Silviculture of stone pine: models and management tools · Pm = 140,1 g + 0,4 g mm-1 R2 = 0,82 0,000 kg 0,100 kg 0,200 kg 0,400 kg mm 200 mm 00 mm 00 mm 00 mm Precipitación del año

AgroPine2011 International Meeting on Mediterranean stone pine for agroforestry Valladolid-Spain, 17-19 November 2011

Rafael Calama SainzDpto. Selvicultura y Gestión de los Sistemas Forestales. CIFOR-INIAInstituto Gestión Forestal Sostenible

Silviculture of stone pine: models and management tools

Main objective and index

To review the scientific advances attained in stone pine silviculture and management in Spain, and how these results have been implemented into

the daily management practice (INIA research line 1992 – 2011)

•Generalities •Introduction:

– Where we were? – What do managers need? – What and how to do?

•Our experimental “devices”•The main results obtained•Improvement of scientific knowledge•Transference to forest management•The future

Agropine 2011. International meeting on Mediterranean stone pine agroforestry. Valladolid, 17 November 2011

Generalities about Pinus pinea in Spain

• 450,000 ha, > 60 % world area• 250,000 ha afforestations since 1940• Multifunctional management since XIXth century: cone and timber• Cone production: 30 – 50 x 106 kg cones/year (1,5 – 2,5 106 kg white nuts / year) • Timber: 200,000 m3/year• Fruit income > timber income• Mushrooms, fuelwood, protection against soil erosion (dunes), recreational use,

CO2 fixation…


LITORAL ANDALUZ

MESETANORTE

SISTEMA CENTRAL

CATALUÑA

Generalities about Pinus pinea in Spain

• Great variety of ecological, historical and management conditions

- Flat area

- Sands and limestones

- Dry cold continental

- 450 mm; 10-13ºc

- Managed public forests

- Cone – timber: typical sillviculture

-Mountain rocky area

- Mild mediterranean climate

- 600 – 800 mm; 12-15ºC


- Cones - livestock

- Uneven-aged stands

MANCHA

Sª MORENA

- Sandy soils

- Humid warm climate

- 600-750 mm; 16-18.5ºC

- Managed public forests.

- Timber - protection

- Rocky mountains: pizarres

- Soils more evolved

- 700 -900 mm; 14-19ºC


- Afforestations

- Sandy soils

- Mixed stands Quercus

- Mild mediterranean climate

- 600-850 mm; 12-17ºC

- Private - owned

- Timber


Where we were in 1992?

- 1960’s: Permanent plots for timber production

- End 80’s: agreements between INIA, public administrations, research centres...

- First workshops: Madrid 1989, FAO meeting 1995... where we were then?

1. Silviculture based on experience and observation. Disparity of criteria aboutthinning practices, rotation length, prunning.

2. Inconsistency among theoretical (timber) and real (cone - timber)management objectives. Conservative management

3. Attempts for transferring the knowledge attained in other species

4. Lack of scientific knowledge, specially concerning cone production.Management based on “myths”: masting cycles theory, crown pruning…


“…study silviculture influence – thinning and pruning - on wood and fruit production in order to define optimum management schedules..:”

“… essential to install a experimental plot net covering the whole range of age, stand density and site quality, where timber and cone production is measured…”

Basic requirements from forest managers

1. To estimate, characterize and optimize the total amount of productions(cone, timber, biomass) and services (fixed CO2) provided by a stone pineforest, for different actual and future scenarios

2. Compare and contrast different management schedules and determine theoptimum schedule in order to attain the defined management objectivesunder sustainability principles

3. Which treatments are more effective in order to attain the managementobjectives and how they should be applied?

4. How to carry a forestry emulating natural processes?: natural regeneration ofthe stands, change structure-composition…

Simple, robust and cheap tools

which aid to adopt management decisions


Main objectives of the research line on stone pine silviculture

1. Knowledge of the dynamic processes on stone pine forests: growth,resource allocation, regeneration, competition, mortality and the mainfactors affecting these processes:

- Extrinsical: site, climate

- Intrinsical: stand and tree attributes, composition, structure

2. Effect of the different silvicultural treatments over the previous definedprocesses

3. Development of models to predict the evolution and production ofstone pine forests under different scenarios and management schedules

4. Characterization and optimization of stone pine forest’s products, withspecial attention to pine cones

5. Adaptation and mitigation silviculture facing to climate change scenarios

Since 1992 CIFOR-INIA in cooperation with CTFC, CSIC, JA, JCyL, OAPN, CAM


How we carry this research?

Research topic

hypothesis

Experimental design

Results

Spread it to the scientific community

Transfer to the forest management community

Improve scientific knowledge about

the species

Improve management

practices

SCI papersConferences

ReportsWorkshops

Tools

Identify gaps of knowledge

Identify management requirements


Experimental design: which are our laboratories?

Net of permanent plots on even-aged pure stands

H

hbc

Dcrown

dbh

(X1,Y1)(Xj,Y j)(X1,Y1)(Xj,Y j)

- 500 plots in 5 regions

- Installation 1992 - 2000

- Inventory 5- 10 years. Stem analysis.

- Installed in cooperation with publicadministration services

- Observed silviculture


Experimental design: which are our laboratories?

Net of permanent plots on even-aged pure stands

Cover the whole range of site, stand density, age, management conditions


Experimental design: which are our laboratories?Net of permanent plots on even-aged pure stands: cone production

5 cones per tree to laboratory

Pine nut extraction

Nut crackingAnnual crop

5 trees/plot

Count and weight

Oven dried

2000 trees with fruit production series ranging 5 – 15 yearsLaboratory analysis covering 5 years


Experimental design: which are our laboratories?Permanent plots on uneven-aged and mixed stands

Large plots 0.3 – 0.5 ha. 4 on uneven-aged – 6 on mixed P. pinea – Quercus – Juniperus standsGrowth, regeneration and sucession dynamics. Physiological response


Experimental design: which are our laboratories?Experimental trials on precommercial thinning, thinning and pruning

- Based on randomized block experimental design- Between and within years diameter and height growth patterns, survival- Flowering and cone production, crown architecture- Effect of prunning on growth and cone production (Andalusia)

P.11TP

P.13CP

P.15CN

P.2TN

P.20CNP.18TP

P.17CP

P.16TN

P.19CP

P.8TP

P.5CN

P.10TN

50 0 50 100 150 200 Meters

TRATAMIENTOP.0.- Número de parcelaTP.- parcela Te stigo de clareos y PodaTN.- pa rcela Testigo de clareo s y No po daCP.- pa rcela de Clare o y PodaCN.- parcela de Clare o y No poda

Th x P Th x NP


Experimental design: which are our laboratories?Natural regeneration trial

- Different intensities: seed tree to shelterwood system- Continuous regeneration survey- Processes : primary and secondary dispersal, germination, predation, seedling growth and survival => bottlenecks -Physiological response


ResultsSite, stand and tree attributes affecting growth, allometry and survival

- Site index models for even, uneven and afforestations- Diameter increment models as a function of stocking, site and competition- Height-diameter and crown attributes equations- Self-thinning models

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

0 10 20 30 40 50 60

edad (años)

altura (m)

MASAS REPOBLADAS

MASAS NATURALES

2

3

4

5

6

7

8

9

10

2 2.5 3 3.5 4ln(Dg)

ln(N

)

CIFOR-INIA

IFN2

IFN3

Montero yCandela (1998)60% SDImax

35% SDImax

10% SDImax


ResultsLarge response to early and heavy thinning in growth and fruiting

- Positive effect on diameter and height growth

- Anticipated cone crops

- Seasonal summer response

- Reduction in crown dieback drought related phenomena

0

5

10

15

20

25

30

35

70 100 150 200 250Initial diameter (mm)

Dia

met

er in

crem

ent 2

004-

2007

Heavy Moderate Control

* **

ns

ns

ns

nsns

* *

Early thinning as an adaptive measure facing climate change scenarios


ResultsNull or negative effects of early pruning

- Negative effect of early pruning on diameter increment- Negative effect of very intensive pruning even on height increment- No effect of stem or crown pruning on cone production- No effect on crown architecture


ResultsMain factors explaining spatial variability in cone production

- Larger production in larger dominant trees- Increasing tree production up to 140 years- Optimum stocking densities 100 – 200 stems/ha- Soils with large water retention ability and spring rainfall

- Spatial models for cone production (average 5-year production)

Tree level Size

CompetitionAge

SiteSoil (WRA)

Climate (rainfall)Site Index

Stand attributesStocking

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0 20 40 60 80 100 120 140Edad

Prod

ucci

ón a

cum

ulad

a de

piñ

a (k

g/ha

)

200 stems/ha 100 stems/ha


0

50

100

150

200

250

300

350

400

1995 1997 1999 2001 2003 2005 2007 2009

pp_m

y_jn

_oc_

nv_-

3 (m

m)

0

1

2

3

4

5

6

7

kg p

iña

/ árb

ol

ResultsMain factors explaining temporal variability in cone production

- pp my_jn_3 and oc_nv_3: bud formation and differentiation- pp summ_2 and freezing days: female flower survival- pp_wint_spring_0: cone maturation- Three-year delayed inhibition after a good crop

- Temporal and spatiotemporal models for cone production

Main climate control over masting habit in Pinus pinea (4 years before dispersal)


ResultsFactors affecting cone and nut quality

- Individual cone weight as a good indicator of cone content quality- Little effect of silviculture on cone weight- Effect of site index and mainly, annual rainfall

- Models for cone content and nut quality

Peso medio de la piña seca

Pes

o m

edio

del

piñ

ón c

on c

ásca

ra

0 100 200 300 400 5000

0,2

0,4

0,6

0,8

1

1,2

Peso medio de la piña seca

Ren

dim

ient

o en

piñ

ón d

e la

piñ

a

0 100 200 300 400 5000

0,1

0,2

0,3

0,4

0,5

Pm = 140,1 g + 0,4 g mm-1

R2 = 0,82

0,000 kg

0,100 kg

0,200 kg

0,300 kg

0,400 kg

0 mm 200 mm 400 mm 600 mm 800 mm

Precipitación del año forestal

Peso

med

io d

e pi

ña


ResultsIdentification of main bottlenecks in regeneration process

- Seed dispersal limitation : 75% of seed under crown, <1% farther than 2 CR- Basal area < 10 m2/ha lead to > 50% of positions without seed dispersal - Lack of fall germination followed by winter seed predation (Apodenus)- Better rates of emergence and survival under crown cover

- Integral model for natural regeneration

1 3 5 7 9 11 1 3

010

2030

4050

SS

020

6010

0

65 70 75 80 85 90

0.00

0.02

0.04

0.06

0.08

0.10

0.12

Relative Humidity (%)

Ger

m. r

ate

(ger

min

ated

/rem

aind

ed·d

ay)

20ºC

15ºC

10ºC

5ºC

0ºC


ResultsCharacterization of timber production: quality, biomass

- Stem curve equation with end-product classification

- Model for stem rot probability (Phellinus pini)

- Biomass fractions equations and BEF

Needles 5%

Branches2-7 cm 11%

Branches >7 cm 19%

Stem: 38%

Root:16%

Branches <2 cm 11%


ResultsUneven-aged forestry

- Sustainability by selective cuttings with 25 year rotation: 6 – 18 m2/ha- Management schedules- Specific growth patterns- Larger production of cones - Smaller timber production and CO2 fixing

- Models for uneven-aged forestry

dbh(cm)

Before felling

(stems/ha)

After felling

(stems/ha)

< 10 100 30

10-20 50 25

20-30 40 20

30-40 30 20

40-50 25 15

50-60 15 5

> 60 10 5

TOTAL 270 120

even

uneven


ResultsIntegrated tree-level model for multifunctional management: PINEA2

- Complement/substitute previous stand-level models and growth yield tables- Tree-level model working on 5-year steps- Different managment schedules: thinning, rotation length, regeneration fellings- Timber volume, biomass, cone production, CO2 fixed- Northern Plateau, Central Range, afforestations






ResultsOptimizing management schedules

- Comparison among different management schedules, structures- VAN, CO2, timber, cones…- Optimization of thinning practices and rotation length based on stochastic climate scenarios

050

100150

200250

300350

400

0 20 40 60 80 100 120Age (years)

CO

2 fix

ed (t

/ha)

even-aged uneven-aged

OPTIMIZATION

N ALGORITHM

Optimal

solution

Expected value of objective function

Decision

variables

Scenarios

Initial values of

decision

variables

STAND SIMULATOR

Initial

stands

Probability-weighted mean of many simulations


Improvement of scientific basis for stone pine silviculture

Results from the INIA stone pine silviculture research line (1992 – 2011)

- PhD Thesis: 4 (+3 in prep.)

- MSc Thesis: 4

- SCI papers: 21

- Papers in other peer-reviewed journals: 7

- Monographic books: 3

- Chapters in general books: 8

- Contributions in national and international conferences: > 45


Transference of results to practical forest management

Proposal for natural regeneration techniques

- Less intense preparatory and seedling fellings. Regeneration fellings should be oriented to liberate so-establisehd seedlings rather than to favour emergence

- Concentrate fellings in optimal-conditions years

- Enlargement of regeneration periods

- Anticipate seeding practices up to fall season



New density management strategies

- Early (ca. 10 years) and heavy (300-400 stems/ha) precommercial thinnings. Whole tree extraction and use for biomass.

- Two low heavy thinnings up to the middle of the rotation length

- Final stand density 120 – 200 stems/ha

- Widening rotation length 120 – 140 years



Pruning strategies

- Delay first pruning up to 20 years (first thinning)

- Stem pruning up to 4 m, facilitating trunk shaker activity

- Avoid crown pruning (“olivación”)



Suitability of uneven-aged and mixed forestry

- Depending on site conditions and management objectives, it is possible to carry sustainable forest management in uneven and mixed forests



Management aided by models and decision support tools

- Site index curves

- Stem taper curves (CUBIFOR)

- Growth and yield tables and models


Future lines of research in silviculture


- Adaptive management facing global change (climate, economical…)

- Physiological based models for management

- The role and management of heterogeneous stands

- Regeneration out of forests

- Improve and extent cone production prediction models

- Models and Decision support tools at forest / region scale

…………………

- Improve the transference of knowledge

And all of these new requirements that we will be able to identify

This is the result of the joint effort carried by a lot of people…

CIFOR-INIA- Gregorio Montero - Isabel Cañellas- Otilio Sánchez- Marta Pardos- Miren del Río- Sven Mutke- Ricardo Ruíz-Peinado- Mariola Sánchez- María Pasalodos- Eduardo López- Guillermo Madrigal- Ángel Bachiller- Enrique Garriga- Rubén Manso- Carolina Mayoral- Javier de Dios- Santiago de Blas- Nieves Cañadas

JUNTA DE CyL- Javier Gordo- Luis Finat- Daniel Álvarez- Carlos García-Güemes- Sabas Yagüe

CTFC- Miriam Piqué

JUNTA ANDALUCÍA- José A. Candela- Juan Pavón

OAPN- Javier Moro

CSIC- Paola Ovando- Pablo Campos


… and funded by a lot of projects

- 1992 – 1999: Convenio IARA: Estudio de la influencia de los tratamientos selvícolas en la producción de fruto y madera de Pinus pinea en la provincia de Huelva

- 1995 – 1998: SC-95-095: Estudio de la influencia de los tratamientos selvícolas en la producción de fruto y madera de Pinus pinea en la provincia de Valladolid

- 1999 – 2002: SC-99-017 Modelos selvícolas para el aprovechamiento sostenible de las masas de Pinus pinea

- 2003 – 2006: CC – 02 – 0017: Estudio autoecológico y modelos de gestión de los rebollares (Quercus pyrenaica Willd.) y de normas selvícolas para Pinus pinea y Pinus sylvestris L. en Castilla y León.

- 2004 – 2007: CPE-03-001-C5: Bases para la gestión sostenible de las masas de Pinus pinea L. en la península Ibérica: Modelos ecológicos-selvícolas, diversidad genética y valoración económica y social de las producciones

- 2007 – 2010: RTA2007-00-00044: La regeneración de P. sylvestris y P. pinea en el contexto del cambio climático: efecto de los factores ambientales

- 2008 – 2011: SUM2008-00002-00-00. Adaptación de los pinares mediterráneos de la península Ibérica al cambio climático: el manejo de la densidad.

- 2010 – 2013: S2009-AMB1668: REGENFOR. Regeneración de sistemas forestales en la CAM- 2011 – 2013: AGL 2010- 15521: Dinámica y gestión en masas heterogéneas de Pinus pinea: de

la respuesta fisiológica ala modelización a escala paisaje


Thank you verymuch for your

attention

Documents

Silviculture of stone pine: models and management tools · Pm = 140,1 g + 0,4 g mm-1 R2 = 0,82 0,000 kg 0,100 kg 0,200 kg 0,400 kg mm 200 mm 00 mm 00 mm 00 mm Precipitación del año