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Forest Policy and Economics 103 (2019) 17-27 



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Forest Policy and Economics 

journal homepage: www.elsevier.com/locate/forpol 



A simulation-based approach to assess forest policy options under biotic and r® 
abiotic climate change impacts: A case study on Scotland's National Forest 
Estate^ 

Duncan Ray 3 ’*, Michal Petr 3 , Martin Mullett , Stephen Bathgate 3 , Maurizio Marchi c , 

Kate Beauchamp 3 

a Forest Research, Roslin, Midlothian, Scotland, United Kingdom 
b Forest Research, Alice Holt Lodge, Surrey, England, United Kingdom 
c Council for Agricultural Research, Forest Research Centre, Arezzo, Italy 


ARTICLE INFO 


ABSTRACT 


Keywords: 

Forest policy analysis 
Uncertainty 
Climate change 
Abiotic impacts 
Biotic impacts 

Ecosystem goods and services 
Forest management simulation 


The future provision of forest goods and ecosystem services is dependent, among other factors, on climate 
change impacts, forest management, and response to forest policies. To assess policy implementation targets for 
Scotland's National Forest Estate under climate change, we simulated forest growth through the 21st century - 
with and without the abiotic impacts of climate change, and with and without the biotic impacts of an important 
fungal disease. Eight different forest management trajectories were simulated under a climate projection, to 
assess the future provision of forest ecosystem goods and services. Climate change was represented by the IPCC 
RCP 4.5 projection, and the biotic impact of Dothistroma needle blight was predicted using a new vulnerability 
matrix. Indicators of three important goods and services: timber production, standing biomass, and biodiversity 
were measured in the simulation of forest growth and reported at decadal intervals using dynamically linked 
forest models. We found that both a broadleaved species trajectory and a Forest Enterprise Scotland selected 
species trajectory would improve standing biomass and biodiversity, but slightly reduce timber volume. 
Dothistroma needle blight could reduce standing biomass (by up to 3tha _1 ) and timber volume (by up to 
5 m 3 ha -1 ), but the predicted impact is dependent on the type of forest management trajectory. Our findings 
show opportunities for diversifying forest management and tree species - and at the same time supporting forest 
policy to improve forest resilience under uncertain climate change and Dothistroma impacts. The forest simu¬ 
lation has been used to demonstrate and evaluate national strategic delivery of multi-purpose forest benefits in 
Scotland, and how species and management might be targeted regionally in Forest Districts, to maintain 
achievable national targets for timber production, carbon sequestration, and biodiversity under climate change. 


1. Introduction 

The sustainable multi-purpose management of forests in Europe 
involves the assessment of complex inter-related land management is¬ 
sues covering various aspects of environmental and biodiversity policy, 
as summarised in the EU Forestry Strategy (European Commission, 
2013). Forests provide multiple benefits to the public. These benefits 
relate to the concept of ecosystem goods and services (Millennium 
Ecosystem Assessment, 2005) that quantify the goods or benefits people 
derive from functioning ecosystems. Forests have attracted much re¬ 
search and policy interest on the subject of ecosystem goods and 


services (e.g. Schroter et al., 2005; Bateman et al., 2013; Quine et al., 
2011). Both managed and unmanaged forests provide a broad range of 
goods and services (Quine et al., 2011) compared to more intensive 
land management (e.g. intensive agriculture). 

Both the UK Government (UK National Ecosystem Assessment, 2011 
& 2014) and Scottish Government (Forestry Commission Scotland, 2006) 
have stated the need for a more sustainable ecosystems approach to land 
management. This requires policy implementation to guide land use and 
land management decisions with the aim of providing multiple eco¬ 
system goods and services now and into the future. Forest management 
in Scotland has for several decades considered multi-purpose benefits 


^ This article is part of a special issue entitled. “Models and tools for integrated forest management and forest policy analysis” 
103C, 2019. 

* Corresponding author. 

E-mail address: duncan.ray@forestry.gsi.gov.uk (D. Ray). 


published at the journal Forest Policy and Economics 


http://dx.doi.Org/10.1016/j.forpol.2017.10.010 

Received 31 October 2016; Received in revised form 4 October 2017; Accepted 9 October 2017 
Available online 06 November 2017 

1389-9341/ Crown Copyright © 2017 Published by Elsevier B.V. All rights reserved. 















D. Ray, et al 

(UK Forestry Standard, 2011) and this has led to a more targeted ap¬ 
proach in the delivery of goods and services at different geographic scales 
(Forestry Commission Scotland, 2013b) through a ‘strategic delivery’ 
approach of ecosystem services. Testing strategic delivery requires an 
assessment of the current and future state of woodlands to understand 
how management choices (reflecting direction and ownership objectives) 
in different areas will influence forest goods and ecosystem service 
provision (Ray et al., 2015). Scotland's publicly owned National Forest 
Estate (NFE) is therefore a good case study for assessing the implications 
of policy implementation under climate change. 

Forestry Commission Scotland's Climate Change Programme 
(2013a) outlines how the forest sector can become more resilient to the 
impacts of climate change. Approaches to adaptation in the UK and 
Scotland include: changes to species choice, increasing the area of na¬ 
tive woodland, selecting more southerly provenances, conversion to 
continuous cover forestry and increasing forest tree species diversity 
(Hemery et al., 2015). Changes in forest management will also impact 
ecosystem goods and service delivery, including timber production, the 
ability to support biodiversity, and carbon sequestration (Ray et al., 
2015; Beauchamp et al., 2016). As identified in Scotland's Adaptation 
Programme (Scottish Government, 2014) and in the ‘Low Carbon 
Scotland - Second Report on Proposals and Policies’ (Scottish 
Government, 2013), adaptation and mitigation strategies must be 
considered together. This will ensure that current mitigation efforts are 
well adapted to future climates, and that adaptation actions support 
mitigation measures; Scotland's forests must be resilient in order to 
deliver emissions abatement targets. 

Scotland's forest industry has emerged rapidly over the course of a 
century (1900-to date), with a change in forest land cover from ap¬ 
proximately 5% to 17% over the period. Its rapid emergence occurred 
in response to phases of forest policy (Harmer et al., 2015). Scotland's 
forest industry has been built on a few robust conifer species, e.g. Sitka 
spruce ( Picea sitchensis ), Scots pine (Pinus sylvestris ), larch ( Larix decidua 
and Larix kaempferi ), and Norway spruce ( Picea abies ) (Quine and Ray, 
2010). These were trialled on different sites and monitored with per¬ 
manent sample plots, where they showed good growth on a range of 
often challenging site types. 

An emerging issue of increasing concern to forests (Boyd et al., 2013), 
and forest managers (Petr et al., 2014), is the increased risk and impact of 
pests and pathogens. This is partly due to an increase in global trade 
(Pautasso et al., 2012; Roy et al., 2014) and partly climate change (Jung, 
2009; Tubby and Webber, 2010) which together have increased the spread 
and the risk of colonisation of pests and pathogens. The dynamics of many 
host-pathogen interactions are influenced by climate, thus climate change 
has the potential to exacerbate or alleviate both the chances of establish¬ 
ment of new pathogens and the emergence of pre-existing ones (Sturrock 
et al., 2011; Pautasso et al., 2012). Foliar fungal pathogens are particularly 
sensitive to temperature and water availability for sporulation, spread and 
infection and are likely to be effective indicators of environmental change 
(Harvell et al, 2002; Garrett et al., 2016). Dothistroma needle blight 
(DNB) affects at least 109 Pinaceae taxa, primarily Pinus spp., and is 
considered one of the most damaging diseases of pines worldwide, causing 
premature defoliation, a reduction in yield, and in extreme cases tree 
death (Drenkhan et al., 2016). In Britain, DNB is caused by Dothistroma 
septosporum and has been particularly serious on Corsican pine ( Pirtus nigra 
ssp. laricio), but also on lodgepole pine ( Pinus contorta var. latifolia) and 
Scots pine (Brown and Webber, 2008). It is thought that increasing pre¬ 
cipitation in the spring and summer months along with warmer tem¬ 
peratures leads to a greater risk of infection (Woods et al., 2016). 

Until recently, Scots pine, lodgepole pine and Corsican pine were 
being selected as suitable species for forest stands in the projected fu¬ 
ture Scottish climate (Ray, 2008). It is therefore of interest to forest 
policy and forest practice (Lindner et al., 2010) to consider pest and 
pathogen impacts in the context of changing climatic conditions and the 
maintenance of resilient forests into the future. This study is concerned 
with the potential impacts of climate change impacts, including DNB, 


Forest Policy and Economics 103 (2019) 17-27 

on the delivery of forest policies and forest management. 

The objective of this study is to demonstrate whether public sector 
forestry in Scotland can make a contribution to greenhouse gas abate¬ 
ment and timber production while maintaining high biodiversity and 
other important benefits. The options are simulated by forest models 
under the uncertainty of climate change and a forest pathogen. Possible 
adjustments to forest management systems and to tree species choice 
are tested to ascertain the continued provision of these forest ecosystem 
goods and services. 

2. Materials and methods 

2.1. Study sites 

In this study we focus on a forest growth and management simulation 
of the National Forest Estate (NFE) in Scotland and four forest districts in 
the north (North Highland District), south (Dumfries & Borders District), 
east (Moray & Aberdeen District) and west (Lochaber District) - (see Fig. 
S2 in online Supplementary material 1). These districts present different 
site conditions leading to variations in species composition, and different 
future climate change projections. Forestry Commission Scotland's stated 
policy of strategic delivery of benefits, plays on the strengths of different 
districts. For example, Lochaber and Dumfries & Borders are heavily 
focused on timber production, whilst Lochaber and Moray and Aberdeen 
have important recreation, biodiversity and community management 
interests. The current species composition of Scotland's forests (public 
and private sector combined), the NFE, and the four Districts are shown 
in Table 1 and Fig. SI (online Supplementary material 1). The NFE re¬ 
present the public forest managed by the Forestry Commission covering 
471,000 ha, approximately 33% of the forested area (Forestry 
Commission, 2016), and it is comprised of a broad species selection with 
a variety of management systems. The conifer species composition of the 
NFE and private sector are similar, but the NFE has a smaller area of 
broadleaf forest than the private sector. 

2.2. Input data 

2.2.1. Spatial Forest inventory and soil data 

The dynamically coupled models require spatially explicit forest 
inventory data showing the tree species, the age of the stand, and the 
current forest management system. This was possible using the Forestry 
Commission Sub-Compartment Database (SCDB) of the NFE. We used a 
digital soil map, based on a composite of the Soil Survey of Scotland soil 
associations mapped at a scale of 1:250,000 (Soil Survey of Scotland, 
1981), combined with higher resolution soil type data for areas of 
public forest where a digital soil layer mapped at a scale of 1:10,000 
was available. These soil data provided information about the soil 
quality in terms of soil moisture regime (SMR - soil wetness) and soil 
nutrient regime (SNR - soil fertility), where SMR and SNR are two of 
the six site quality factors used in the forest classification model, Eco¬ 
logical Site Classification (Pyatt et al., 2001). 

2.2.2. Spatial climate data 

To represent the future climate change impact on Scottish forests, 
we used the Representative Concentration Pathways (RCP 4.5) climate 
change projections of the IPCC Fifth Assessment Report (IPCC, 2014). 
The RCP 4.5 was matched to one single variant of the UK 11-member 
RCM Regional Climate Model (3Q14) using a Pearson correlation 
method (details in online Supplementary material 1). The projected 
3Q14 variant provided daily simulated values of temperature, pre¬ 
cipitation and potential evapotranspiration through the 21st Century. 
These were used to calculate monthly values for two of the the four 
climatic variables used in the forest model Ecological Site Classifica¬ 
tion, these were: Accumulated Temperature (AT - day degrees above 
5 °C) and Climatic Moisture Deficit (MD - accumulated excess of po¬ 
tential evapotranspiration over precipitation in mm units). 


18 


D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


Table 1 

Current species composition of the four Forest Districts using data from the Forestry Commission Sub-Compartment 
Database; Scotland's National Forest Estate (NFE) “Public Sector”, and Scotland's combined public and private forest 
“Scotland”(Forestry Commission, 2016). Values in the table are in hectares. 


Scotland's National & Regional Forest Composition 



U/o 

North Highland 

Lochaber 

Moray & 
Aberdeen 

Dumfries & 

Borders 

Public Sector 

Scotland 

QOther Broadleaves 

1083.61 

927.18 

1309.18 

1770.42 

15000 

73000 

R Alder species 

37.98 

91.69 

58.74 

21.16 

1000 

17000 

□ Ash 

1.54 

46.32 

25.54 

29.17 

1000 

16000 

□ Sycamore 

116.28 

0.83 

33.56 

53.58 

1000 

22000 

□ Beech 

8.9 

14.82 

132.77 

54.3 

1000 

15000 

ESOak species 

33.03 

152.44 

104.23 

156.53 

3000 

26000 

□ Birch species 

637 

1659 

874.7 

296.82 

11000 

128000 

H Other Conifers 

314.68 

157.16 

1381.59 

298.65 

5000 

14000 

□ Douglas Fir 

286.33 

167.15 

1044.87 

613.11 

5000 

12000 

□ Norway Spruce 

235.49 

684.24 

1742.22 

1608.54 

11000 

25000 

El Larches 

2043.55 

1249.88 

4431.02 

2823.5/ 

26000 

66000 

□ Lodgepole Pine 

16199.61 

3544.64 

3783.8 

960.75 

49000 

88000 

H Scots Pine 

6884.81 

1080.73 

11621.08 

926.06 

45000 

154000 

□ Sitka Spruce 

9756.73 

12187.81 

17345.07 

28688.19 

225000 

507000 


Climate data 

3Q14 variant (11-RCM) 
representing RCP 4.5 


Forest soil map 

Digital at low to 
moderate resolution 


Forest inventory 

Digital spatially explicit 
data on species and age 


Forest Management Trajectories 

Business as Usual - replace 
species and management like for 
like 

Diversification for Production - 
stand replaced with the most 
productive species 
CCF- transformation from one to 
two ages classes in a stand 
Short rotation forestry - same 
species, rotations at 25 years 
Native species - sites are 
replaced with native species at 
restocking 

Broadleaves only - restock with 
broadleaved species only 
No Sitka spruce - replace SS from 
a list of five well suited 
alternatives 
FES priority species - at 
restocking select one of the most 
suitable five species from a list of 
25 trialed in Scotland 


Forest site conditions 

Climatic - accumulated temperature, moisture deficit, DAMS 

(exposure), continentality 

Edaphic - soil moisture regime, soil nutrient regime 




Output results for three 

indicators of ecosystem goods 

and services at decadal 

intervals 


1. Total biomass 

2. Sawlog volume 

3. Biodiversity 


Annual management cycle 


Fig. 1. Schematic diagram of the simulation method of forest management trajectory scenarios on the National Forest Estate of Scotland. 


19 

















































































































































D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


Table 2 

Description of forest management trajectories with assumptions and constraints according rules dictated by site characteristics. 


Forest management trajectory (FMT) FMT description, assumptions and constraints 

Note: in all FMT types - Norway spruce (Picea abies) and Scots pine ( Pinus sylvestris ) are retained to provide red squirrel habitat. 


Business as usual (BAU) No change in species, stands are replanted with the current species. 

Thinning in sub-compartments where DAMS < 16. For no thin sub-compartments replace existing species at year 50. For thinning 
sub-compartments start at year 20 and then every 5 years to year 50, then fell and replace. 

Broadleaves only (BL2) Allows replanting selecting the most suitable broadleaf species. 

Continuous cover forestry (CCF) No change in species composition, stands regenerated with the current species. If site conditions suitable, a heavy thinning 

intervention is simulated at 25 years. 

Sub-compartments DAMS < 14 - marked FMA2 for conversion at year 50 - grow to year 50 thin to half the basal area. DAMS > 14 
and < 16 - thin as FMA 4 in BAU. Sub-compartments > 50 years classified as FMA 3 and grown to 100 years before felling. 

Diverse species (DIV) Selection of species using high predicted yield class for the site conditions from a selection of available 57 species in ESC. Continue 

same FMA allocation as in BAU, only species allowed to change after felling. Most suitable species for the sub-compartment site 
conditions for the rotation is chosen. No particular preference made for broadleaved trees or native trees. 

Sub-compartments > 50 years old allocated FMA 3 and felled at year 100. 

Forest Enterprise Scotland priority species Selection by highest yield class from a management list of 19 priority species suitable for timber production in Scotland. Continue 

(FESP) with the same FMA allocation as in BAU, only species allowed to change at time of felling. Broadleaves replace felled broadleaved 

stands, and larch and ash are excluded from replanting due to tree health limitations. 

Native species (NAT) Native species selected according to the suitability of the site for an NVC woodland type. Continue with the same FMA allocation as 

in BAU, only species allowed to change at time of felling. Norway spruce is replaced by Scots pine. 

No Sitka spruce (NOSS) Replacement species is selected at replanting, and available species are restricted to priority species with the addition of lodgepole 

pine (Alaskan) (Pinus contorta var. latifolia ) and rowan (Sorbus aucuparia) and grand fir ( Abies grandis ) on moist lowland sites to 
ensure sufficient species diversity. Continue with the same FMA allocation as in BAU, only species allowed to change at time of 
felling 

Short rotation forestry (SRF) No change in species composition, stands are replanted with the current species. SNR > very poor, SMR > Wet, and DAMS <16, 

otherwise the site is classed as unthinned FMA4. Sub-compartment stands are felled and replaced at age 25 years. 


DAMS - wind exposure, SNR - soil nutrient regime, SMR - soil moisture regime, FMA - Forest Management Alternative stand type. 


2.3. Forest simulation using dynamically coupled models 

2.3.1. Forest management trajectories under climate change projections 

We ran the coupled forest models to simulate tree growth, carbon 

sequestration, biomass, timber production and biodiversity on the NFE. 
The method builds on previous work described by Ray et al. (2015). A 
schematic diagram (Fig. 1) summarizes the simulation method. Three 
spatial datasets were used to simulate forest management through the 
21st century: climate projections at decadal intervals (2020s, 2030s, 
2040s etc); forest soils set as constants for the simulation; forest in¬ 
ventory data - initialised using the 2016 SCDB. The SCDB inventory 
was updated within each annual cycle of the model simulation to reflect 
changes in the forest structure and its management under eight dif¬ 
ferent management trajectories. The forest management trajectories are 
comprised of management systems and decision rules designed to im¬ 
plement different forest policy directions. They were created by ap¬ 
plying specific forest management systems to forest SCDB data in the 
simulation. For example: ‘Broadleaves only’ (Table 2) attempts to 
change species choice to broadleaved species when the opportunity 
arises at restocking; ‘No Sitka spruce’ attempts to remove and replace 
Sitka spruce stands with a mix of suitable alternative high yielding 
conifer and/or broadleaved species at the time of restocking. The tra¬ 
jectories simulated (Table 2) were: business as usual, species diversifi¬ 
cation for production, continuous cover forestry using a shelterwood 
system of two age components, short rotation forestry, native species 
selection, broadleaved species selection, species diversification without 
Sitka spruce, and finally species selection using Forest Enterprise Sco¬ 
tland's selected species for diversification. 

2.3.2. Forest management alternative simplification of the Forest inventory 
data 

The eight forest management trajectory types specify rules to si¬ 
mulate the different forms of forest management applied to the SCDB. 
To facilitate the diverse range of silviculture and species described by 
the SCDB, we simplified the forest inventory silvicultural descriptions 
into Forest Management Alternatives (FMA). Forest Management 
Alternatives, described by Duncker et al. (2012), provide a means of 
classifying differences in management intensity. They described five 
FMA types ranging from FMA type 1 Forest Reserve with no 


management, to FMA type 5 intensive single species short rotation 
forestry. Production forestry in Scotland is largely described by FMA 
types 3 and 4: “combined objective forestry” and “intensive even-aged 
forestry”, respectively. “Close to nature forestry”, FMA type 2, is in¬ 
creasing in Scotland in the form of continuous cover forest manage¬ 
ment, but has limited potential due Scotland's high wind exposure cli¬ 
mate. The FMA classification seeks to describe forest management 
intensity using criteria such as type of regeneration, level of machine 
operation, ground preparation, and size of harvesting coupes. As the 
forest model simulation progressed on an annual cycle, rules were ap¬ 
plied at the appropriate time in the rotation (Table 2) to the FMA types 
of the SCDB to maintain the selected forest management trajectory, and 
the forest inventory SCDB was updated. Any changes required by the 
forest management trajectory (thinning, felling, etc) were controlled by 
the rules applied to the SCDB to describe the particular forest man¬ 
agement trajectory running in the dynamically coupled models. 

2.3.3. DNB vulnerability matrix indicator evidence and approach 

Our addition of a DNB vulnerability model was based on a body of 
literature that associates outbreaks of DNB with spring and summer 
rainfall, particularly above average amounts (Watt et al., 2011; Welsh 
et al, 2014). Exact values vary but Woods et al. (2016) surmise that 
rainfall in excess of 100 mm per month in the warmer months leads to 
outbreaks of DNB, which are far less likely to occur when rainfall 
is < 50 mm per month. In Britain, high levels of infection were ob¬ 
served (Murray and Batko, 1962) when total rainfall exceeded 315 mm 
from June to September, while no outbreaks were seen when total 
rainfall during this period was below 175 mm. Needle wetness is more 
important than total seasonal or monthly precipitation in the germi¬ 
nation and infection of spores. Therefore, extended periods of needle 
wetness (e.g. due to frequent low-volume showers or mist) were as¬ 
sumed to lead to greater levels of disease than heavy downpours fol¬ 
lowed by long dry spells. The fungus is able to tolerate a wide range of 
temperatures, however, 16-20 °C is optimal for both infection and 
stomatal development (Gadgil, 1974, 1977). Overall, spring and 
summer rainfall along with temperature provide good indicators to 
estimate DNB severity. 

The vulnerability of a forest to DNB impact depends not only on the 
environmental conditions but also the host (e.g. more or less susceptible 


20 





D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


Table 3 

Classified values of tree vulnerability to Dothistroma needle blight (DNB) based on a) climatic characteristics of a stand, b) tree species/ 
provenance type, c) stand Forest Management Alternative (FMA), and d) the total vulnerability class and effect on stand yield, based on the 
sum of indices from a, b, & c. 


a) Climatic characteristic with DNB vulnerability levels (1 - low, 2 - medium, and 3 - high) 


AT Subalpine Cool Warm Very warm 

MD 


Wet 1 

Moist 1 

Dry 1 

Very dry 1 


2 

2 

2 

1 


3 

3 

3 

2 


3 

3 

2 

1 


b) Tree species DNB vulnerability 

HIGH MEDIUM LOW 

vulnerability vulnerability vulnerability 

Species Corsican pine, lodgepole pine Alaskan lodgepole pine, Scots pine Sitka spruce, Douglas-fir 

Shift 0 -1 -2 


c) FMA DNB vulnerability 

FMA1 

FMA2 

FMA3 

FMA4 

FMA5 

No thin 

0 

0 

+ 1 

+ 1 

0 

Thin 

N/A 

-1 

-1 

-1 

N/A 


d) Total vulnerability index of forest stands to DNB - impact on YC reduction 
Final Vulnerability Index DNB Vulnerability Class 


0 or < 0 
1 
2 

3 + 


VERY LOW 
LOW 

MODERATE 

HIGH 


Yield Impact 
None 

Reduce YC by 10% 
Reduce YC by 30% 
Reduce YC by 50% 


N/A = thinning not performed in FMA 1 (Semi-natural reserve) and FMA5 (Short rotation forestry). 


species) and pathogen (e.g. levels of inoculum in the area, virulence of 
strains) with the complex interaction between host, pathogen and en¬ 
vironment. The effect of DNB infection of primary concern to foresters 
is a reduction in growth, with radial increment more severely affected 
than height, although in extreme cases mortality may follow. Studies 
generally agree that at least 25% of foliage must be affected before 
losses in growth are measurable (Christensen and Gibson, 1964; 
Hocking and Etheridge, 1967; Whyte, 1969). A study on P. radiata in 
New Zealand showed that there was a proportional relationship be¬ 
tween disease level (percentage of foliage infected) and volume loss, so 
that, for example, an average disease level of 50% resulted in a volume 
loss of 50% after three years (Van der Pas, 1981). Once severely high 
levels of infection occur (i.e. 75% of foliage becomes affected) diameter 
increment practically ceases (Christensen and Gibson, 1964). 

To calculate the DNB impact on forest stands, we used the current 
knowledge to modify the yield class (YC) of pine species according to a 
classification method based on climatic characteristics (Table 3a), 
conifer and pine species vulnerability (Table 3b), and the forest man¬ 
agement alternative (Duncker et al., 2012) system used (Table 3c). Each 
table contains vulnerability values related to the potential DNB impact. 
We summed the values in the first three tables to obtain an overall 
vulnerability index, listed in the lookup table (Table 3d), which gives 
the yield adjustment applicable to the forest stand. 

The DNB vulnerability model used the following assumptions: DNB 
affects only pines, DNB infection is present in all pine stands (even 
though that might not be the case), a change in species choice can be 
applied only as a change in forest management system - not as a re¬ 
sponse to infection, infected stands are retained until the end of the 
rotation, and timber quality is unaffected. 

2.3.4. Dynamically coupled models and ecosystem goods and services 
indicators 

The dynamically coupled forest models used in the simulation were: 


Ecological Site Classification (Pyatt et al., 2001), ForestGALES 
(Gardiner and Quine, 2000), Forest Yield (Matthews, 2008), ASORT 
(Rollinson and Gay, 1983) and BSORT (McKay, 2003; Broadmeadow 
and Matthews, 2004), and our new DNB vulnerability matrix model 
(Section 2.3.3). 

1. Ecological Site Classification (ESC) is a forest site classification 
model using six site factors: - four climatic factors - accumulated 
temperature (AT -degree.days > 5 °C) which describes the growing 
season warmth; climatic moisture deficit (MD -mm) describing the 
relative wetness or droughtiness of the growing season; wind ex¬ 
posure (DAMS score); continentality (Conrad index): - and two soil 
quality factors - Soil Moisture Regime (SMR) or soil wetness; and 
Soil Nutrient Regime (SNR), or soil fertility. ESC predicts the site 
potential for a given species in the form of a general yield class. 

2. ForestGALES is a wind risk model that calculates the risk of wind 
damage, either windthrow, or stem breakage, to forests stands. 

3. Forest Yield provides estimates of various aspects of tree growth 
(height, diameter at 1.3 m) by stand age, for a range of tree species, 
yield classes and management prescriptions. 

4. ASORT is an assortment model to provide estimates of potential 
timber production volumes. 

5. BSORT estimates the tree size class distribution and through allo- 
metric equations the biomass per hectare by size components. 

The models use the SCDB forest inventory and a set of rules 
(Table 2) based on forest management principles to form the eight 
forest management trajectories, applied to individual forest stand FMA 
types, and described spatially within a Geographic Information System, 
with and without both the climate change projections, and the effects of 
the DNB vulnerability matrix. 

For each of the forest management trajectories, we calculated three 
ecosystem goods and services indicators (online Supplementary 


21 









D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 




decade 

Fig. 2. Change in the provision of standing biomass on the (NFE) under climate change a) 
comparing forest management trajectories without DNB impact to business as usual 
(BAU) (standing biomass in the 2010 for BAU around 48.6 Mt), and b) changes due to 
DNB impact. 


material 2): 1) standing biomass (t ha - 1 ), 2) harvested timber volume 
(m 3 ha -1 ), and a forest biodiversity index (index ha -1 ). Standing 
biomass is a good that stores carbon (regulating service) and when 
harvested, can be used as timber in construction (provisioning service), 
is used for pulp in making paper (provisioning service), or as biomass 
for renewable energy (provisioning service). When used in the latter 
way it also substitutes fossil fuel use (regulating service). 

Biomass and timber volume were based on a predicted site yield 
from Ecological Site Classification and growth using Forest Yield, and 
then calculated using ASORT (timber volume) and BSORT (biomass). 
The biodiversity index used was based on a method developed by 
Humphrey et al. (2002, 2004), based on the age of a stand and its FMA 
type. The coupled model outputs have an annual time step, and results 
from the models were compiled and reported at decadal intervals. 


3. Results 

3.1. Changes in ecosystem goods and services on Scotland's National Forest 
Estate 

The findings highlight changes in the provision of three ecosystem 
goods and services under a single climate change scenario, using dif¬ 
ferent forest management trajectories. In this section we present results 


for the NFE in Scotland at decadal intervals between the RCP4.5 climate 
projection and the baseline climate, exploring changes in standing 
biomass, timber production and biodiversity. 

3.1.1. Biomass 

The variability in standing biomass provision under different man¬ 
agement trajectories on the whole NFE (Fig. 2a) shows that in the long 
term (50-70 years) an increase from the business as usual management 
will occur for native species, broadleaved species, and continuous cover 
forest management. This resulted in increases of up to 40 t ha - 1 com¬ 
pared to business as usual. The continuous cover silviculture showed a 
steady increase through the period. However, broadleaves and native 
species management trajectories showed a steep increase from 2040 at 
which time business as usual (largely fell-restock systems) stands began 
to be felled at the age of maximum mean annual increment. In contrast, 
the largest reduction of up to 20tha -1 was projected for the short 
rotation forestry management, with modelled rotation lengths of only 
25 years. 

The diverse and small impacts of DNB depend on the type of forest 
management trajectory (Fig. 2b). At initialisation of the forest model 
simulation, DNB was predicted to reduce standing biomass across the 
NFE by approximately 2tha -1 (-1.7%). We see that some forest 
management trajectories improved the negative biomass impact of 
DNB, especially broadleaved and FE selected species (FESP) in Scot¬ 
land- since these management trajectories gradually removed high risk 
species; Corsican pine and lodgepole pine. Broadleaved management 
(with reliance on birch species), was predicted to increase biomass 
compared to business as usual management, and may also mitigate DNB 
impacts. 

In contrast, other management trajectories were projected to con¬ 
tinue to maintain a reduced standing biomass compared to business as 
usual. These include: no Sitka spruce; low impact silviculture; and short 
rotation forestry - since these three management trajectories main¬ 
tained both Corsican and lodgepole pine. 

3.1.2. Timber Production 

A decrease in timber volume (TDC17 - diameter above 17 cm) was 
projected across all management trajectories (Fig. 3a), mainly due to 
the currently optimised high timber production of fast growing Sitka 
spruce using fell-restock silviculture. Therefore, the current composi¬ 
tion of tree species and management (business as usual) maintained the 
highest provision of timber. On the NFE, we predicted a 50 m 3 ha -1 
reduction in timber production, if all stands suitable for short rotation 
forestry were transformed by the 2080s. In contrast, a general trans¬ 
formation to more continuous cover forestry projected little effect on 
timber production, since this management trajectory would be possible 
on a relatively small proportion of the NFE - forest stands not con¬ 
strained by wind exposure. Diversifying species selection or selecting 
favoured FES species (FESP) would cause a small reduction in pro¬ 
duction by 2060 (< 10 m 3 ha -1 ). This reduction was predicted to 
change to 20-25 nAa' 1 by 2080, as slower growing species compared 
to Sitka spruce would become more widespread on sites for which they 
were more ecologically suitable. By gradually removing Sitka spruce 
from all stands at restocking, the production forecast would reduce by 
10 m 3 ha -1 in 2060 and by 50 m 3 ha -1 by 2080, again because of 
replacement by lower yielding species. 

The impact of DNB on timber volume was projected to be similar 
across all forest management trajectories until the 2060s (Fig. 3b), with 
the reduction of approximately 4 m 3 ha - 1 (3%). Then, DNB impacts 
were shown to diverge with the most negative effects on short rotation 
forestry and business as usual and the least negative effects on broad¬ 
leaved species management trajectories. 

For production, all forest management trajectories provided less 
timber in the future in contrast to business as usual, but DNB was 
projected to have a major impact on the business as usual management. 
Comparing the diverse species management (DIV) with the favoured 


22 






D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


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decade 

Fig. 3. Change in the timber volume production on the National Forest Estate (NFE) 
under climate change a) from BAU to other forest management trajectories without DNB 
impact (timber volume in the 2010 for BAU around 4.4 mil m 3 ), and b) due to DNB 
impact. 

bau o div + ccf noss B 

^ b!2 A fesp x nat V srf * 


03 



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decade 



Fig. 5. Changes in the provision of standing biomass in four Forest Districts (Moray & 
Aberdeen (standing biomass in 2010 around 5.4 Mt), North Highland (standing biomass 
in 2010 around 3.2 Mt), Dumfries & Borders (standing biomass in 2010 around 4.8 Mt), 
and Lochaber (standing biomass in 2010 around 3.7 Mt)) under climate change a) from 
BAU to other forest management trajectories without DNB impact, and b) due to DNB 
impact. 

species selection (FESP), the forest simulation showed the former would 
be impacted more severely by DNB as the latter FESP selection does not 
include Corsican pine or lodgepole pine. 

3.1.3. Biodiversity 

Fig. 4 shows changes (compared to the business as usual manage¬ 
ment system) in the provision of biodiversity - using a relative indicator 
(1 = low and 10 high). The main increase in biodiversity by up to 
0.6 units was shown to occur for continuous cover management. In 
contrast, the main decrease, by up to 0.4 units, occurred for short ro¬ 
tation forestry, while other management trajectories ensured a similar 
provision of biodiversity to business as usual. DNB would have no im¬ 
pact on biodiversity using the remaining management trajectories, as 
the index is not sensitive to species changes in pine forests. 

3.2. Changes in ecosystem goods and services for individual districts 


Fig. 4. Change in the provision of biodiversity on the NFE under climate change from 
BAU to other forest management trajectories without DNB impact. 


In this section we present results showing changes in standing bio¬ 
mass, timber production and biodiversity index under climate change 
and for different management trajectories for four Forest Districts of the 
NFE (see Fig. S2 - online Supplementary material). The districts are 
Moray and Aberdeen in the east, North Highland in the north, Dumfries 


23 

























D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


and Borders in the south, and Lochaber in the west of Scotland. 


a 


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bl2 


o 

A 


div 

fesp X 


ccf 

nat V 


noss E) 

srf * 


3.2.1. Biomass 

As in Fig. 2a on the NFE, biomass provision was shown to increase 
gradually in all four districts (Fig. 5a) under the continuous cover for¬ 
estry management trajectory, slightly more in Lochaber and Moray & 
Aberdeen than in North Highland and Dumfries & Borders due to a 
greater proportion of suitable sites for CCF in the former two districts. 
In Moray & Aberdeen, Dumfries & Borders and Lochaber the changes in 
biomass production among management trajectories were very similar 
to the NFE national results. In North Highland there was a large in¬ 
crease in biomass provision for native species selection and broadleaved 
species, largely because of the availability of suitable sites for native 
birch species under warmer climatic conditions, which is expected to 
improve the yield. 

Three districts (Lochaber, Moray & Aberdeen, and Dumfries & 
Borders) showed a smaller proportion of lodgepole pine than North 
Highland, leading to an initial DNB impact reducing biomass provision 
by approximately 4 t ha - 2 (Fig. 5b). In North Highland, a much larger 
reduction in biomass due to DNB was predicted for the business as 
usual, continuous cover and short rotation forestry (up to 12 tha -1 ). 
For these management trajectories the species present at initialisation 
was maintained through to 2080, leading to the continuation of large 
areas of lodgepole pine, and larger impacts from DNB. In Moray & 
Aberdeen, Scots pine is widely distributed, and the results showed a 
medium impact of DNB reducing biomass provision by approximately 
4 tha -1 which decreased slightly from 2060 and then increased 
slightly by 2080. 

3.2.2. Timber production 

Compared to business as usual, the forest simulation showed re¬ 
ductions in timber production volume for all management trajectories 
in Moray & Aberdeen, Lochaber, and Dumfries & Borders districts, with 
the largest reductions (50-100 m 3 ha - 2 ) in the latter district by 2080 
(Fig. 6a). Lochaber and Dumfries & Borders have large proportions of 
Sitka spruce, and the results showed spatial differences in the way 
climate change and management trajectories interact between the south 
of Scotland (drier summers) and western Scotland (wetter summers), 
which caused the variation in the production volumes. Compared to 
business as usual, results for the FESP preferred species selection 
showed similar production targets as business as usual in Lochaber by 
2070 and 2080 (20-25 m 3 ha - 2 ), but greater reductions in production 
in Dumfries and Borders in 2070 and 2080 (50 m 3 ha -1 ). Similarly, 
results for the native species management trajectory showed production 
losses of 75-100 m 3 ha -1 in Dumfries & Borders, and < 50 m 3 ha - 1 in 
Lochaber. 

Changes in Moray & Aberdeen followed a similar pattern to 
Lochaber, but in North Highland the results showed production benefits 
to be gained over business as usual in moving to FE preferred species 
(FESP), native species, species diversity, and broadleaved species 
management trajectories. DNB impacts were shown to be greater in 
Moray & Aberdeen, and North Highland (Fig. 6b) where Scots pine, 
Corsican pine and lodgepole pine are currently more extensively 
planted than in the other two districts. Unsurprisingly, in both districts 
a change to broadleaved species and/or native species was shown to 
reduce DNB impacts. Dumfries & Borders currently has much less pine 
and is largely unaffected by DNB. 

3.2.3. Biodiversity 

The same changes in biodiversity as described for the NFE (see 
Fig. 4) were shown to occur in each of the four districts (Fig. 7). Con¬ 
tinuous cover systems produced increases in the biodiversity index and 
the short rotation forestry trajectory reduced the biodiversity index. 
The DNB vulnerability matrix model had no impact on the biodiversity 
index. 


03 

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1 1 1 1 1 1 


2020 2040 2060 2020 2040 2060 

decade 


Fig. 6. Change in timber volume production in four Forest Districts (Moray & Aberdeen 
(timber volume in 2010 around 0.55 mil m 3 ), North Highland (timber volume in 2010 
around 0.28 mil m 3 ), Dumfries & Borders (timber volume in 2010 around 0.43 mil m 3 ), 
and Lochaber (timber volume in 2010 around 0.39 mil m 3 )) under climate change a) from 
BAU to other forest management trajectories without DNB impact, and b) due to DNB 
impact. 


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Fig. 7. Change in the provision of biodiversity in four Forest Districts (Moray & Aberdeen, 
North Highland, Dumfries & Borders and Lochaber) under climate change a) from BAU to 
other forest management trajectories without DNB impact, and b) due to DNB impact. 


24 




























D. Ray, et al 

4. Discussion 

4.1. Sensitivity of ecosystem goods and service delivery to changes in 
management choices, climate and disease 

This study investigated ways in which the public sector forestry in 
Scotland can make a contribution to greenhouse gas abatement and 
timber production while maintaining high biodiversity and other im¬ 
portant benefits. Scottish forest policy encourages species and forest 
management diversity, and the use of strategic targeting to meet mul¬ 
tiple objectives. The results show the National Forest Estate's im¬ 
plementation of policy will deliver these intended benefits. In parti¬ 
cular, given an RCP4.5 climate projection, with associated abiotic and 
DNB impacts, the production forecast could be maintained, or would 
suffer only small reductions. This outcome could be achieved by in¬ 
creasing the use of continuous cover forestry systems and by introdu¬ 
cing more Forest Enterprise Scotland favoured species (FESP). Such a 
change would also maintain the forest biodiversity index. The com¬ 
bined abiotic and biotic analysis is an example case study that will help 
policy developers assess the sensitivity of forest ecosystem goods and 
services to changes in climate and pathogens (Lindner et al., 2010), and 
improve understanding of trade-offs resulting from different policy and 
practice decisions (Seidl and Lexer, 2013). 

Our dynamically coupled forest model predicts that DNB could re¬ 
duce standing biomass (by up to 3 t ha - *) and timber volume (by up to 
5 m 3 ha -1 ). The impact is dependent on the type of forest management 
systems applied and introducing FESP would reduce this impact. 

We demonstrated how interactions between management systems 
and abiotic and biotic climate impacts differ among regions in Scotland. 
In North Highland and in Moray & Aberdeen particular changes in 
species and silvicultural management (less pine more broadleaved 
species; more continuous cover systems) would improve biomass pro¬ 
vision and timber production, and at the same time relieve the current 
impact of DNB, and improve biodiversity in forests. 

4.2. Use of simulation tools in understanding forest policy implementation 

There are relatively few models that can examine policy options and 
forest management scenarios together. Notable examples include the 
European Forest Information Scenario model (EFISCEN) (Schelhaas 
et al., 2015), which has been used to analyse large scale applications of 
climate change abiotic effects (Hanewinkel et al., 2012; Verkerk et al., 
2014) and also regional forest biotic disturbances (Seidl et al., 2009) 
with the patch-based model PICUS (Lexer and Honninger, 2001). For 
national and district analyses where detailed FMA descriptions, soil 
types, and climate scenarios are available, our dynamically coupled 
model approach can examine the effects of implementing forest policy 
in different ways, in different places and at different times into the 
future. The approach can accommodate the effects of forest planning on 
policy targets, by accumulating goods and services to regional and 
national scales. 

The decision support tool used in this study is not intended to be 
used by forestry professionals alone, but jointly with forest scientists to 
assess scenarios and future implications of current policy and practice. 
This will enable capacity building (Grainger, 2012) and help manage 
uncertainty (Petr et al., 2014) within the National Forest Estate and, 
with modifications, within private forests. 

The novelty of the forest model simulation is the multi-scale tem¬ 
poral view of forest policy implementation and future outcomes. The 
decision support tool uses ecosystem service indicators to appraise the 
combinations of forest management, and climate change abiotic and 
biotic impacts and can explore the notion of resilient forests meeting 
their intended delivery of ecosystem goods and services into the future 
(Ray et al., 2015). 

It has been argued (Buizer and Lawrence, 2014), that re¬ 
commendations for mitigation have used a more quantitative approach 


Forest Policy and Economics 103 (2019) 17-27 

than recommendations for adaptation. This is because adaptation is 
concerned more with changing forestry professional's frames on tree 
species selection and/or silvicultural systems. Our approach uses high 
resolution spatial data in a multi-scale analysis which can provide re¬ 
commendations tailored to forest regions and ecosystem services. Such 
results can be used in novel action expiration charts (Petr et al., 2016) 
for knowledge exchange with forestry professionals. The combination 
of simulations with the action expiration chart methodology also partly 
answers the Buizer and Lawrence (2014) recommendation to “engage 
with both the social and ecological complexity and value conflicts” in 
climate change adaptation discourse, through a dynamic spatial and 
temporal scenario assessment. 

4.3. Opportunities for stakeholder involvement in simulation assessment 

The mix of policy, management objectives, economic benefits and 
natural science is very much a multidisciplinary complex system 
(Costanza, 2001) involving forest policy makers, practitioners and sci¬ 
entists. It is in this area of uncertainty and mixed objectives that the 
simulation approach shows much potential. Our results have been used 
in discussions at the national level on forest policy, and at the forest 
district level regarding maintaining the multiple objectives of forestry. 
This has helped show how Forestry Commission Scotland's ‘strategic 
directions’ policy can target regional resources to provide particular 
benefits at the national level (Forestry Commission Scotland, 2013b), 
rather than each district being expected to deliver on ‘aspirational 
targets’ for all ‘key commitments’. The work has helped inform the 
potential of alternate land management plans at the district scale to 
deliver recreation and biodiversity benefits (Beauchamp et al., 2016) 
requested in community discussions. 

5. Conclusions 

If large forestry enterprises, ignore information on likely abiotic and 
biotic impacts of climate change, and ignore policy recommendations, 
there is a risk of loss of production and a reduced resilience of forest 
stands. Scotland's National Forest Estate delivers important forest eco¬ 
system goods and services (Ray et al., 2016; Sing et al., 2015), and we 
have shown under the uncertainty of climate change, how spatio-tem¬ 
poral scenario forest model simulations can inform solutions for the 
targeted delivery of benefits (Forestry Commission Scotland, 2013b). 
Furthermore, we have shown how forest model simulations can explore 
scenarios and show differences in the interactions between forest 
management trajectories, species choice, abiotic and biotic impacts. 
Our results support the policy of targeted delivery, and this leads us to 
believe that better informed decisions will improve future forestry ob¬ 
jectives and strategic delivery, compared to trial and error manage¬ 
ment. 

Our decision support tool currently extends to Scotland's National 
Forest Estate, which covers one third of Scotland's forest area. The 
principles of our findings can not be extended to the remaining area, 
due differences in species composition between the public and private 
ownerships (see Supplementary material) due to the underlying dif¬ 
ferences in soil and climatic conditions; so we plan to develop private 
sector case studies. In addition, other pest/pathogen models could be 
developed and incorporated to test combined abiotic/biotic climate 
change impacts. 

Our approach applied single forest management trajectories across 
the National Forest Estate to assess and compare the impact of one 
trajectory with others. In practice, the forest simulation would test land 
management plans and strategic plans where different forest manage¬ 
ment trajectories could/should be spatially targeted to meet forest ob¬ 
jectives and ecosystem goods and service provision. 


25 


D. Ray, et al 


Forest Policy and Economics 103 (2019) 17-27 


Funding and acknowledgements 

The study was funded by Forestry Commission GB within the re¬ 
search programmes of the Forest Research Science and Innovation 
Strategy (ISBN:978-0-85538-903-l). The work was completed as a case 
study for Working Group 2 of the European COST Action FP1207 
(Orchestra) - Orchestrating forest policy implementation in Europe. We 
are grateful for comments from two reviewers and the editor, and to 
Professor Chris Quine for helpful comments on an earlier draft. 

Appendix A. Supplementary data 

Supplementary data to this article can be found online at https:// 
doi.org/10.1016/j.forpol.2017.10.010. 

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