. Moreover, destructive measurements were performed at each flight day in order to determine the 'true' values of GLAI and chlorophyll content in each test site. A canopy radiative transfer model (SAIL) was coupled to a within-leaf radiative transfer model (PROSPECT) to retrieve GLAI and Cab from spectral reflectances, using soil reflectances parameterized versus measured soil moisture as model inputs.

This work was conducted in two steps. The first step consisted in the parameterization of empirical relationships and the calibration of the radiative transfer model using the test sites data. Destructive measurements were used to calibrate LAI 2000 and N-tester. Empirical relationships were built: i) between LAI2000 measurements and 'true' GLAI, ii) between N-tester values and 'true' chlorophyll contents. The radiative transfer model was calibrated by adjusting unknown model parameters such as mean leaf angle and minimizing the difference between simulated and measured variables on the 6 test sites. The second step consisted in extrapolating the method elaborated on the test sites to the whole field and validating it. We used the calibrated radiative transfer model to estimate GLAI and Cab over the field from airborne radiometric measurements. The results are maps of GLAI and Cab obtained with a 2 m spatial resolution. A comparison was performed in terms of GLAI and Cab on the 22 grid points.


est destinée au dépôt

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  Comparison of δ13C and WUE between seedlings of Quercus petraea and Q. robur subjected to different irradiance regimes and water availability levels Stéphane Ponton, Jean-Luc Dupouey, Nathalie Bréda, Erwin Dreyer To cite this version: Stéphane Ponton, Jean-Luc Dupouey, Nathalie Bréda, Erwin Dreyer. Comparison of δ13C and WUE between seedlings of Quercus petraea and Q. robur subjected to different irradiance regimes and water availability levels. 1. Rencontres, Jan 2001, Autrans, France. hal-02759090 Comment citer ce document : Ponton, S., Dupouey, J.-L., Breda, N., Dreyer, E. (2001). Comparison of 13C and WUE between seedlings of Quercus petraea and Q. robur subjected to different irradiance regimes and water availability levels. In: Ecophysiologie de l'arbre (p. 1 p.). Presented at 1. Rencontres, Autrans, FRA (2001-01-16 -2001-01-19).

  1


text:
Sophie Leguédois

Odile Yves Le Bissonnais

published or not. The documents may come

Aggregate stability as an indicator of interrill erosion processes


domain: sdv info

text:
F Clement

G Duchamp

J L Larry

M Vidament

Effects of frequency of insemination, number of spermatozoa and insemination site on fertility of equine frozen semen

One insemination with 400x10 6 total sperm into the uterine body close to the cervix (BOD) results in higher fertility than: 1) 4 inseminations within 24 h, in BOD, with 100x10 6 total sperm at each insemination, 2) 1 insemination with 50x10 6 total sperm in BOD or at the tip of the horn, ipsilateral to the preovulatory follicle, by a rectally-guided approach.

Introduction

We demonstrated that fertility with equine frozen semen was improved when the mares were inseminated more than once in a cycle before ovulation and that doses with 300x10 6 total sperm resulted in higher fertility than doses of 150x10 6 total sperm per AI [START_REF] Vidament | Equine frozen semen: freezability and fertility field results[END_REF]. The explanation of the positive effect of multiple inseminations is still unclear.

Numerous studies with either low dose of spermatozoa and/or deep uterine AI have been conducted recently with equine semen (reviews: [START_REF] Ball | Hysteroscopic and low dose insemination techniques in the horse[END_REF][START_REF] Morris | Low dose insemination in the mare: an update[END_REF]). Unfortunately, some of them are inconclusive because: 1) the comparison between groups is confounded with too many factors, 2) number of cycles and stallions are insufficient, 3) freezing technique is unspecified or invalid. There is a lack of comparison between these techniques and well established standard procedures [START_REF] Sieme | Effects of different artificial insemination techniques and sperm doses on fertility of normal mares and mares with abnormal reproductive history[END_REF].

Three studies were carried out: 1) to compare multiple inseminations during 24 h versus once, and 2) to compare 2 sites of insemination: the uterine body close to the cervix (BOD), and the tip of the horn ipsilateral to the preovulatory follicle by a rectally-guided approach (TIP).

Material and Methods

If not specified, sperm numbers are expressed in total number. Semen from saddle stallions was frozen (freezing extender: INRA82 + 2% egg yolk + 2.5% glycerol, final concentration of semen in 0.5 ml straws: 100x10 6 spermatozoa per ml) [START_REF] Vidament | Centrifugation and addition of glycerol at 22°C instead of 4°C improve post-thaw motility and fertility of stallion spermatozoa[END_REF]. Post-thaw rapid and progressive motilities of used ejaculates was 55% and 40%, respectively.

In experiment 1, mares were inseminated in BOD, 1 or 4 times, with semen from 4 different stallions. Two pairs of stallions were used: AB or CD. Mares were injected with hCG at 10.00 a.m. on Day 0. In the "1x400" group, mares were inseminated once with 400x10 6 spermatozoa (200x10 6 from one stallion and 200x10 6 from the second stallion of the pair) at 10.00 a.m. on Day 1. In the "4x100" group, mares were inseminated 4 times with 100x10 6 spermatozoa at each AI: at 5.00 p.m. on Day 0 and at 7.00 a.m., 1.00 p.m. and 5.00 p.m. on Day 1, either in the AABB order or in the BBAA order. Paternity of delivered foals was determined.

Comment citer ce document : Clément, F., Duchamp, G., Larry, J. L., Vidament, M. (2005). Effects of frequency of insemination, number of spermatozoa and insemination site on fertility of equine frozen semen. In:

Proceedings of the 4th International Symposium on Stallion Reproduction (p. 208-211). Animal Reproduction Science, 89 (1-4). Presented at 4. International Symposium on Stallion

In experiment 2, mares were inseminated twice with 400x10 6 spermatozoa per AI, 24h apart, with the last AI 12 h before ovulation. Semen of two stallions was used. The inseminations were performed either in BOD or at TIP with a special catheter (Minitüb, Germany).

In experiment 3, mares were inseminated once, 12h before ovulation, with either 400x10 6 spermatozoa in BOD, or 50x10 6 spermatozoa in BOD or 50x10 6 spermatozoa at TIP. Semen of 4 stallions was used. The inseminations in the two groups "50" were performed with a special catheter (IMV, France).

Differences between fertilities were tested with a categorical data analysis, considering effects of treatment and stallion (CATMOD, SAS, USA). Statistical significance was considered at P < 0.1 [START_REF] Amann | Weaknesses in reports of "fertility" for horses and other species[END_REF].

Results

Experiment 1. Per-cycle fertility was significantly higher in the "1x400" group (57%, 16/28) than in the "4x100" group (34%, 8/24) (P=0.08). Among pair of stallions AB, per-cycle fertility was 60% (9/15) in the "1x400" group, 33% (2/6) and 29% (2/7) in the "4x100" group for the AABB and the BBAA order, respectively. Among pair CD, per-cycle fertility was 54% (7/13) in the "1x400" group, 33% (2/6) and 40% (2/5) in the "4x100" group for the CCDD and the DDCC order, respectively. In the "1x400" group, the resulting foals were mainly from stallion A (7/8) in the AB pair and from stallion D (6/6) in the CD pair. The foals from the "4x100" group were very few in each pair (n=4 and 3) but all the stallions have sired foals.

Experiment 2. Per-cycle fertility was similar: 63% (17/27) in the "2x400 BOD" group versus 59% (16/27) in the "2x400 TIP" group (P>0,1). For stallion E, it was 67% (10/15) and 39%

(5/13), respectively. For stallion T, it was 58% (7/12) and 79% (11/14). No embryonic loss was observed between 14 and 35 days post-ovulation.

Experiment 3. Due to the overall low fertility of this experiment, the more fertile stallion was used more intensively to produce foals for the next breeding season. So the results had to be adjusted by stallions. Per-cycle fertility were significantly different between groups (P=0.06) (Table 1), with higher significance if the two groups "50" were pooled and compared to the "400" group (26% (78) versus 46% (39), respectively, P=0.02).

Discussion

The negative effect of 4 AI versus 1 AI in experiment 1 could be explained by the high number of interventions in the uterus during 24h that could have resulted in a more acute inflammation post-AI. Another explanation could be mechanical with losses of spermatozoa due to the contractions of the uterus after each AI and to losses in the 4 catheters used, resulting in a total lower number of spermatozoa. It was striking to observe that the foals from the "1x400" group were mostly from only one stallion per pair. This heterospermic experimental scheme could be very powerful to compare fertility between 2 stallions [START_REF] Amann | Weaknesses in reports of "fertility" for horses and other species[END_REF].

In experiment 2, fertility with 400x10 6 spermatozoa was similar, whatever insemination site used. In experiment 3, fertility with 50x10 6 was similar, whatever insemination site used. These results agree with some recent papers in which no improvement in fertility was found

Comment citer ce document : Clément, F., Duchamp, G., Larry, J. L., Vidament, M. (2005). Effects of frequency of insemination, number of spermatozoa and insemination site on fertility of equine frozen semen. In:

Proceedings for TIP versus BOD with different doses of frozen semen [START_REF] Squires | Simplified Strategy for Insemination of Mares with Frozen Semen[END_REF][START_REF] Sieme | Effects of different artificial insemination techniques and sperm doses on fertility of normal mares and mares with abnormal reproductive history[END_REF]review in Ball, 2004;[START_REF] Morris | Low dose insemination in the mare: an update[END_REF].

AI with 50.10 6 resulted in much lower fertility than AI with 400x10 6 which is consistent with our previous results.

Discrepancies between publications could result from factors like: proper fertility of stallions used, fertility of freezing technique used, number of AI, number of spermatozoa per AI and interval between AI and ovulation.

Table 1 :

 1 Per-cycle fertility in Experiment 3 a Different letters (a, b) within the row denote differences (P=0.06)Comment citer ce document : Clément, F., Duchamp, G., Larry, J. L.,Vidament, M. (2005). Effects of frequency of insemination, number of spermatozoa and insemination site on fertility of equine frozen semen.

		Insemination site and number of sperm per AI
		Uterine body	Uterine body	Horn tip
		(BOD)	(BOD)	(TIP)
		400x10 6 spz	50x10 6 spz	50x10 6 spz
	Stallions
	BAL	3/8 (38%)	2/8 (25%)	2/8 (25%)
	DOL	9/15 (60%)	6/15 (40%)	4/15 (26%)
	INT	2/8 (25%)	1/8 (13%)	2/8 (25%)
	HUR	5/8 (63%)	2/8 (25%)	2/8 (25%)
	Total	19/39	11/39	10/39
	Adjusted %	46% a	26% b	25% b
	a

In: Proceedings of the 4th International Symposium on Stallion Reproduction (p. 208-211). Animal Reproduction Science, 89 (1-4). Presented at 4. International Symposium on Stallion

Acknowledgements

To IMV for supply of catheters


Maximum entropy production and ecosystems

Roderick Dewar

To cite this version:

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  Roderick Dewar. Maximum entropy production and ecosystems: Maximum entropy production and ecosystems. Workshop on quantitative ecology, The Abdus Salam International Centre for Theoretical Physics (ICTP). ITA., May 2005, Trieste, Italy. 22 pl. hal-02759469 ������� ������ �������� ���� ��� ������������ �� �������������


Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" in forest trees

• The idea of compensation for change in environmental conditions :

short-term adaptation is physiological

• Quest of individual fitness or/and most probably of population fitness long-term adaptation is genetic

"The amount of heritable genetic variation is the ultimate determinant of populations' potential to respond and adapt to environmental changes" Definition

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" in forest trees

Tools

Quantitative genetics fundamental discipline in plant and animal breeding with extended application to evolutionary biology • knowledge on structure and location of specific genes non needed

• phenotypic resemblance between relatives

• description of genetic and environmental components of phenotypic variation of quantitative traits

P = + G + E + GxE μ Fisher 1918

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. Geographical structuration for adaptive variation in Scots pine effects of migration history or/and natural selection ?

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

Differentiation of Scots pine populations for adaptive traits

In provenance tests : F prov -test from ANOVA t = VBetween / (VBetween + VWithin) (Kremer, 1994(Kremer, , 1997) ) (Spitze, 1993) Neutral markers can't substitute direct measures of quantitative variation for adaptive traits in Scots pine (Karhu et al. 1996)

t' = t / (2-t) = VBetween /(VBetween + 2*VWithin) = G ST = Q ST

Tools : indirect prediction with marker loci

Direct assessment of adaptive variation is still needed for Scots pine and many other forest species

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

What could we learn from provenance tests ?

Tools : genetic variation within population

based on phenotypical approximation V w = within provenance variance of design-adjusted individual performances CV wp = 100 * sqrt(V w ) / X, corresponding coefficient of variation R w = t 90 -t 10 , range of design-adjusted individual performances r p = phenotypical matrix of correlations between traits if more than 50 to 80 unrelated individuals per population

Caution = overestimation of genetic adaptive variability !

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

How to measure (easily) usable genetic variation under sexual reproduction ?

Tools : genetic variation within population

G = A + D + I Fisher 1918

One of Fisher's key insights was that the genotypic value consists of a fraction that can be passed from parent to offspring and a fraction that cannot.

We can thus estimate the Breeding Value A for a parent by twice the deviation of his offspring from the pop mean

A = Breeding Value = 2 (μ pop -μ G )
Average effects of alleles i and j at locus k

A = Breeding Value

= Σ ( a i k + a j k ) k= 1 to n loci

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

How to measure (easily) usable genetic variation under sexual reproduction ?

Tools : genetic variation within population

Fisher 1918

Estimates of V A require known collections of relatives

• The amount of phenotypic resemblance among relatives for the trait provides an indication of the amount of genetic variation for the trait. • If trait variation has a significant genetic basis, the closer the relatives, the more similar their appearance • Easiest available collections of relatives for forest tree species: open pollinated progenies : half-sib, parent-offspring controlled crosses : full-sib, half-sib (polymix, nested /factorial design) vegetative copies : clones • Two key statistical ANOVA identities -Total variance = between-group variance (V Fam ) + within-group variance (V W ) -Variance(between groups) = covariance (within groups) 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

G = A V G = V A + D + I + V D + V I Comment citer ce document : Bastien, C. (

"Adaptive variation" within population

How to measure (easily) usable genetic variation under sexual reproduction ?

Tools : genetic variation within population

Half-sib progenies

V Fam = Cov (HS) V Fam = V A /4 4 V Fam gives an estimation of V A Full-sib progenies V Fam = Cov (FS) V Fam = V A /2 + V D /4 2 V Fam is an upper bound for V A
Coefficient of additive genetic variation CV A =100 * sqrt(V A ) /mean,

• Two key statistical ANOVA identities -Total variance = between-group variance (V Fam ) + within-group variance (V W ) -Variance(between groups) = covariance (within groups)

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

Tools : genetic variation within population

Narrow sense heritability h 2 = V A / V P

• heritability determines the degree of resemblance between parents and offsprings and thus determines the response to selection

• Heritabilities are functions of populations h 2 values only make sense in the content of the populations for which it was measured

Estimations of genetic variability measures in Estimations of genetic variability measures in Scots pine progeny tests : Data Scots pine progeny tests : Data

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

Tools : genetic variation within population

Genetic and environmental correlations

• Pleotropic effects of loci on both traits • Linkage desequilibrium which will decay over time 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

X Y A X E X A Y E Y

"Adaptive variation" within population

Tools : genetic variation within population

Genetic and environmental correlations

X Y A X E X A Y E Y r A r P Phenotypic correlation r E
Phenotypic (observed correlation) is a function of the heritabilities of the traits and the genetic and environmental correlations

r P = r A h X h Y + r E √ (1-h x 2 ) (1-h Y 2 )
Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

Haguenau

"Adaptive variation" within population

Tools : genetic variation within population

Prediction of response to natural/artificial selection in the whole phenotype

Informations needed :

• genetic variance of each trait V A

• genetic correlation or covariance of each set of traits r A • selection on each trait: vector of selection gradients β

X Y β 1 β 2 β negative genetic correlation between X and Y ΔP Environment 1 Environment 2
Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

• Genetic variability measures are available mostly for Scots pine populations from the continuous range covered by ice during last glaciation.

• Few differences between these populations are observed for the amount of genetic variability for adaptive, morphological and wood production traits.

• High level of within population genetic variability can be observed for complex traits such as volume growth or for pest resistance

• Most studies are based on "+" tree progenies : estimates of genetic variability of unselected populations are probably underestimates

• Few data are available on genetic variability for reproductive behaviour of Scots pine which is directly linked to fitness.

• Few multi-environmental evaluation of genetic variability within populations

Estimations of genetic variability measures in Estimations of genetic variability measures in Scots pine progeny tests : lessons and gaps Scots pine progeny tests : lessons and gaps

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

Tools : partitioning of GxE interaction

Genetic basis of phenotypic plasticity ?

Option 1 : phenotypic plasticity evolves in response to selection for plasticity genes per se

Option 2 : phenotypic plasticity is simply a by-product of selection favoring the expression of specific phenotypes in different environments

?

How phenotypic plasticity could be measured in multisite experiments

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

"Adaptive variation" within population

Tools : partitioning of GxE interaction

Informations collected on multisite experiments

E(G ij ) = μ + G i + E j + (GE) ij

Mean value over the range of sites

Site effect

Specific adaptation to a particular environment

Genotype. x Site interaction

General adaptation to the range of sites tested

Of interest only if GxE is limited

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. Scots pine within population general adaptability : GxE interactions limited to scale effects over sites but not clearly explained by genetic variability for nutrient efficiency (Gullberg and Vegerfors 1987, Jiang 1988,Jonsson et al. 1992)

Stability parameters experiment-dependent

Scots Pine Genetic variability for adaptability to Scots Pine Genetic variability for adaptability to different different environments environments

Comment citer ce document : Bastien, C. ( 2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

• Most studies concern general adaptation to a given range of environments and not specific adaptation to climatic, edaphic or silvicultural constraints.

• Environmental conditions of the European range of Scots pine forests must be described by pertinent covariates : latitude, altitude, longitude but also covariates describing selective pressures (frost, drought, wind, biotic aggressors, competition,…)

"

  Scots pine differentiation for adaptive traits" Tools : indirect prediction with marker loci genotype Qualitative information per locus A = nb alleles in the population or coefficient of allelic richness H e = 1-Σp i 2 , Nei genetic diversity or expected Heterozygosity within population N e = 1 / (1-H e ) , mean effective number of alleles per locus in the population G ST = 1 -H S /H T , Genetic Differentiation Coefficient between populations (Nei 1986)

  correlation of environmental deviations • Includes non-additive genetic effects • Arises from exposure of the two traits to the same individual environment Comment citer ce document : Bastien, C. (

  document : Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute."Adaptive variation" within populationTools : genetic variation within populationPrediction of response to natural/artificial selection in the whole phenotypeInformations needed :• genetic variance of each trait V A• genetic correlation or covariance of each set of traits r A • selection on each trait: vector of selection gradients βComment citer ce document : Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute."Adaptive variation" within populationTools : genetic variation within populationPrediction of response to natural/artificial selection in the whole phenotypeInformations needed :• genetic variance of each trait V A• genetic correlation or covariance of each set of traits r A • selection on each trait: vector of selection gradients β

  Scots pine provenance flexibility: a seed transfer guide for scandinavian populations(Eiche 1966, Eriksson et al 1980,Raymond and Lindgren 1990)E(Y) = A / (1-((X-B)/C) 2 ) X = site indexreflecting the relative site severity for volume production (described by latitude adjusted to a constant altitude) A = maximal performance of the provenance over the range of sites B = optimal site index for the given provenance C = change in the environment from the optimum which cause a 50% reduction in performance

  markers linked to adaptive traits And candidate loci involved in adaptive traits (ATL) Genetic basis of phenotypic plasticity Comment citer ce document : Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. Thank you very much for your attention Thank you very much for your attention Catherine Bastien INRA, UAGPF Orléans PROFOREST Workshop, Warsaw, 24-27 August 2004

"Adaptive variation" in forest genetic experiments Scots pine Provenance tests Ogiyevskii series 1910-1916 IUFRO international series 1937-1939, 1982 VNILM series 1974-1976 Tools : genetic variation in the natural range W.B. Critchfield & E.L. Little, 1966.

Specific adaptation Specific adaptation Growth potential Reproductive to abiotic factors to biotic factors potential

	frost resistance	resistance to pathogens opt. growth rhythm	Flowering ability
	(4 ref in Sweden)	(9 ref in Sw, Ge, Pl, Fr)	(3 ref in Sw)	(2 ref in Ru, Fr)
	drought resistance	resistance to insects	competition ability Seed maturation
	(1 ref in Es)	(4 ref in Sw,Pl, Ge, Fr)
	pollution resistance resistance to herbivores nutrient efficiency
	(0 3 ,S0 2 ,N0 x )
	(10 ref in Pl, Ge,Fi)	(3 ref in Fi)

Q ST ≅ 0.25 -0.55

Comment citer ce document : Bastien, C. (

2004

). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

Differentiation of Scots pine populations at marker loci Geographical area Nb pop. Nb. loci N A He Gst

							References
	Sweden	9	11 isoz.	4.36	-	0.008	Gullberg et al. 1985
	Finland	4	10 isoz.	-	0.34	0.002	Karhu et al. 1996
		5 4 2 4	3 RFLP 8 rDNA 2 microsat SNP 2phyto	3.0 -8.5 -	0.49 -0.77 -	0.02 0.14 0.014 no diff	Karhu et al. 1996 Karvonen and Savolainen 1993 Karhu et al. 1996 Garcia-Gil et al. 2003
	Scotland	14	16 isoz.	2.60	0.309	0.028	Kinloch et al 1986
	East and Central	16	7 isoz.	2.74	0.363	0.025	Prus-Glowacki and
	Europe						Stephan 1994
		30	3 RAPD	-	0.1-0.25	0.215	Nowakowska 2003
	Latvia, Ukraine,	18	21 isoz.	4.00	0.282	0.030	Goncharenko et al 1994
	Russia
	Ukraine, Western	13	8 isoz.	3.50	0.357	0.076	Prus-Glowacki and
	Siberia, Turkey						Bernard 1994
	Spain	7	7 isoz.	2.86	0.325	0.040	Agundez et al 1990
	Spain+France	14	11 isoz.	2.44	0.311	0.042	Prus-Glowacki et al. 2003
	Comment citer ce document :
	Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in
	Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots
	pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics",
	Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

Tools : indirect prediction with marker loci

	Genetic diversity
	mutation migration
	genetic drift
	Comment citer ce document :
	Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in
	Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots
	pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics",
	Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

low population differentiation high within population diversity Genetic variability mutation migration selective pressures high population differentiation for some adaptive traits still between 45% and 75% of genetic variability within population

of the distribution of environmental values

	Adaptive and	Age	Population	h 2	References
	production Traits		Progenies
	Frost resistance	1	"+" trees Full-Sib progenies	?	Nilsson and Andersson 1987
	Frost hardiness	1	"+" trees Full-Sib progenies	?	Norell et al 1986
	Bud-set phenology	1-3	"+" trees Full-Sib progenies	0.51	Mikola 1982
	Twisting rust resist	3	"+" trees OP progenies	0.70	Quencez etBastien 2000
	Height growth	6-11	"+" trees OP progenies	0.24-0.38	Krusche et al 1980
		13	random trees OP progenies		Poykko 1982
		16	random trees OP progenies	0.33	Bastien 1998, non publ.
		30	random trees OP progenies.	0.21-0.42	Eriksson et al 1987
	Diameter growth	11	"+" trees OP progeniesP	0.15	Krusche et al 1980
		16	random trees OP progenies	0.26	Quencez et Bastien 2000
	140 h 2 values measured in one environment may not be valid under another random trees OP progenies 0.27 Bastien et Kowalczyk 2003 30 random trees OP progenies 0.10-0.35 Eriksson et al 1987 interest of multisite evaluation to predict response to different selection pressures Branch angle 13 random trees OP progenies 0.12 Poykko 1982
		16	"+" trees Full-Sib progenies	0.20	Velling and Tigerstedt 1984
	140 • Heritability is a good to excellent predictor of short-term random trees OP progenies 0.35 Bastien et Kowalczyk 2003 response to selection BUT is completely unreliable for long-term Stem straightness 30 random trees OP progenies 0.13-0.23 Eriksson et al 1987
	response (over 5 to 10 generations) Wood density 33 "+" trees Full-Sib progenies	0.50	Hannrup and al 1998

• Heritabilities are also functions Comment citer ce document : Bastien, C. (

2004

). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

S i 2 , Shukla variance stability (1972) W i , Wricke ecovalence (1962) S i 4 , Hühn rank coefficient (1979)

	γ 1 , γ 2 ,., γ r

, r multiplicative terms of AMMI model (Gauch and Zobel 1988) (eq. PCA of GE terms) Stability parameters and predictive models bj , regression coefficient of Finlay and Wilkinson joint regression (1963) limit of linear model of interaction

	λ i 1 , λ i 2 ,.., λ i l , regression coefficients of
	factorial regression with sites
	covariates (Denis 1988)
	interest of environmental constraints covariates
	(drought index, site index, mean t°)

Potential measures of genetic variability Potential measures of genetic variability within populations of Scots pine within populations of Scots pine

Comment citer ce document : Bastien, C. (

2004

). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

Scots Pine genetic variability for adaptability: Scots Pine genetic variability for adaptability: lessons and gaps lessons and gaps More analyses of reaction norms or response curves is needed

  • Is Scots pine adaptability a matter of genotypic buffering (nb and variability of genetic components) or a matter of heterozygosity per se ? No real data availableComment citer ce document : Bastien, C. (2004). What might be useful measures of genetic variability for adaptive traits in Scots pine natural populations ?. In: Analysis of microsatellite sequences in Scots pine (p. p.). Presented at PROFOREST Workshop WP 5.4 on "New approaches on forest tree genetics", Sekocin, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute.

	What
	(Debat and David 2002,Sultan 2003)

might be useful measures of genetic variability for What might be useful measures of genetic variability for adaptive traits adaptive traits in Scots pine in Scots pine populations? populations? OBJECTIVES FOR THE FUTURE OBJECTIVES FOR THE FUTURE ATL diversity analysis over Scots pine natural range


Objectives of forest genetic field experiments

Keywords:

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Rij

To minimize for maximum precision (experimental designs)

Controlled experimental variation

Block +

To maximize for a better control of environmental variation

Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Breeding value A i

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute. Varsovie, POL : Forest Research Institute.

forest genetic field experiments

Adjustment for local environmental effects

Control of environmental variation

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

forest genetic field experiments

Adjustment for local environmental effects

Control of environmental variation by block effects

Example : analysis of total height of a clonal test in a 6 complete block design

P ij = μ + G i + b E(Ψr) + R ' ij Papadakis iterative method E(Ψr) = Σ R ' i'j' / n (r) i'j' P ' ij = P ij -b E(Ψr)

Iterative procedure

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL ( 2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Adjustment for local environmental effects

Control of environmental variation by spatial analysis

ANOVA Table 2003 on Total Height corrected by Papadakis

Reduced residual variation CV r = 12.8%

Neighborhood : 5 trees x 9 trees

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL ( 2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

-200 20 100 -200 20 100

Adjustment for local environmental effects

Control of environmental variation by spatial analysis

Example : analysis of total height of a clonal test in a 6 complete block design

Papadakis iterative method

Final choice : adjustment by spatial analysis and elimination of five rows in block 03

Adjustment by spatial analysis Adjustment to block effects

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL ( 2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Adjustment for local environmental effects

Control of environmental variation by spatial analysis Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL ( 2004-08-24 -2004-08-27).

Papadakis iterative method

Varsovie, POL : Forest Research Institute.

forest genetic field experiments

Estimation of breeding values

Estimation of breeding values and phenotypic variance components

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute. Varsovie, POL : Forest Research Institute.

Estimation of breeding values

Prediction of Breeding Values A i before genetic thinning in clonal seed orchards

A = b 2 P 2

Evaluation criteria

Open pollinated progeny performance P 2 b 2 = Cov( P 2 , A ) / var(P 2 )

b 2 = ½ V A / var(P 2 ) b 2 = ½ V A / (V Fam + V resid / n) Var(mean) = common variance + specific / n n = nb. ind in progeny b 2 = h 2 Fam = 2n 4 -h 2 h 2 n +

Heritability of progeny test b 2 depends on the number of progeny and on the heritability

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Estimation of breeding values

Estimation of breeding values

Prediction of Breeding Values A i before genetic thinning in clonal seed orchards

Estimation of variance components

Estimation of variance components

• Two key statistical ANOVA identities -Total variance = between-group variance (V Fam ) + within-group variance (V W ) -Variance(between groups) = covariance (within groups)

• One key genetic property of Fisher model (Kempthorne 1957)

X and Y , two individuals

Cov( X, Y) = 2 r XY V A + u XY V D
Open-pollinated progenies collected randomly in most Scots pine stands could be considered as a random sample of half-sib progenies

In practice

V Fam = Cov (HS) V Fam = V A /4 4 V Fam gives an estimation of V A

Estimation of variance components accoding to the experimental design

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Estimation of variance components

Estimation of variance components

Two methods

Restricted maximum likelihood estimation (REML)

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Estimation of variance components

Estimation of variance components

Expected means squares of Analysis of Variance (ANOVA)

Estimation of variance components

Estimation of variance components

Expected means squares of Analysis of Variance (ANOVA)

Estimation of variance components

Estimation of variance components

Restricted maximum likelihood estimation (REML)

Precision of variance component estimations depends on nb. of progenies

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Estimation of variance components

Estimation of variance components

Seed collection

Seeds

Realized genetic gain

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

R = P 1 -P 0

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute. This is a the response to selection, the change in the trait in the next generation (between-generation change) measured by

R = P 1 -P 0

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Prediction of response to selection

The Breeder's Equation R = h 2 S

• Note that no matter how strong S, if h 2 is small, the response is small • S is a measure of selection, R the actual response. One can get lots of selection but no response

Applications

• In agriculture and forestry breeding • Construction of divergent pedigree for QTL mapping and gene expression (microarray) analysis : inferences about nb. Of loci, effects and frequencies • Evolutionary inferences : correlated charcaters, effects on fitness, long-term response

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Prediction of response to selection

The Selection Intensity, i 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Prediction of response to selection

Selection on Trait 1, predicting response of Trait 2

R 2 = i 1 r A 1,2 h 1 h 2 σ p2
The correlated response

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Prediction of response to selection

A general formulation r = coancestry coefficient between candidate and ind. measured 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

(OP progeny parent-offspring r=1/4 ) X = trait selected Y= trait measured R = i ρ σ A X ρ = 2. r. r A X,Y . h ' Y .√ (n/[1+(n-1)t]) Ollivier,2002
Varsovie, POL : Forest Research Institute.

Response to selection

Response to selection with progeny testing Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Response to selection with progeny testing Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Response to selection

Response to selection with progeny testing

Forward selection R = 2 h 2 f S f = 2 i h 2 f σ Pf
Selection on 2 parents (male and female)

h 2 f = σ 2 f σ 2 f + σ 2 R /n σ 2 Pf = σ 2 f + σ 2 R /

Problem if unfavourable correlation

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Ind. sélectionnés

Index line

Multitrait selection : Independent Culling vs.

Index

Multi-trait selection Index Selection

Index Selection and technical weights

Index Selection I = w 1 A 1 + w 2 A 2 + … w q A q = [w'A] Varsovie, POL : Forest Research Institute.

Index Selection and technical weights

Response to Index Selection

I = w 1 A 1 + w 2 A 2 + … w q A q = [w'A] w = vector of technical or economical weights R = = R 1 R 2 . R k i w' M A √ w' M P w
Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Index Selection and technical weights

Response to Index Selection

Forward selection

Example : HUMPTULIPS Population W BudFlush TH Ang Br Def (-1,0,0,0,0) -55% 8.9% 1.8% 12% -19% (0,1,0,0,0) -24.4% 20% -0.5% -0.4% 9.9% (0,0,1,0,0) -4.4% -0.4% 22.5% 11.0% -3.9% (0,0,0,1 0) -32.2% -0.4% 12.1% 20.5% -16.3% (0,0,0,0,-1) -34% -6.4% 2.8% 10.8% -31% I = w 1 BudFlush + w 2 TH + w 3 Ang + w 4 Br + w 5 Def

Estimation of maximum relative genetic expected gains

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Index Selection and technical weights

Response to Index Selection Espected relative genetic gain %

Coefficient w5 with w1=0 w2=5 w3=2 w4=2

-400 -300 -200 -100 0

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Index Selection and technical weights

Response to Index Selection I = w 1 A 1 + w 2 A 2 + … w q A q = [w'A]

Total height Branch angle

Comment citer ce document : Bastien, C. ( 2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Sélection multi-caractères et Liaisons génétiques défavorables

Quels sont les effets?

•Augmentation de la variation du progrès génétique (imprévisibilité)

• Perte du mérite général

•

  Comparison of different populations of a given species for quantitative and qualitative traits expressed in forest conditions: provenance tests • Genetic evaluation in forest conditions of phenotypical selections : progeny tests (« + » trees open-pollinated progenies, polymix progenies, controlled crosses), clonal tests, multisite experiments • Backward selection in clonal seed orchard on multitrait evaluation in forest conditions of phenotypical selections : progeny tests (« + » trees open-pollinated progenies, polymix progenies, controlled crosses) • Forward selection on multitrait evaluation in forest conditions for long-term breeding strategies : progeny tests (« + » trees openpollinated progenies, polymix progenies, controlled crosses) • Evaluation of genetic variability of natural and artificial populations for quantitative and qualitative traits expressed in forest conditions :

  Test and adjustment for local environmental effects: • Efficiency of block designs • Correction with spatial analysis : Papadakis iterative method INTRODUCTION Prediction of Breeding Values A i before genetic thinning in clonal seed orchards Fisher's key insights : Each individual pass to its offspring a fraction of its genetic value which at a minimum is equal to ½ genetic additive value A 1 P 1 + b 2 P 2 + …+ b n P n + … + c n M m

  Test and adjustment for local environmental effects: • Efficiency of block designs • Correction with spatial analysis : Papadakis iterative method • 2 -Estimation of breeding values I = a 1 G 1 + a 2 G 2 + …+ a n G n Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. forest genetic field experiments PLAN • 1 -Test and adjustment for local environmental effects: • Efficiency of block designs • Correction with spatial analysis : Papadakis iterative method • 2 -Estimation of breeding values • BLUP's • variance components estimation • 3 -Multi-trait selection • Prediction of response to selection • Independent Culling vs. Index • Economic vs technical weights in selection index Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

  forest genetic field experiments Estimation of breeding values Prediction of Breeding Values A i before genetic thinning in clonal seed orchards Finding the optimal regression coefficients b n A = b1P1 + b2P2 + …+ bnPn Evaluation criteria Own performance P 1 b 1 = Cov( P 1 , A ) / var(P 1 ) b 1 = Cov( A+D+I+E, A ) / var(P 1 ) b i = h 2 b 1 = Cov( A, A ) / var(P 1 ) Y = f(X) = b X b= var(X) cov(X,Y) BLUP = Best linear unbiased prediction Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

  Prediction of Breeding Values A i before genetic thinning in clonal seed orchards M P = matrix of phenotypic variances-covariances b 2 = ½ M A M

  Restricted maximum likelihood estimation (REML) Example : analysis of total height and branch angle in a Scots pine progeny test Model : Y adj = μ + B lock + F amily + document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27). Varsovie, POL : Forest Research Institute. I = a 1 G 1 + a 2 G 2 + …+ a n G n Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL(2004-08-24 -2004-08-27).Varsovie, POL : Forest Research Institute.

•

  The response R is the betweengeneration change in the mean

•

  Selection can change the distribution of phenotypes. We typically measure this by changes in mean. This is a within-generation change measured by S = P s -P 0• Selection can also change the distribution of breeding values (changes in allele frequencies).

  Populations with the same selection differential (S) may experience very different amounts of selection The selection intensity i provided a suitable measure for comparisons between populations, 2 S = i h 2 σ p = i h σ A • Since h = correlation between phenotypic and breeding values Response = Intensity * Accuracy * Spread in V A Comment citer ce document : Bastien, C. (

  r A X,Y = genetic correlation between X and Y if different h' Y = heritability of the selection criterion (ind. Values, progeny means) n = nb. of measures on the candidate (nb. offspring per parent) t = correlation between observations on the same candidate

  44.8 cm R Y/X = -0.16

  1 A 1 + w 2 A 2 + … w q A qDisadvantage in one trait off set by advantage in the otherComment citer ce document : Bastien, C. (2004

  In general, weights on phenotypic information sources are not esay to « recognize » Comment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

  BudFlush + w 2 TH + w 3 Ang + w 4 Br + w 5 Def Simulation of expected genetic gains with varying w

Adjustment for local environmental effects Control of environmental variation by block effects

		Example : analysis of total height of a clonal test
		in a 6 complete block design
		TH.2003 in cm
		B03 ANOVA Table 2003 Total Height B04 400
			Df		SSE	300	MS	F-test	P-value
		Bloc B05	5	B02	603119 120624 72.36 200 TH.2003	0.000
		Genotype 354		1988304 5617	3.3692 0.000
		Residuals 1718 B06	B01	2864033 1667 100
							B01	B02	B03	B04	B05	B06
	0	200	CV r = 14.1% 400 cm Strong block effects !	bloc
	Comment citer ce document :
	Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In:
	Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST
	Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).
	Varsovie, POL : Forest Research Institute.

308.7 cm 283.2 cm 257.0 cm 281.7 cm 301.1 cm 300.0 cm

	block effects will control part of environmental
	variation. What does remain ?
	Comment citer ce document :
	Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In:
	Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST
	Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).
	Varsovie, POL : Forest Research Institute.

Adjustment for local environmental effects Control of environmental variation by block effects

  Example : analysis of total height of a clonal test in a 6 complete block design

A lot of plants with relative low height

					Plot(fitted,residuals)
		100
		50
		0					Analysis of
	Residuals	-50					residual variation
		-100
		-150	63	60	55		100	Quantile-Quantile plot of residuals
		200			250	300	350	50
					Fitted : bloc + genotype
							0
							Residuals	-50
		transplantation effect ? local environmental effects ?	-100 -150	60	63 55
							-2	0	2
							Quantiles of Standard Normal

Comment citer ce document : Bastien, C. (

2004

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

spatial distribution of residual variation

	Map of residual of Y=
	-200	20	100

μ+B+G+R Adjustment for local environmental effects Control of environmental variation by block effects

	Example : analysis of total height of a clonal test in a 6 complete block design
	Environmental variation still
	exist within block !
	Comment citer ce document :
	Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In:
	Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST
	Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).
	Varsovie, POL : Forest Research Institute.

Adjustment for local environmental effects Control of environmental variation by spatial analysis

  Example : analysis of total height of a clonal test in a 6 complete block design

	Environmental variation is
	measured by the neighborhood
	residual information (Ψr)

M A = matrix of additive genetic variances-covariances

		b 2 for A Total height age 15
	Total height age 15	0.562
	Total height age 15
	Total height age 10 Girth age 15	0.714
	Branch angle age 10
	From Bastien 1999, unpublished data

Comment citer ce document : Bastien, C. (

2004

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL

(2004-08-24 -2004-08-27)

.

Varsovie, POL : Forest Research Institute.

Table on Total Height adjusted to block effects Y'= Y -Block

	Bloc ANOVA Fixed	Df 41	SSE 100978 2463 MS	E(MS) V R + kφ bloc
	Random	Genotype 64	1039806 16247 V R + nV Fam
	Random	Residuals 1935	7260365 3752	V R
			Average n = 31.4 trees per progeny
			V R = 3752 VFam = (16247 -3752)/31.4 = 397.9 VA = 4*V F = 1591.7 ^ĥ 2 = 1591.7 / (397.9 + 3752) = 0.383

Example : analysis of total height and branch angle in a Scots pine progeny test

^

Comment citer ce document : Bastien, C. (

2004

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 2004-08-27).

Varsovie, POL : Forest Research Institute.

Total Height , Branch angle adjusted to block effects Y'= Y -Block

	MANOVA Fixed	Bloc	Df 41	SCPE -232.27 -5.66 MCP	E(MCP) Cov R + kφ bloc
	Random	Genotype 64	722.97	11.30 Cov R + nCov Fam
	Random	Residuals 1911	2423.75 1.27	Cov R
			Average n = 31.2 trees per progeny
			Cov R = 1.27 Ĉov Fam = (11.30-1.27)/31.2 = 0.32 Ĉov A = 4*Cov F = 1.28 ^r

Example : analysis of total height and branch angle in a Scots pine progeny test A = 1.28 /√ (1591.7 *0.45) = 0.047 ^ Comment citer ce document : Bastien, C. (

2004

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

lock + F amily + R esidual

		Fixed	Random Random
		Total Height	Branch angle
	V Fam	411.86		0.116
	Sd(V Fam )	95.21		0.024
	V R	3753		0.609
	Sd(V R )	29.33		0.020
	h 2	0.395		0.640
	Sd(h 2 )	0.085		0.051

Example : analysis of total height and branch angle in a Scots pine progeny test Model : Y adj = μ + B

selection : Independent Culling vs. Index Multi-trait selection Independent Culling

  nComment citer ce document : Bastien, C. (2004). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL(2004-08-24 -2004-08-27).Varsovie, POL : Forest Research Institute.

	Response X Total height 0.395 411.86 3753 2 0 2 5 Multitrait Selected Individuals h 2 σ 2 Fam σ 2 R 5 1 0 1 5 800 Culling point 1 600 650 700 750 Culling Point 2 Total Height age 8	h 2 f = 0.767 Pf =537 0.04 σ 2 0.10 0.12 0.06 0.08 Volume age 15
	Rx = 62.4 Earliness of budflushing (days)	-29 Wood density (Pilodyn) -28 -27 -26 -25 -24 -23

Independent Culling vs. Index Index Selection vs. Independent Culling

	Theoretical comparisons	Practical considerations
	If same total of nb. of	•Index selection:
	individuals measured on all	-must keep all individuals until
	traits:	all traits measured
	genetic gain	-cull in one stage
	Index S > Independent Culling > Tandem selection	•Traits differ greatly in costs to measure
		•Traits differ greatly in age of
		evaluation
		•Selection intensity may be
		greater for multistage (culling)
		selection

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.

Multitrait selection :

Comment citer ce document : Bastien, C. (

2004

). Statistical analysis of forest genetic experiments. Some key points. In: Analysis of microsatellite sequences in Scots pine (p. 145-158). Presented at PROFOREST Workshop on "New approaches in forest tree genetics", Varsovie, POL (2004-08-24 -2004-08-27).

Varsovie, POL : Forest Research Institute.


NOM-Metal Complexation A537

Fundamental aspects of interaction between metals and humics in the environment

W.H. VAN RIEMSDIJK1 AND L.P. WENG2 1 Dreienplein 10 Department Soil Quality, Wageningen University, The Netherlands (willem.vanriemsdijk@wur.nl) 2 Dreienplein 10 Department Soil Quality, Wageningen University, The Netherlands (liping.weng@wur.nl)

Metal ion interaction with humic substances is pH dependent, and the pH dependence has to obey the thermodynmamic consistency principle. One of the simplest models in this respect is the pH dependent Freundlich model. Such models have their limitation, because they can not easily be extended to include metal-metal competition and moreover the basic proton buffering behavior of humics is not icluded in the simplified models. The NICA-Donnan model and model V/VI do link the basic charging behavior of the humics with competitive metal ion binding. The NICA-Donnan model has been applied to model metal ion binding and mobility in soils with quite some succes. Especially the possibility to measure the free metal ion at very low concentration with the recently improved DMT technique is very helpful to test the quality of the models. The mobility of metal ions will be affected by the binding to DOC and by the binding to the immobile phase. The DOC concentration can be influenced by the binding of the DOC to the immobile mineral phase. Metal ions may also interact with humics that are in close association with mineral particles. The DOC-mineral-metal interaction process is in our opinion the next frontier for a better understanding of the mobility of metal ions in the environment. Minerals have a rather complex surface chemistry, and to combine this type of chemistry with the also rather complex chemistry of humics is an enormous challenge. A first attempt in this direction has been the development of the LCD model, which combines the NICA-Donnan model for humics with the CD-MUSIC model for metal(hydr)oxides. This model has been applied to fulvic acid binding to goethite. Extension of this model to humic acid binding has so far been an unresolved challenge. We will show a new theoretical approach that will probably allow to solve this challenging problem.

Influence of SOM on aluminium mobility in a forested brown acidic soil: A view from soil solutions held at different matrix potentials

F. GÉRARD 1 , J. JAFFRAIN 1 , J.-P. BOUDOT 2

We studied a number of soil water samples held at different matrix potential from the surface horizons of a brown acidic forested soil. The matrix potential can be converted into an equivalent pore diameter. Solutions have been analysed for total chemistry in major elements, pH and total inorganic monomeric Al. We used the WHAM VI speciation model to calculate Al speciation, by fitting results to the mesured pools of inorganic monomeric species.

Results are shown in the figure below. Black symbols represent solutions collected beneath the litter layer (0 cm), white symbols stand for solutions collected at 15 and 30 cm depth by mean of tension lysimeters (matrix potential; |ψ| < 600 hPa), and grey symbols are for solutions held by centrifugation (1800 hPa < |ψ| < 16000 hPa) at the 0-15 cm and 15-30 cm depth intervals. We found that Al mobility in solutions collected in the larger soil pores (tension lysimeters) are controlled by the neoformation of poorly crystallized Al-hydroxides, likely to be interlayer Al. In smaller pores (centrifugation) and especially those from the top soils, which contain more acidic water, a control by Al 3+ -H + exchange reactions with SOM is found. The maximum control by SOM is consistently found beneath the litter layer.

INRA Nancy, BEF, 54280 Champenoux, France

CNRS Nancy, LIMOS, 54501 Vandoeuvre, France