Teacher’s Notes 4.2 Does selective logging degrade the...

Teacher’s Notes 4.2 Does selective logging degrade the genetic quality of succeeding generations through dysgenic selection?

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Forest Genetic resources traininG Guide

MODULE 4 Forest Management

Teacher’s Notes 4.2

Does selective logging degrade the genetic quality of succeeding generations through dysgenic selection?Jonathan Cornelius

Acknowledgements

The editors of this Forest Genetic Resources Training Guide wish to thank Jarkko Koskela and Barbara Vinceti for their contribution in identifying the need for the guide and for their continuous support during its preparation. We acknowledge the important advice from a reference group of scientists at Bioversity International - Elizabeth Goldberg, Jozef Turok and Laura Snook - who at various stages supported this project.

This training guide was tested during several training events around the world. We would like to acknowledge the valuable feedback received from many students and their teachers.

We would like to give special thanks to Ricardo Alía, National Institute of Agriculture and Food Research (INIA), Spain, for his review of the Case studies presented in this module.

The photos and maps in the PowerPoint presentation are the copyright of Jonathan Cornelius, Leonardo F. Freitas, Josiah Townsend and the American Geographical Society.

Finally, the production of the Forest Genetic Resources Training Guide would never have been possible without the financial support of the Austrian Development Cooperation through the project, ‘Developing training capacity and human resources for the management of forest biodiversity’, implemented by Bioversity International during 2004-2010. We would also like to thank the European Commission-funded “SEEDSOURCE” project for additional financial support.

All cover illustrations were drawn by Rosemary Wise and the layout was created by Patrizia Tazza. We are grateful for their beautiful work.

in collaboration with

Financed by

Citation:

Cornelius J. 2014. Does selective logging degrade the genetic quality of succeeding generations through dysgenic selection? A case study and teacher’s notes. In: Forest Genetic Resources Training Guide. Edited by Boshier D, Bozzano M, Loo J, Rudebjer P. Bioversity International, Rome, Italy.

http://forest-genetic-resources-training-guide.bioversityinternational.org/

ISBN 978-92-9043-994-3 ISSN 2223-0211

Bioversity International Via dei Tre Denari, 472/a 00057 Maccarese Rome, Italy © Bioversity International, 2014 Bioversity International is the operating name of the International Plant Genetic Resources Institute (IPGRI).




1

Module 4Forest Management

Teacher’s notes 4.2

Does selective logging degrade the genetic quality of succeeding generations through dysgenic selection?

Jonathan Cornelius, World Agroforestry Centre (ICRAF), Lima, Peru

Introduction

These Teacher’s notes aim to assist teachers in using Case Study 4.2 Dysgenic selection: can logging degrade the genetic quality of succeeding generations? in the classes. The notes:

• describe the key concepts covered in the case study, referring to forest genetics textbooks and other sources where explanations can be found (full references are given at the end of these notes)

• give tips on how to prepare and run the exercise and discuss the main learning points (genetic and other) that students should be able to derive from the case study

• outline the PowerPoint presentation, which introduces the case study to the students, and provides commentary the teacher can use (the presentation contains pictures of the species, sites where it occurs, relevant land-use issues in the area and figures/tables from the exercise)

• include an explanatory commentary on the case study document• summarize key elements to be covered in the tasks.

The case study document is intended to be a stand-alone document, assuming that students are undergraduates or graduates in forestry (or in related disciplines). However, prior reading on basic quantitative genetics (polygenic traits, response to selection) might be advantageous (see, for example, Jansson 2005).

Support materials are provided on the accompanying DVD and are available on the Forest Genetic Resources Training Guide webpage at www.bioversityinternational.org

These include:• The case study• The Teacher’s notes• The Teacher’s PowerPoint presentation.

Key concepts to cover/introduce in this case study

General conservation• Selective logging: see FAO et al. (2001, pp. 14–18, 25–231).Genetic concepts• Dysgenic selection: see FAO et al. (2001, pp. 20, 26–31); FAO et al. (2004a,

p. 104); FAO et al. (2004b, pp. 18–19); Finkeldey (2005, pp. 177, 181–198); Geburek and Turok (2005, pp. 443–444).

http://www.bioversityinternational.org

Module 4 Forest Management

2

• Heritability and genetic gain: see Jansson (2005); Walsh and Lynch (2008a; 2008b).

There is widespread perception of dysgenic1 selection as a threat to forest genetic resources, based on the belief that species or populations will degenerate if only the ‘worst individuals’ reproduce. However, this perception is largely the result of the simplicity and apparent reasonableness of the central belief rather than being based on experimental observations or study. Indeed, there are no proven examples of dysgenic selection having occurred, at least in the forestry sector, and the necessary conditions for it to occur in a forest management context appear to be rather stringent. This exercise aims to lead students towards this conclusion, while fulfilling two specific learning objectives:

• That the student should be able to identify situations in which dysgenic selection is likely to occur (or not occur)

• That the student should be able to explain to forest managers, certifying agencies and others why a given silvicultural regime might or might not lead to dysgenic selection.

As dysgenic selection is a form of phenotypic selection, the potential for dysgenic selection is explored using the framework of the ‘breeders’ equation.’ This equation encapsulates the theory of phenotypic selection on quantitative traits and facilitates a clear and logical presentation of the issues.

The case study includes background material on:• the breeders' equation• mahogany ecology and genetics• the mahogany-rich Marajoara site in Brazil.

How to run the exercise

The exercise can be run in a number of ways, depending on the time available, size of the class and level of knowledge of the students. The approach described below corresponds to a three-hour block session, e.g. during a training course or university practical class. In each case, the exercise is likely to work best if students work in groups of three to five and no more than six. Teachers should distribute the case study document at least 48 hours before the scheduled session. Careful reading of the document will take up to one hour and should be completed before the class. Teachers and any assistants should be fully familiar with both the case study and these Teacher’s notes.

• Introduction: Begin the session by using the PowerPoint presentation to introduce the theme and the exercise (30 minutes). The presentation is intended as an overview and ‘appetizer,’ rather than as an exhaustive briefing. The table in Annex 1 describes the function of each slide and includes a commentary and notes that presenters may find useful. Teachers should encourage students to ask questions during the presentation rather than simply reciting the text to them. The text is also included on the notes panel of each slide.

• Group work: The group work focuses on three tasks: Task 1. To discuss whether, in this logging operation, dysgenic selection would be likely to

1 Students may question whether “dysgenic” is a real word! The term dates from the early 20th century, and was initially used in the context of human societies and genetics. For example, the novelist Aldous Huxley referred to “dysgenics—the carrying on of the species by the worst members”. “Dysgenics” is the opposite of eugenics, i.e. selective breeding to improve the genetic quality of the human race, which was widely advocated in the late 19th and early 20th centuries, but has since been recognized as both unethical (at best) and based on dubious scientific assumptions. Neither term is derived directly from “gene”, which came into use later.


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occur; Task 2. To formulate a general set of risk factors that would suggest susceptibility to dysgenic selection; Task 3. To discuss the consequences of dysgenic selection. Assign one of the three tasks to each group (but note that more advanced students may be able to cover Task 1 or 2 and Task 3). Students should discuss the case study amongst themselves, responding to the specific points and assigned tasks. The teacher should be present to answer questions (45 minutes discussion, 15 minutes to prepare presentations).

• Presentations and teacher feedback: Each group presents the outcomes of its work (10 minutes per presentation, with around 5 minutes after each presentation for questions and comments from the rest of the class and the teacher (based on five groups; more time can be allocated if there are fewer groups).

There are a number of alternative approaches to running the exercise. In the context of a training course, groups could be asked to reconvene to make their presentations the following day. In a university context, all three tasks could be assigned to each group as a take-home assessment task for completion over all or part of a one-semester course. In this case, one 50-minute lecture period could be devoted to the introduction and preliminary discussion.

Notes and commentary by case study headings

IntroductionThis section introduces the concept of dysgenic selection, noting that the conditions under which it might occur are not as widespread as might be expected. It then states the tasks and learning objectives.

Exploring dysgenic selection: response to selection and the ‘breeders’ equation’The breeders’ equation is used to predict response to selection. For this reason, it is important to explain clearly what we mean by the ‘response to selection.’ The approach taken here is to begin with realized response, as this is easily understood. We use an example from tree improvement because (a) tree improvement techniques may be familiar to some students and (b) there are no available examples of realized response to dysgenic selection. The idea that, just as tree improvement produces a positive response to selection, dysgenic selection produces a negative response has already been presented in the introduction and should be readily appreciated here.

Some students may struggle with the concept of response to selection as a genetic response because it is measured on phenotypic values. One way to deal with this is to explain that, at a given site, genetic and environmental deviations from the phenotypic mean would sum to zero and that therefore genetic and phenotypic means are identical. However, that concept would probably only be grasped readily by students who had already understood the initial point. A more effective approach would be to ask “what other factors could have caused the response?” and then, if necessary, point out why the approach to measuring the realized response in fact rules these out.

The response to selectionThe general approach mentioned at the start of this section describes improvement from one generation to the next. Some students may notice that in the example given in Box 1 both seedlots come from the same generation. It may be necessary to point out that it is the improved progeny that would actually be carried forward to form a new generation. The “SSO [seedling seed orchard] routine” seedlot represents what would happen if the parental population were used to form a new generation without any selection being applied.


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Predicting response: the breeders’ equationThis section introduces the breeders’ equation, providing a simple form of the equation before going on to discuss its application in subsequent subsections.

Selection differentialThe selection differential (S) is commonly expressed in units of the phenotypic standard deviation, i.e. as the selection intensity. This approach has two advantages: (a) it permits direct comparison of the strength of selection in different traits, or in the same trait when populations have different standard deviations, and (b) under truncation selection (i.e. when all individuals to the right or left of a given point in a frequency distribution are selected), values can be derived from the proportion selected, assuming that values of the trait in question are normally distributed.

In spite of these advantages, we use the unstandardized selection differential here, i.e. expressed in terms of the measurement units rather than the standard deviation units of the selection intensity. We have chosen to do this because using selection intensity would add complexity (truncation selection, normal probability function, an extra term in the breeders’ equation). This is because selection intensity rests on a dubious assumption (normal distribution), and because it would give an erroneous impression that dysgenic selection is necessarily truncation selection. In any case, the selection differential is a more readily understandable measure of phenotypic superiority.

Students often confuse the selection differential with the response to selection. The key here is to stress that S is a phenotypic, within-generation difference, whereas response to selection (R) is a genetic and between-generation difference.

HeritabilityStudents frequently have problems with heritability concepts. The familiarity and the common use of the word ‘heritable’ cause problems; students may wrongly assume that, because they know the meaning of ‘heritable,’ they also know the meaning of ‘heritability.’ This misunderstanding should be addressed by ensuring that the students read the case study document carefully. In their interactions with individual groups, teachers may find it useful to introduce a parent–progeny regression concept of heritability, and/or the concept of heritability as the coefficient of determination in a regression of genotype and phenotype. However, both approaches assume additional knowledge and the teacher will need to assess whether the students possess such knowledge.

The breeders’ equation applied to dysgenic selectionThe example used is hypothetical, partly to facilitate learning and partly to stimulate thinking about the factors that might mitigate apparent dysgenic selection in real situations.

Case study species and case study site and management regimesThese sections provide a reasonably complete account of the case study species, site and management regimes. The information provided is sufficient for the students to appreciate the context and to respond to the tasks. Not all the details included are needed to do the tasks; students will have to distinguish directly relevant information from less relevant data and background details to complete the tasks successfully.

Note that the scenario presented is based on logging at Marajoara, rather than being an exact case study. As is pointed out in the case study document, a ‘business-as-usual’ scenario would probably lead to zero regeneration. In that case, dysgenic selection would be unimportant.


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Notes on the tasks

Task 1. Discuss whether, in this logging operation, dysgenic selection would be likely to occurThe best way to approach this question is by working backwards from hypothesized postlogging regeneration. You can guide the students by posing a number of questions, as follows:

Where will regeneration be found?Postlogging regeneration is likely to be made up almost exclusively of seedlings in the cleared areas around remnant trees, as elsewhere most seedlings will be shaded out.

Which trees will be the seed parents of the regeneration?Clearly, remnant trees will be the seed parents of all, or practically all, of the seedlings.

Which trees will be the pollen parents of the regeneration?As mahogany trees are usually outcrossing (see ‘Ecology’ in the case study), remnant trees are unlikely to be both pollen parents and seed parents of seedlings in their immediate vicinity. Based on the information given under the heading ‘Regeneration and management’ in the case study, and assuming that the logging that occurred between 1992 and 1994 was completed in one season, there are six flowering events that could give rise to seed during the ‘regeneration window’ afforded by opening the canopy around the remnant mother trees: the first would occur in the dry season before felling, the second following felling, and then annually in the years corresponding to the four subsequent annual weedings. Logged trees could contribute to the first of these, but not to the others. Populations around Marajoara had already been heavily logged, so it is unlikely that a significant proportion of pollen parents in any of these six events came from trees in the original populations.

Given the expected parentage of the regeneration, what is the selection differential?Some groups may choose to disregard the contribution of logged trees, as this would occur in just one of six flowering events. They could then proceed to calculate selection differential based only on the mean diameter at breast height (dbh) of remnant trees:

Selection differential (S) = mean dbh of remnant trees –mean dbh before logging

S = 41 cm – 67 cm = –26 cm.

Some groups may take other approaches. For example, the annual variation in fruit production mentioned in the case study may imply annual variation in flower production. So, if the dry season before felling (that is, the year in which logged trees would have been able to contribute as pollen parents) were a heavy-flowering year, then the influence of logged trees would be greater than if it were a year of little flowering. Furthermore, if the role of logged trees as pollen producers is to be taken into account, then groups might attempt to allow for differential contribution by different size classes. One approach would be to weight size classes crudely using the near four-fold greater fruit production of trees in the >60 cm dbh class (assuming proportionality of flower and fruit production).

The prelogging mean dbh of trees ≤60 cm dbh and >60 cm dbh was 40.6 cm and 83.6 cm respectively. There were 804 and 1609 stems respectively in these two broad size classes (values can be estimated from Figure 1 in the case study document). If trees in the >60 cm dbh group produce, on average, three times as much pollen as those in the ≤60 cm dbh group and they are approximately


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twice as numerous, then in the calculation of weighted mean dbh of pollen parents contributing to postlogging regeneration in that year, the former would be accorded a weight six times as great as that of the latter:

[40.6 + (83.6)6]/7 = 77.46 cm]

Consequently, the selection differential for the same year would be:

S = mean dbh of pollen and seed parents of next generation – unlogged population mean dbh

S = (77.46 + 40.6)/2 – 67 cm = 59.03 – 67 = –7.97 cm

The overall selection differential applying to the future regeneration would be the mean over the six flowering events. One possible estimate of selection differential (S = –20.0 cm) is shown in Table 1, in which it is assumed that two of the years (the first, to which logged trees contribute, and year 5) are heavy-flowering years in which flowering and fruiting are four times the long-term mean. Here, no within-year, between-size class weighting has been applied for the second and subsequent years, because after logging there is only one size class in the higher fertility group >60 cm dbh). Very ambitious groups might decide to tackle this issue by assuming some continuous relationship between size class and reproductive contribution, such that there are differences in reproductive contribution between the ≤60 cm dbh classes. Arguably, unlogged population mean dbh should also be calculated by weighting the contribution of different size classes; this would give higher values of the selection differential.

Table 1. Illustration of calculation of average selection differential over six years

Year 11 Year 2 Year 3 Year 4 Year 5 Year 6

Weighting factor for flowering2

4 1 1 1 4 1

Mean dbh of parents of regeneration3

59.03 41 41 41 41 41

Selection differential (cm)

−7.97 −26 −26 −26 −26 −26

Mean selection differential = [(-7.97)(4) − 26 − 26 − 26 − (26)(4) − 26]/12 = −20.00 cm

1 Year 1 corresponds to the flowering season before felling.2 Assuming that trees produce on average four times as many fruits in heavy-flowering years as in normal

years.3 Mean in Year 1 reflects contribution of subsequently logged trees, which have a higher mean and are

assumed to have higher pollen production (see text).

What are the likely heritability values?Following the calculation of selection differential, groups will need to make assumptions about the value of the heritability for growth traits, based on the comments in the ‘Heritability’ and ‘Genetics’ sections of the case study. Values less than or equal to 0.1 would appear most reasonable, as hinted at in the case study. Based on this, they should conclude that dysgenic selection is unlikely to be significant, principally because of low heritability values.

Teachers might also point out the implications of variation in fertility even between trees of similar dbh (even when, as is the case here, only trees that produce ≥25 capsules are considered). The implication is that in each size class relatively few trees actually make a significant reproductive contribution. This


7

decreases the reliability of heritability as a guide to the relationship between phenotype and genotype. Consequently, the dysgenic response could be either lower (including zero) or greater than predicted.

How might the logging reforms introduced in 2003 affect your conclusions?As far as dbh is concerned, the 2003 reforms should further reduce the likelihood of dysgenic effects. Assuming the new regime is adequately overseen, no trees ≤60 cm dbh would be logged and larger numbers of trees ≥60 cm dbh would be retained (i.e. around 205, based on five trees per 100 ha over the total area at Marajoara of 4100 ha). However, the lack of restrictions on the form of seed trees is likely to mean that these are the worst formed of the legally harvestable trees. These 205 seed trees about 17% of the remnant trees; the others (the 1000 trees that are <60 cm) are expected to be of average form (because they were left on size criteria), implying that around 17% (202/1205) of the remaining trees are likely to be poorly formed trees of relatively high average fertility (because they are relatively large). It is possible, therefore, that without further fine-tuning, the new regime might lead to an increased probability of dysgenic selection. However, further study would be needed before concluding that there is a major risk of this occurring.

Task 2. Formulate a general set of risk factors that would suggest susceptibility to dysgenic selectionA model answer is provided below (Figure 1). Some groups may arrive at something similar without any guidance beyond the template included in the case study document.

PROCESS OR CHARACTERISTICS RISK FACTORS EXPLANATION

HARVESTING REGIME

1.Remnant trees are strongly inferior in one or more phenotypic characteristic: logging not highly selective

The less selective the logging, the more likely loggers are to take everything but the worst. If remnant trees are not inferior, then there

can be no dysgenic effect

SURROUNDING POPULATIONS

REPRODUCTIVE ECOLOGY

GENETICS

2. Logging is large-scale, with many remnant trees; or multiple small-scale operations with similar logging

criteria

3.Logging is carried out before flowering or before seed dispersal

4.No nearby populations of the same species, or only logged populations

6. There is little pollen flow (inter- or intrapopulation)

7.There is no seed bank or there is little advance regeneration

9.Inferior remnant trees are highly fertile

11.Selected trait(s) moderately or strongly genetically controlled

10.Selected trait(s) has high genetic variation

12.Trait non-quantitative with simple Mendelian inheritance, little environmental effect on phenotype

With small numbers of selections, mean phenotype is a poor guide to mean genotype. However, small numbers of remnants implies

unpredictability rather than absence of effects

No opportunity for logged trees to contribute to subsequent generations from “beyond the grave” (either through pollen or seed)

8.Logged trees do not coppice

No mitigating gene flow from unlogged populations

Implying that their contribution to future generations will not be outweighed by smaller numbers of non-inferior but more fertile trees

All implying that future generations will be derived solely or very largely from remnant trees

In a highly variable population, the worst trees are likely to be more inferior than in a less variable population

In many cases, genetic control of commercial traits is weak. In such cases, dysgenic effects between successive generations will be

negligible

Could produce strong dysgenic effects between successive generations. Possible example: destructive harvesting of aguaje palm

5.Logged species is a facultative or obligate selfer

Figure 1. Risk factors for dysgenic selection, classified according to four classes of process or characteristics.


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Task 3. Discuss the consequences of dysgenic selection and how it can be mitigatedIs dysgenic selection a conservation genetics issue?The question is meant to be provocative. Nevertheless, in the case of quantitative traits, and given both that selection on any one locus is weak and that this is reduced still further by low heritabilities, changes in allele frequencies over a few generations are likely to be negligible. Although a large number of such negligible changes can have a perceptible effect on the mean value of the trait selected for, there is little chance of a given allele being lost due to selection, particularly at realistic levels of heritability and over the number of generations applicable in the case of long-lived organisms such as timber trees.

To say that dysgenic selection is not a conservation genetics issue would overstate the case, but at least in timber trees it appears likely to be of limited short-term importance. Its importance has probably been overstated in the past.

If dysgenic selection occurs, how can it be mitigated or reversed?Groups should be thinking in terms of both management (given that most commercial traits are heavily influenced by environment as well as genetics) and genetic measures. Mitigation could be through silvicultural techniques such as thinning, pruning and fertilization that can be used to improve product quality and quantity. Positive selection could reverse dysgenic selection by being built into forest management regimes or by being implemented through supplemental planting with improved or ‘average’ stock. However, even such simple measures may be difficult to achieve where institutions (either executing or enforcing) are weak.

Further information

Cornelius JP, Navarro CM, Wightman KW, Ward SE. 2005. Is mahogany dysgenically selected? Environmental Conservation 32:129–139. (This is a useful reference for instructors, but should not be given to students until after completion of the exercise).

FAO, DFSC, IPGRI. 2001. Forest Genetic Resources Conservation and Management, vol. 2: In managed natural forests and protected areas (in situ). International Plant Genetic Resources Institute, Rome, Italy.

FAO, FLD, IPGRI. 2004a. Forest Genetic Resources Conservation and Management, vol. 1: Overview, concepts and some systematic approaches. International Plant Genetic Resources Institute, Rome, Italy.

FAO, FLD, IPGRI. 2004b. Forest Genetic Resources Conservation and Management, vol. 3: In plantations and genebanks (ex situ). International Plant Genetic Resources Institute, Rome, Italy.

Finkeldey R. 2005. An Introduction to Tropical Forest Genetics. Georg-August-University, Göttingen, Germany.

Geburek T, Turok J, editors. 2005. Conservation and Management of Forest Genetic Resources in Europe. Arbora Publishers, Zvolen, Slovakia.

Jansson G. 2005. Quantitative genetics. In: Geburek T, Turok J, editors. Conservation and Management of Forest Genetic Resources in Europe, Arbora Publishers, Zvolen, Slovakia. pp. 213–235.

Walsh B, Lynch M. 2008a. 7. The population genetics of selection. In: Walsh, B. and Lynch, M. Evolution and Selection of Quantitative Traits:


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I. Foundations.. Online prepublication draft. Version: 12 December 2009. Available from: http://nitro.biosci.arizona.edu/zbook/NewVolume_2/newvol2.html#2A Date accessed: 21 November 2013.

Walsh B, Lynch M. 2008b. 12. Short-term changes in the mean: 1. The breeders’ equation. In: Walsh, B. and Lynch, M. Evolution and Selection of Quantitative Traits: I. Foundations. Online prepublication draft. Version: 17 November 2008. Available from: http://nitro.biosci.arizona.edu/zbook/NewVolume_2/newvol2.html#2A Date accessed: 21 November 2013.


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Annex

1.

Sum

mary

of

the a

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visu

al

pre

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Tab

le A

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umm

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nic

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be

a fo

rm

of ‘n

egat

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tic

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ay w

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irect

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epth

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had

att

ract

ed t

he a

tten

tion

of fo

reig

n lo

ggin

g co

mp

anie

s.

Pho

tos

from

Von

Hag

en W

V. 1

940

The

Mos

qui

to C

oast

of H

ond

uras

and

its

inha

bita

nts.

Geo

grap

hica

l Rev

iew

30:

238–

259.

S

ee a

lso

Slid

e 32

(alte

rnat

ive)

.


11

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

4/N

o tit

leE

xam

ple

of l

oggi

ng

sugg

estiv

e (s

uper

ficia

lly,

per

hap

s) o

f DS

.

Von

Hag

en (1

940)

, writ

ing

in t

he G

eogr

aphi

cal R

evie

w, d

escr

ibed

a

logg

ing

oper

atio

n as

a r

esul

t of

whi

ch, i

n hi

s w

ord

s “f

or t

he fi

rst

time

sinc

e 19

00 t

he w

ood

s ar

e co

min

g to

life

aga

in.”

The

com

pan

y op

erat

ing

the

conc

essi

on w

ould

fell

all c

omm

erci

ally

val

uab

le

mah

ogan

y tr

ees

(i.e.

tre

es m

ore

than

ab

out

30 y

ears

old

). Th

ese

wer

e flo

ated

to

the

mou

th o

f the

Car

atas

ca L

agoo

n an

d fr

om t

here

wer

e sh

ipp

ed t

o Fl

orid

a. H

owev

er, V

on H

agen

rep

orte

d t

hat

rege

nera

tion

of t

he fo

rest

was

, non

ethe

less

, ass

ured

.

The

rich

(uni

nten

ded

) iro

ny is

wor

th

high

light

ing!

P

hoto

: Leo

nard

o F

Frei

tas,

Par

á, B

razi

l. Fl

ona

de

Jam

anxi

m P

ara.

htt

p:/

/ww

w.fl

ickr

.com

/p

hoto

s/le

offr

eita

s/14

6942

7761

/siz

es/m

/

5/R

egen

erat

ion

assu

red

?Th

e ai

m h

ere

is t

hat

stud

ents

sho

uld

th

emse

lves

won

der

w

heth

er s

usce

ptib

ility

to

term

ite a

ttac

k co

uld

hav

e so

me

gene

tic b

asis

.

[Rea

d o

r p

arap

hras

e th

e q

uote

from

Von

Hag

en o

n th

e sl

ide]

, the

n:

...so

, the

fore

st w

ould

be

rege

nera

ted

exc

lusi

vely

by

thos

e m

ahog

any

tree

s th

at h

ad b

een

infe

sted

by

term

ites.

Le

t’s n

ow g

o so

uth

to t

he A

maz

on, b

ut t

o th

e w

est

rath

er t

han

the

east

.

Que

stio

ns o

r co

mm

ents

mig

ht b

e in

vite

d a

t th

is s

tage

(par

ticul

arly

if a

n ob

viou

s ‘p

regn

ant

pau

se’ i

s m

ade

afte

r “t

erm

ites”

), or

mig

ht

be

rais

ed a

nyw

ay. S

usce

ptib

ility

of t

rees

to

atta

ck b

y te

rmite

s co

uld

per

hap

s b

e re

late

d

to g

ener

al v

igou

r, w

hich

in t

urn

wou

ld b

e ex

pec

ted

to

be

influ

ence

d b

y ge

noty

pe.

6/Iq

uito

s, P

eruv

ian

Am

azon

Lead

ing

into

sub

top

ic o

n ag

uaje

pal

m.

Iqui

tos

is a

dyn

amic

, bus

tling

city

in t

he P

eruv

ian

Am

azon

, in

spite

of

hav

ing

no r

oad

con

nect

ions

to

the

outs

ide

wor

ld. M

any

kind

s of

fo

rest

pro

duc

ts c

an b

e fo

und

in t

he m

arke

ts o

f Iq

uito

s…

Forw

ard

to

slid

e 7

on “

mar

kets

of I

qui

tos.

..”

7/M

edic

inal

sp

ecie

s,

Iqui

tos

Inte

rest

/var

iety

, lin

king

to

the

mai

n su

bto

pic

....

incl

udin

g m

edic

inal

sp

ecie

s an

d…

Forw

ard

to

slid

e 8

on t

he w

ord

“an

d”

[Thi

s sl

ide

shou

ld la

st fo

r ab

out

one

seco

nd.]

8/Fr

uit

spec

ies

Link

ing.

…of

cou

rse,

frui

ts, p

erha

ps

the

mos

t im

por

tant

of w

hich

is…

Forw

ard

to

slid

e 9

on “

of w

hich

is…

” [T

his

slid

e sh

ould

last

for

abou

t on

e se

cond

.]

9/Th

e ag

uaje

pal

m

(Mau

ritia

flex

uosa

)E

xam

ple

of h

arve

stin

g su

gges

tive

(sup

erfic

ially

, p

erha

ps)

of D

S. M

aurit

ia

flexu

osa

was

sel

ecte

d t

o em

pha

size

tha

t co

ncer

ns

are

not

rest

ricte

d t

o ge

netic

res

ourc

es o

f tim

ber

sp

ecie

s.

... t

he a

guaj

e p

alm

, Mau

ritia

flex

uosa

.


12

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

10/A

maj

or lo

cal

ind

ustr

yLi

nkin

g th

roug

h to

the

ha

rves

ting

met

hod

.In

Iqui

tos

a si

gnifi

cant

ind

ustr

y is

bui

lt ar

ound

the

agu

aje

pal

m, g

ivin

g em

plo

ymen

t to

ab

out

5000

peo

ple

in d

iffer

ent

stag

es o

f the

sup

ply

ch

ain,

incl

udin

g ha

rves

ters

, mid

dle

men

, str

eet-

corn

er v

end

ors,

and

m

anuf

actu

re a

nd s

ale

of p

roce

ssed

pro

duc

ts li

ke t

his

ice

crea

m.

Aro

und

20

tonn

es o

f agu

aje

frui

ts a

re c

onsu

med

eac

h d

ay in

the

city

. O

ur in

tere

st, t

houg

h, is

in t

he fi

rst

stag

e of

the

sup

ply

cha

in.

11/H

arve

stin

g ag

uaje

Set

ting

up t

he s

ugge

sted

d

ysge

nic

scen

ario

.Th

ose

20 t

onne

s ar

e eq

uiva

lent

to

abou

t 40

0 tr

ees,

whi

ch a

re fe

lled

to

har

vest

the

frui

t. A

roun

d 1

500

ha o

f agu

aje—

pur

e or

alm

ost

pur

e st

and

s—ar

e fe

lled

eac

h ye

ar. A

s th

e m

arke

t p

refe

rs la

rge

frui

t, t

rees

w

ith la

rge

frui

t ar

e p

refe

rent

ially

felle

d. F

elle

d t

rees

do

not

cop

pic

e,

and

all

thei

r se

ed is

col

lect

ed.

12/M

aurit

ia fl

exuo

sa

typ

esTh

e su

gges

ted

DS

sc

enar

io.

Fort

unat

ely,

in o

ne s

ense

, the

sp

ecie

s is

dio

ecio

us, s

o al

l the

mal

e tr

ees

are

left

, tog

ethe

r w

ith r

emna

nt fe

mal

es—

esca

pee

s (th

ose

that

did

not

pro

duc

e fr

uit

that

yea

r or

tha

t w

ere

‘mis

sed

’ by

the

harv

este

rs) o

r th

ose

with

sm

all f

ruit.

The

suc

ceed

ing

gene

ratio

n w

ill

be

pro

duc

ed fr

om t

hese

esc

apee

s an

d in

ferio

r tr

ees.

Ano

ther

thr

eat

is lo

w e

ffect

ive

pop

ulat

ion

size

res

ultin

g fr

om u

neq

ual s

ex r

atio

s (a

s on

ly

fem

ales

are

felle

d).

The

two

fact

ors

may

als

o ac

t sy

nerg

istic

ally

.

13/N

o tit

leS

umm

ing

up a

nd le

adin

g in

to t

he d

efini

tion.

So,

bot

h th

ese

harv

estin

g re

gim

es h

ave

in c

omm

on t

he p

ossi

bili

ty

that

onl

y th

e ‘w

orst

’ mem

ber

s of

the

pop

ulat

ion

will

rep

rod

uce.

..w

hich

brin

gs u

s to

our

defi

nitio

n of

dys

geni

c se

lect

ion.

"Bot

h" r

efer

s to

mah

ogan

y in

Hon

dur

as a

nd

agua

je p

alm

in P

eru.

14/D

ysge

nic

sele

ctio

nTh

e d

efini

tion.

Dys

geni

c se

lect

ion

is s

elec

tion

that

lead

s to

an

und

esira

ble

d

irect

iona

l cha

nge

in g

enet

ic q

ualit

y ov

er o

ne o

r m

ore

gene

ratio

ns.

By

‘gen

etic

qua

lity’

we

usua

lly m

ean

per

form

ance

for

a gi

ven

com

mer

cial

ly im

por

tant

tra

it (s

uch

as g

row

th r

ate

or s

urvi

val),

and

b

y ‘d

irect

iona

l cha

nge’

we

mea

n a

pos

itive

or

nega

tive

chan

ge in

m

ean

valu

es. D

irect

iona

lity

dis

tingu

ishe

s d

ysge

nic

sele

ctio

n fr

om

gene

tic d

rift,

whi

ch c

an a

lso

lead

to

und

esira

ble

cha

nges

in g

enet

ic

qua

lity,

but

in a

ran

dom

way

and

in a

noth

er s

ense

(i.e

. ran

dom

loss

of

alle

les)

.

The

inst

ruct

or s

houl

d c

onsi

der

ask

ing

for

defi

nitio

ns o

f bot

h ‘g

enet

ic q

ualit

y’ a

nd

‘dire

ctio

nal,’

and

ask

ing

how

dire

ctio

nal d

iffer

s fr

om r

and

om d

rift

(or,

for

that

mat

ter,

‘gen

etic

co

ntam

inat

ion’

thr

ough

gen

e flo

w).

15/C

laim

s of

dys

geni

c se

lect

ion

and

var

iatio

n p

atte

rns’

Poi

ntin

g ou

t th

at t

he r

isks

ha

ve b

een

sugg

este

d in

th

e lit

erat

ure:

the

the

me

is

‘on

the

agen

da.

’

It ha

s b

een

sugg

este

d a

num

ber

of t

imes

tha

t d

ysge

nic

sele

ctio

n m

ight

be

of im

por

tanc

e in

fore

st t

rees

. For

exa

mp

le, P

alm

ber

g su

gges

ted

tha

t it

coul

d e

xpla

in w

hy p

rove

nanc

e va

riatio

n in

tw

o M

edite

rran

ean

pin

e sp

ecie

s fa

iled

to

show

rel

atio

nshi

ps

with

latit

ude

or lo

ngitu

de.

Pal

mb

erg

C. 1

975.

Geo

grap

hic

varia

tion

and

ear

ly g

row

th in

sou

th-e

aste

rn s

emi-

arid

A

ustr

alia

of P

inus

hal

apen

sis

Mill

. and

the

P.

bru

tia T

en. s

pec

ies

com

ple

x. S

ilvae

Gen

etic

a 24

: 150

–160

.


13

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

16/C

laim

s of

dys

geni

c se

lect

ion

and

se

lect

ive

logg

ing

Poi

ntin

g ou

t th

at t

he r

isks

ha

ve b

een

sugg

este

d in

th

e lit

erat

ure:

the

the

me

is

‘on

the

agen

da.

’

Sim

ilarly

, it

has

bee

n cl

aim

ed t

hat

the

poo

r fo

rm o

f the

Car

ibb

ean

mah

ogan

y, S

wie

teni

a m

ahag

oni,

is t

he r

esul

t of

the

sam

e fa

ctor

….

17/C

laim

s of

dys

geni

c se

lect

ion

and

se

lect

ive

logg

ing

Poi

ntin

g ou

t th

at t

he r

isks

ha

ve b

een

sugg

este

d in

th

e lit

erat

ure:

the

the

me

is

‘on

the

agen

da.

’

...w

hile

, tur

ning

from

pos

sib

le p

asts

to

pos

sib

le fu

ture

s, L

emes

et

al.

sugg

este

d t

hat

this

mig

ht s

till b

e ha

pp

enin

g in

the

cas

e of

Sw

iete

nia

mac

rop

hylla

. W

e ha

ve o

f cou

rse

bee

n hi

ntin

g at

suc

h p

roce

sses

with

the

tw

o ex

amp

les

of L

a M

osq

uitia

and

Iqui

tos.

How

ever

, to

clar

ify t

hese

id

eas

a lit

tle w

e ne

ed t

o lo

ok c

aref

ully

at

the

term

‘sel

ectiv

e lo

ggin

g.’

Lem

es M

R, G

ribel

R, P

roct

or J

, Gra

ttap

aglia

D

. 200

3. P

opul

atio

n ge

netic

str

uctu

re o

f m

ahog

any

(Sw

iete

nia

mac

rop

hylla

Kin

g,

Mel

iace

ae) a

cros

s th

e B

razi

lian

Am

azon

, bas

ed

on v

aria

tion

at m

icro

sate

llite

loci

: im

plic

atio

ns

for

cons

erva

tion.

Mol

ecul

ar E

colo

gy 1

2:

2875

–288

3.

18/W

hat

is s

elec

tive

logg

ing?

Aim

s to

cla

rify

the

mea

ning

, par

ticul

arly

to

avoi

d t

he id

ea t

hat,

with

in

spec

ies,

it m

eans

‘hig

h gr

adin

g.’

‘Sel

ectiv

e lo

ggin

g’ r

efer

s, o

f cou

rse,

to

the

felli

ng a

nd e

xtra

ctio

n of

on

ly c

erta

in t

ypes

of t

rees

. How

ever

, for

our

pur

pos

es, i

t is

use

ful t

o d

istin

guis

h tw

o sl

ight

ly d

iffer

ent

typ

es o

f sel

ectio

n as

pra

ctis

ed b

y lo

gger

s an

d o

ther

har

vest

ers

of fo

rest

pro

duc

ts.

Firs

t, w

e ha

ve t

he s

elec

tive

logg

ing

of p

artic

ular

sp

ecie

s. T

ypic

ally

, lo

gger

s on

ly e

xtra

ct t

hose

sp

ecie

s th

at h

ave

com

mer

cial

val

ue, a

nd

this

is t

he u

sual

mea

ning

of ‘

sele

ctiv

e lo

ggin

g’ w

hen

used

in fo

rest

ry.

Pho

to:

Leon

ard

o F.

Fre

itas.

Fel

iz N

atal

, Mat

o G

ross

o, B

razi

l. ht

tp:/

/ww

w.fl

ickr

.com

/p

hoto

s/le

offr

eita

s/79

0041

598/

size

s/m

/in/s

et-

7215

7600

6059

3314

4/

19/W

ithin

-sp

ecie

s se

lect

ive

logg

ing

Aim

s to

cla

rify

the

mea

ning

, par

ticul

arly

to

avoi

d t

he id

ea t

hat,

with

in

spec

ies,

it m

eans

‘hig

h gr

adin

g.’

Sec

ond

, we

have

sel

ectio

n w

ithin

sp

ecie

s. In

thi

s ca

se, l

ogge

rs

don

’t us

ually

sel

ect

‘onl

y th

e b

est’

(as

the

quo

te in

slid

e 17

see

ms

to s

ugge

st).

Rat

her,

they

fell

ever

ythi

ng t

hat

it is

wor

thw

hile

to

fell,

an

d t

here

fore

leav

e on

ly t

he w

orst

. In

fact

, if l

ogge

rs t

ook

only

the

ve

ry b

est,

the

n d

ysge

nic

sele

ctio

n w

ould

not

be

a se

rious

wor

ry. I

t w

ould

be

like

tryi

ng t

o ca

rry

out

gene

tic im

pro

vem

ent

by

lett

ing

all

ind

ivid

uals

rep

rod

uce

exce

pt

the

very

wor

st. T

his

wou

ld n

ot w

ork,

b

ecau

se g

enet

ic im

pro

vem

ent

by

rem

oval

of j

ust

the

very

wor

st

wou

ld h

ave

a ne

glig

ible

effe

ct o

n th

e fr

eque

ncy

in t

he p

opul

atio

n of

th

e b

est

alle

les.

Pho

to:

Leon

ard

o F.

Fre

itas.

Sen

ador

Jos

e P

orfir

io,

Par

á, B

razi

l. ht

tp:/

/ww

w.fl

ickr

.com

/pho

tos/

leof

frei

tas/

4476

1604

8/si

zes/

m/in

/set

-72

1576

0060

5933

144/


14

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

20/D

ysge

nic

sele

ctio

n: t

he m

irror

im

age

of g

enet

ic

imp

rove

men

t

Link

ing

bac

k to

DS

as

the

opp

osite

of g

enet

ic

imp

rove

men

t.

In g

enet

ic im

pro

vem

ent,

bre

eder

s of

ten

sele

ct t

he v

ery

bes

t an

d

allo

w o

nly

thos

e in

div

idua

ls t

o re

pro

duc

e.

In lo

ggin

g, lo

gger

s of

ten

leav

e on

ly t

he v

ery

wor

st, a

nd t

hese

‘s

elec

ted

ind

ivid

uals

’ (w

hich

of c

ours

e ar

e th

ose

left

by

logg

ers,

ra

ther

tha

n th

ose

sele

cted

by

them

) are

tho

se t

hat

rep

rod

uce

and

gi

ve r

ise

to t

he n

ext

gene

ratio

n.

So

dys

geni

c se

lect

ion

is li

ke t

he m

irror

imag

e of

gen

etic

im

pro

vem

ent.

..

21/P

ositi

ve

phe

noty

pic

sel

ectio

n ai

min

g at

gen

etic

im

pro

vem

ent

Con

solid

atin

g th

e ‘m

irror

im

age

idea

’ and

lead

ing

into

exp

licit

case

s of

ne

gativ

e an

d p

ositi

ve

sele

ctio

n.

…an

d w

e ca

n ill

ustr

ate

that

with

the

se d

ata

from

a V

ochy

sia

guat

emal

ensi

s p

lant

atio

n in

Sar

apiq

uí, C

osta

Ric

a… [b

riefly

exp

lain

w

hat

the

grap

h sh

ows]

In t

his

case

, we’

re il

lust

ratin

g p

ositi

ve

phe

noty

pic

sel

ectio

n. T

rees

ab

ove

7 cm

db

h ha

ve b

een

sele

cted

, an

d e

vent

ually

onl

y th

ese

will

be

allo

wed

to

rep

rod

uce.

22/N

egat

ive

phe

noty

pic

sel

ectio

n,

pos

sib

ly le

adin

g to

d

ysge

nic

sele

ctio

n

Neg

ativ

e se

lect

ion.

In t

his

case

, we

are

imag

inin

g th

e se

lect

ion

of o

nly

thos

e tr

ees

with

db

h <

2 c

m. I

f onl

y th

ese

35 o

r so

sm

all t

rees

wer

e al

low

ed t

o re

pro

duc

e, t

hen

ther

e w

ould

be

a ris

k of

dys

geni

c se

lect

ion.

23/T

here

are

no

doc

umen

ted

ex

amp

les

of d

ysge

nic

sele

ctio

n in

fore

st

tree

s

Lead

ing

in t

o th

e ne

ed

for

pre

dic

tion

and

the

b

reed

ers’

eq

uatio

n.

In fa

ct, t

here

are

no

doc

umen

ted

exa

mp

les

of d

ysge

nic

sele

ctio

n ac

tual

ly h

avin

g ha

pp

ened

in fo

rest

tre

es. T

his

shou

ld n

ot b

e se

en a

s an

ind

icat

ion

that

it is

not

imp

orta

nt—

rath

er, i

t re

flect

s th

e fa

ct t

hat

no o

ne h

as s

erio

usly

look

ed in

to it

. For

exa

mp

le, n

o on

e ha

s ev

er

com

par

ed t

he g

row

th r

ate

of p

roge

ny o

f log

ged

and

rem

nant

tre

es.

As

a re

sult,

we

need

to

app

roac

h th

is s

ubje

ct fr

om a

the

oret

ical

vi

ewp

oint

. For

tuna

tely

, as

dys

geni

c se

lect

ion

is li

ke g

enet

ic

imp

rove

men

t in

rev

erse

, the

hig

hly

succ

essf

ul t

heor

y th

at u

nder

lies

gene

tic im

pro

vem

ent

serv

es a

s ou

r fr

amew

ork.

Muc

h of

thi

s fr

amew

ork

is s

umm

ariz

ed in

one

rel

atio

nshi

p, k

now

n as

…

24/T

he b

reed

ers’

eq

uatio

n...

the

bre

eder

s’ e

qua

tion,

whi

ch a

llow

s us

to

pre

dic

t th

e ef

fect

of

sele

ctio

n, w

heth

er p

ositi

ve (i

mp

rove

men

t) or

neg

ativ

e (d

ysge

nic)

. Le

t’s lo

ok b

riefly

at

the

thre

e co

mp

onen

ts.


15

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

25/T

he b

reed

ers’

eq

uatio

n:

Res

po

nse

to

sele

ctio

n (R

) =

sele

ctio

n d

iffer

entia

l (S

) x h

erita

bili

ty (h

2 )

Exp

lain

s th

e re

spon

se t

o se

lect

ion—

wha

t it

is t

hat

we

are

tryi

ng t

o p

red

ict.

The

effe

ct o

f sel

ectio

n is

qua

ntifi

ed b

y th

e re

spon

se t

o se

lect

ion,

w

hich

mea

sure

s th

e ch

ange

in p

erfo

rman

ce b

etw

een

one

gene

ratio

n (th

e on

e in

whi

ch s

elec

tion

is c

arrie

d o

ut) a

nd t

he n

ext

(the

imp

rove

d

[or

dys

geni

c] g

ener

atio

n). I

t is

mea

sure

d in

wha

teve

r un

its a

re

app

rop

riate

to

the

trai

t b

eing

sel

ecte

d (e

.g. d

bh—

cm, h

eigh

t—m

, st

em q

ualit

y-sc

ore,

den

sity

—kg

/m3)

, or

can

be

exp

ress

ed a

s a

per

cent

age.

For

exa

mp

le, i

f we

sele

ct p

lus-

tree

s in

pla

ntat

ions

, and

tr

ees

grow

n fr

om t

heir

seed

gro

w 1

0% m

ore

qui

ckly

tha

n av

erag

e se

ed fr

om t

he s

ame

pla

ntat

ions

, the

n th

e re

spon

se t

o se

lect

ion

is

10%

. B

ut b

efor

e w

e ca

rry

out

sele

ctio

n, w

e w

ill n

ot k

now

its

futu

re im

pac

t,

whi

ch is

why

we

need

to

pre

dic

t it.

We

do

so u

sing

tw

o p

aram

eter

s.

26/T

he b

reed

ers’

eq

uatio

n:

Res

pon

se t

o se

lect

ion

(R) =

sel

ecti

on

diff

eren

tial

(S) x

he

ritab

ility

h2 )

Exp

lain

s th

e se

lect

ion

diff

eren

tial.

Firs

t, le

t’s lo

ok a

t th

e se

lect

ion

diff

eren

tial,

whi

ch is

the

diff

eren

ce

bet

wee

n th

e se

lect

ed in

div

idua

ls a

nd t

he o

vera

ll m

ean.

For

exa

mp

le,

in t

he c

ase

just

men

tione

d, i

f the

plu

s-tr

ees

had

a m

ean

db

h of

40

cm a

nd t

he p

opul

atio

n m

ean

is 2

0 cm

, the

n th

e se

lect

ion

diff

eren

tial

is 2

0 cm

. In

itsel

f, th

e se

lect

ion

diff

eren

tial t

ells

us

noth

ing

abou

t w

heth

er t

he s

uper

iorit

y it

exp

ress

es is

due

to

gene

tics

or s

ome

othe

r ca

use—

it is

just

a w

ithin

-gen

erat

ion

mea

sure

of d

iffer

ence

.

27/T

he b

reed

ers’

eq

uatio

n:

Res

pon

se t

o se

lect

ion

(R) =

sel

ectio

n d

iffer

entia

l (S

) x

heri

tab

ility

(h2 )

Intr

oduc

es h

erita

bili

ty.

Sec

ond

, we

look

at

the

herit

abili

ty, w

hich

mea

sure

s th

e d

egre

e to

w

hich

the

sup

erio

rity

mea

sure

d in

the

sel

ectio

n d

iffer

entia

l is

pas

sed

on

to

the

pro

geny

. The

val

ue o

f her

itab

ility

var

ies

from

zer

o to

on

e—a

typ

ical

val

ue fo

r d

bh

mig

ht b

e ar

ound

0.2

. Put

ting

thes

e tw

o to

geth

er, w

e ca

n p

red

ict

the

resp

onse

to

sele

ctio

n.

28/T

he b

reed

ers’

eq

uatio

n:

Res

pon

se t

o se

lect

ion

(R) =

sel

ectio

n d

iffer

entia

l (S

) x

herit

abili

ty (h

2 )

Exa

mp

le o

f pre

dic

tion

of

resp

onse

to

sele

ctio

n.Th

e he

ritab

ility

tel

ls u

s th

at 2

0% o

f the

phe

noty

pic

sup

erio

rity

exp

ress

ed in

the

sel

ectio

n d

iffer

entia

l is

due

to

herit

able

gen

etic

ch

arac

teris

tics

(alle

les

that

the

plu

s-tr

ees

have

). W

e th

eref

ore

pre

dic

t a

bet

wee

n-ge

nera

tion

gene

tic r

esp

onse

of 2

0% o

f the

sel

ectio

n d

iffer

entia

l, i.e

. 4 c

m.


16

Slid

e no

./T

itle

Func

tio

nS

ugg

este

d s

po

ken

text

No

tes

29/M

ahog

any

logg

ing

in B

razi

lFi

nish

ing

with

the

ch

alle

nge

pos

ed b

y th

e ex

erci

se, w

hich

invo

lves

ap

ply

ing

the

bre

eder

s’

equa

tion.

In o

ur e

xerc

ise,

we

will

use

thi

s fr

amew

ork

to e

xplo

re b

oth

the

natu

re

of d

ysge

nic

sele

ctio

n an

d t

he p

rob

abili

ty o

f it

occu

rrin

g in

a s

pec

ific

exam

ple

bas

ed o

n lo

ggin

g in

the

Mar

ajoa

ra F

ores

t, P

ará

Sta

te,

Bra

zil.

Mar

ajoa

ra is

a 4

100

ha in

dus

try-

man

aged

fore

st a

rea,

and

is

pro

bab

ly t

he m

ost

stud

ied

mah

ogan

y-ric

h fo

rest

any

whe

re.

30/M

araj

oara

bef

ore

logg

ing

Her

e is

the

dis

trib

utio

n of

db

h at

Mar

ajoa

ra b

efor

e lo

ggin

g...

The

grap

h ac

tual

ly s

how

s va

lues

for

the

sam

ple

d a

rea

at M

araj

oara

, ext

rap

olat

ed o

ver

the

entir

e 41

00 h

a, o

n th

e as

sum

ptio

n of

eq

ual

stoc

king

thr

ough

out.

31/M

araj

oara

bef

ore

logg

ing…

Mar

ajoa

ra

afte

r lo

ggin

g

Lead

s in

to t

he r

est

of t

he

sess

ion

(cas

e st

udy)

....

and

her

e is

the

db

h d

istr

ibut

ion

afte

r lo

ggin

g. W

ill t

he “

cont

inuo

us

exp

loita

tion

of la

rge,

sup

erio

r in

div

idua

ls”

lead

to

dys

geni

c se

lect

ion,

as

sug

gest

ed b

y so

me

rese

arch

ers?

One

of y

our

task

s is

to

answ

er

this

que

stio

n!

The

two

grap

hs a

re q

uite

str

ikin

g an

d s

houl

d

arou

se in

tere

st.

Dra

w a

tten

tion

to t

he o

bvi

ous

dem

ogra

phi

c im

pac

t of

the

logg

ing,

if it

is n

ot c

lear

whe

ther

th

is h

as a

lread

y b

een

notic

ed.

32/’

Mah

ogan

y b

ush’

Alte

rnat

ive

to s

lide

3.P

hoto

s:

Left

: Jos

iah

Tow

nsen

d. M

osq

uitia

Mar

sh,

Gra

cias

a D

ios

Dep

artm

ent,

Hon

dur

as.

http

://w

ww

.flic

kr.c

om/p

hoto

s/jo

siah

_to

wns

end

/275

8880

722/

size

s/m

/ R

ight

: Jos

iah

Tow

nsen

d. R

io T

apal

was

, W

amp

usirp

i, R

us R

us, G

raci

as a

Dio

s D

epar

tmen

t, H

ond

uras

. htt

p:/

/ww

w.fl

ickr

.com

/p

hoto

s/jo

siah

_tow

nsen

d/2

7589

4050

0/si

zes/

m/


B

Forest Genetic Resources Training GuideMODULE 1 Species conservation strategies

1.1 Leucaena salvadorensis: genetic variation and conservation

1.2 Talbotiella gentii: genetic variation and conservation1.3 Shorea lumutensis: genetic variation and conservation

MODULE 2 Trees outside of forests

2.1 Conservation of tree species diversity in cocoa agroforests in Nigeria

2.2 Devising options for conservation of two tree species outside of forests

MODULE 3 Tree seed supply chains

3.1 Genetic bottlenecks in the restoration of Araucaria nemorosa

3.2 Tree planting on farms in East Africa: how to ensure genetic diversity?

MODULE 4 Forest management

4.1 Impacts of selective logging on the genetic diversity of two Amazonian timber species

4.2 Does selective logging degrade the genetic quality of succeeding generations through dysgenic selection?

4.3 Conserving Prunus africana: spatial analysis of genetic diversity for non-timber forest product management

MODULE 5 How local is local? – the scale of adaptation

5.1 Selecting planting material for forest restoration in the Pacific north-west of the USA

5.2 Local adaptation and forest restoration in Western Australia

Other modules to be published among the following: Plantation forestry, Tree domestication, Forest restoration, Genetic modification

Teacher’s Notes 4.2 Does selective logging degrade the...

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Transcript of Teacher’s Notes 4.2 Does selective logging degrade the...