Describing a recent drought-related forest dieback event in south-western Australia in 2011 (Matusick 2012), a colleague remarked upon the distinctive sounds of wood boring beetles feeding on weakened eucalypt trees during one of the most severe droughts on record (K. Ruthrof, personal communication). For this insect population, normally scarce and benign, drought stress had most likely triggered a surge in their abundance, thereby amplifying declines in forest health during an already stressful event. Observations of an apparent coincidence of stressors such as drought and pests are of course common across many ecosystems (Mattson and Haack 1987, Ayres and Lombardero 2000). The subsequent impacts on forest function and structure from stressors such as drought and herbivory represent complex interactions between abiotic and biotic factors (Raffa et al. 2008).

During its lifetime, a tree faces a diverse range of conditions arising from the combination of climatic, soil and pest dynamics and disturbances that may induce periods of stress, culminating in reduced growth, vigour, canopy dieback or mortality. Based on the sequence, timing and intensity of these stressors, their associated impacts may be persistent or acute and manifest over different temporal and spatial scales. For example, recent observations of episodic mortality from acute drought stress across the USA, Europe and Australia highlight the role of single extreme events (Martínez-Vilalta and Piñol 2002, Breshears et al. 2005, Matusick 2012), while longer term forest declines result from persistent and subtle stress interactions that make identifying specific causes more difficult (Manion 1981, Close and Davidson 2004). It is increasingly suggested that forests in the future will experience increased levels of stress as a result of the direct impacts of shifting ­climatic patterns, increasing atmospheric [CO2], land use change and associated feedbacks on processes such as pest demographics, invasive species and host susceptibility (Intergovernmental Panel on Climate Change 2007). Any assessment of future forest vulnerability must consider the differential contributions from single and multiple stress factors and how their timing, intensity and frequency may interact to affect individuals, stands and ecosystems.

Climate is arguably the most influential factor affecting vulnerability in managed and unmanaged forests due to its role as a primary or underlying stress, that precedes or enables the arrival and expansion of associated biotic stressors (Figure 1a) (Kurz et al. 2008). Drought itself is not a proximal stress but the cause of multiple stresses that impact on trees (Figure 1a) and is often characterized by multiple stressors: i.e., large water deficits and high temperatures/heat waves (Allen et al. 2010). In turn, these can interact with carbon and water dynamics differentially (McDowell et al. 2008). In many cases the primary stress such as drought promotes the presence of secondary stressors such as insects or pathogens via a weakening of plant defences (Boyer 1995), changes in pest distributions and disruption of food webs that would otherwise be kept in check (Figure 1a) (Carnicer et al. 2011).

Figure 1.

Conceptual representation of multiple stressors and how they interact. (a) Flow diagram of key interactions between primary, secondary and conditioning factors that determine physiological stress. Primary stress is imposed directly or in association with secondary stress via the conditioning factors that give rise to a range of responses at the stand or ecosystem level. Acclimation is triggered by previous stress events and plays an important role in modulating the current stress via structural or functional adjustments. (b) A hypothetical scenario of the changes in the importance of primary, secondary and multiple stressors on tree vigour across different stress intensities. The two stressors are herbivory (solid black line) and drought (solid blue line) and their interaction for any given intensity is represented by the drought × herbivory line (grey, dot-dash). Under this scenario, at high intensities drought is capable of reducing vigour to zero (death), whereas herbivory has lesser impacts on vigour. The trajectory of the additive impact of the two stressors, i.e., drought + herbivory, is given as a reference (dashed line). The positioning of the drought × herbivory line below the additive impact line indicates a synergistic effect (multiple stress impact is greater than the sum) and above the additive impact line indicates an antagonistic effect (multiple stress impact is less than the sum). In this scenario, the stress impacts of drought × herbivory on tree vigour are determined by ‘multiple stress effects’ at low to moderate intensities up until some threshold value (vertical dashed line). Beyond this threshold, the drought × herbivory line converges on the drought stress line, indicating tree vigour is solely determined by the ‘primary stress effect’ (drought in this case).

Figure 1.

Conceptual representation of multiple stressors and how they interact. (a) Flow diagram of key interactions between primary, secondary and conditioning factors that determine physiological stress. Primary stress is imposed directly or in association with secondary stress via the conditioning factors that give rise to a range of responses at the stand or ecosystem level. Acclimation is triggered by previous stress events and plays an important role in modulating the current stress via structural or functional adjustments. (b) A hypothetical scenario of the changes in the importance of primary, secondary and multiple stressors on tree vigour across different stress intensities. The two stressors are herbivory (solid black line) and drought (solid blue line) and their interaction for any given intensity is represented by the drought × herbivory line (grey, dot-dash). Under this scenario, at high intensities drought is capable of reducing vigour to zero (death), whereas herbivory has lesser impacts on vigour. The trajectory of the additive impact of the two stressors, i.e., drought + herbivory, is given as a reference (dashed line). The positioning of the drought × herbivory line below the additive impact line indicates a synergistic effect (multiple stress impact is greater than the sum) and above the additive impact line indicates an antagonistic effect (multiple stress impact is less than the sum). In this scenario, the stress impacts of drought × herbivory on tree vigour are determined by ‘multiple stress effects’ at low to moderate intensities up until some threshold value (vertical dashed line). Beyond this threshold, the drought × herbivory line converges on the drought stress line, indicating tree vigour is solely determined by the ‘primary stress effect’ (drought in this case).

The paper by Bansal et al. (2013) in this issue directly addresses the role of singular and combined impacts of drought and herbivory on plant functioning. The paper demonstrates that the impacts of multiple stressors on leaf gas exchange and growth traits are not always equal to the sum of the parts and are instead ‘antagonistic’ (less than the sum of the impacts from the singular stressor). Similarly, the interactive effects of elevated [CO2] and temperature on herbivory are generally opposing; increasing [CO2] diminishes leaf quality for herbivores in host plant species independent of temperature, while higher temperature may enhance herbivore activity through changes in metabolism and partially compensate for these reductions in plant quality (Zvereva and Kozlov 2006, Murray et al. 2012). These types of emergent responses show that secondary stressors such as bark herbivory can act to both dampen and amplify the effects of a primary stressor, such as drought, presumably via changes in carbon balance and feedbacks on growth and photosynthesis (Pinkard et al. 2011).

The intensity of single stress events such as drought has important consequences for the impacts of subsequent stressors (Jactel et al. 2012). As drought stress progresses, cell expansion and growth are often the first casualties of water deficit, followed by a cessation of photosynthesis (Hsiao et al. 1976), and the eventual breakdown of water and sugar transport (Hölttä et al. 2009). The addition of a secondary stressor for a given drought intensity can act to preserve or further disrupt these processes. The study by Bansal et al. (2013) considered a range of both drought and herbivory intensities and found that the impacts of multiple stressors were dependent on the stress intensity of one or both of the stressors. For example, the combined impacts of drought and herbivory at moderate intensities reduced radial growth to a larger extent than when either of these stressors were severe (Bansal et al. 2013). Figure 1b provides a hypothetical representation of why predicting the impacts from multiple stressors is notoriously complex and difficult. Primary and secondary stressors such as drought and herbivory presented in this example have differing levels of impacts individually at any given intensity. However, their interactive impact is not always additive, as demonstrated by Bansal et al. (2013), and may be a function of intensity of one or either of the stressors (Figure 1b). The importance of intensity of one or both stressors underscores the role of threshold dependence on emergent relationships between the stress and physiological responses across the whole plant. The response of photosynthesis to combined effects of elevated [CO2] and drought stress is a clear example of this; at high soil water contents the enhancement of photosynthesis from high [CO2] is realized, yet as soil water declines below a threshold value the impacts of drought on stomatal closure overwhelm [CO2]-mediated increases in photosynthesis (Centritto et al. 1999). The temporal dynamics of stressors are also critical to assessing stress interactions particularly where the primary stress is characterized by low to moderate intensities and longer durations or higher frequencies. In the case of drought, the duration of the event can promote carbon depletion through prolonged periods of low to zero assimilation (Mitchell et al. 2013), while enhancing the period of exposure to biotic agents that can further reduce vigour and the ability to recover (Galiano et al. 2011).

Evaluating recovery often provides a better gauge of the combined severity of the stress than observations made during the stress event. A seemingly severe drought event for a species capable of resprouting may merely manifest as a ­transient loss of above-ground tissues that can be rapidly regrown and represent an adaptive strategy that helps a species avoid dehydration. Broadly speaking, both symptomatology and interpretation of event severity must be considered from a ‘plants-eye’ view in the context of the species adaptive life strategies. Tracking the trajectory of physiological responses such as growth beyond the climatic event may also reveal the extent to which the stress was transient, delayed or sustained and elucidate the contributions of resistance and resilience-based strategies for plant through to ecosystem responses (Mitchell et al. 2013). Bansal et al. (2013) as well as others (Jacquet et al. 2013) have shown that recovery is hampered by high-intensity drought in the previous year and not herbivory. Patterns in stress response and recovery reflect the history of stressors on growth, carbon and water status and instil some level of ‘physiological memory’ that may affect the severity of future stressors on survivorship (Loehle and LeBlanc 1996; Niinemets 2010). The state and conditioning of the system at the time of an event impacts on the event severity from a plant or community perspective—the event severity or physiological stress is not independent of the system state (Figure 1a). For example, an analysis of radial growth patterns in pinyon-pine stands after severe drought showed that regardless of site condition, patterns of tree mortality were associated with reduced and more variable ring widths in the preceding 10–15-year period (Ogle et al. 2000). The mechanisms of recovery can impose serious metabolic costs that delay a return to pre-stress levels as demonstrated by the impact of cavitation on water transport during severe drought. Brodribb et al. (2010) found that recovery of gas exchange via the restoration of hydraulic conductance tracks the growth of new xylem tissues, suggesting that recovery imposes significant carbon costs after drought.

Stress impacts at the stand level are rarely uniform and emphasize the view that the observed responses of individual trees are a function of conditioning factors such as stress history and tolerance, ontogeny, competition and acclimation (Figure 1a). In the real world, no two events are identical—the preconditions and the progression of the stress event are always unique. Capturing some of the important drivers of stand-level variation involves a shift from deterministic thinking that invokes one-to-one causality to a more probabilistic way of thinking. Within a probabilistic context, processes such as forest stand mortality are viewed as a manifestation of the individual responses and performance of the constituent trees. Modelling frameworks appropriate for this task will need to consider a hierarchy of multiple stressors and interactions with their environmental drivers and distribute them within the forest landscape using probabilistic approaches that can provide an assessment of future risk and uncertainty in key forest processes. Hierarchical Bayesian modelling approaches are an ideal candidate in that they facilitate the synthesis of diverse data sources such as controlled experiments, environmental drivers (climatic, pest dynamics, soils), stand-level response data and mechanistic/process-based models (Ogle and Barber 2008, Cable et al. 2009, Metcalf et al. 2009).

Studies such as Bansal et al. (2013) elucidate the direction and severity of multiple stress interactions that would not be predicted by considering the singular stress impact in isolation. Extrapolating this growing body of experimental studies on multiple environmental stressors into the real world is one of the key challenges in forest and ecosystem science. Within the framework that we have proposed, multiple stress interactions need to be considered across a range of intensities, durations (that include the recovery period) and frequencies within the state and conditioning of the system in which they are occurring. Obtaining such data is unlikely and we emphasize the role of merging experimental data, field observational data and process models within an appropriate hierarchical and probabilistic framework. A suitable approach will be when one captures the impacts of stressors across heterogeneous stands that reflect underlying responses of a collection of individuals and provide a means of propagating parameter uncertainty across scales from trees through stands to landscapes.

References

Allen
CD
Macalady
AK
Chenchouni
H
et al
(
2010
)
A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests
.
For Ecol Manag
 
259
:
660
684
.
Ayres
MP
Lombardero
MJ
(
2000
)
Assessing the consequences of global change for forest disturbance from herbivores and pathogens
.
Sci Total Environ
 
262
:
263
286
.
Bansal
S
Hallsby
G
Löfvenius
MO
Nilsson
M-C
(
2013
)
Synergistic, additive and antagonistic impacts of drought on herbivory on Pinus sylvestris: leaf, tissue and whole-plant responses and recovery
.
Tree Physiol
 
33
:
451
463
.
Boyer
JS
(
1995
)
Biochemical and biophysical aspects of water deficits and the predisposition to disease
.
Annu Rev Phytopathol
 
33
:
251
274
.
Breshears
DD
Cobb
NS
Rich
PM
et al
(
2005
)
Regional vegetation die-off in response to global-change-type drought
.
Proc Natl Acad Sci USA
 
102
:
15144
15148
.
Brodribb
TJ
Bowman
DJMS
Nichols
S
Delzon
S
Burlett
R
(
2010
)
Xylem function and growth rate interact to determine recovery rates after exposure to extreme water deficit
.
New Phytol
 
188
:
533
542
.
Cable
JM
Ogle
K
Tyler
AP
Pavao-Zuckerman
MA
Huxman
TE
(
2009
)
Woody plant encroachment impacts on soil carbon and microbial processes: results from a hierarchical Bayesian analysis of soil incubation data
.
Plant Soil
 
320
:
153
167
.
Carnicer
J
Coll
M
Ninyerola
M
Pons
X
Sánchez
G
Peñuelas
J
(
2011
)
Widespread crown condition decline, food web disruption, and amplified tree mortality with increased climate change-type drought
.
Proc Natl Acad Sci USA
 
108
:
1474
1478
.
Centritto
M
Magnani
F
Lee
HSJ
Jarvis
PG
(
1999
)
Interactive effects of elevated [CO2] and drought on cherry (Prunus avium) seedlings II
.
Photosynthetic capacity and water relations
 .
New Phytol
 
141
:
141
153
.
Close
DC
Davidson
NJ
(
2004
)
Review of rural tree decline in a changing Australian climate
.
Tasforests
 
15
:
1
18
.
Galiano
L
Martínez-Vilalta
J
Lloret
F
(
2011
)
Carbon reserves and canopy defoliation determine the recovery of Scots pine 4 yr after a drought episode
.
New Phytol
 
190
:
750
759
.
Hölttä
T
Mencuccini
M
Nikinmaa
E
(
2009
)
Linking phloem function to structure: analysis with a coupled xylem–phloem transport model
.
J Theor Biol
 
259
:
325
337
.
Hsiao
TC
Acevedo
E
Fereres
E
Henderson
DW
(
1976
)
Water stress, growth, and osmotic adjustment
.
Philos Trans R Soc London B Biol Sci
 
273
:
479
500
.
Intergovernmental Panel on Climate Change
(
2007
)
Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
.
Parry
ML
Canziani
OF
Palutikof
JP
van der Linden
PJ
Hanson
CE
(eds).
Cambridge University Press
,
Cambridge, UK
.
Jacquet
J-S
Bosc
A
O'Grady
AP
Jactel
H
(
2013
)
Pine growth response to processionary moth defoliation across a 40 year age chrono­sequence
.
For Ecol Manage
 
293
:
29
38
.
Jactel
H
Petit
J
Desprez-Loustau
M-L
Delzon
S
Piou
D
Battisti
A
Koricheva
J
(
2012
)
Drought effects on damage by forest insects and pathogens: a meta-analysis
.
Glob Chang Biol
 
18
:
267
276
.
Kurz
WA
Dymond
CC
Stinson
G
Rampley
GJ
Neilson
ET
Carroll
AL
Ebata
T
Safranyik
L
(
2008
)
Mountain pine beetle and forest carbon feedback to climate change
.
Nature
 
452
:
987
990
.
Loehle
C
LeBlanc
D
(
1996
)
Model-based assessments of climate change effects on forests: a critical review
.
Ecol Model
 
90
:
1
31
.
Manion
PD
(
1981
)
Tree disease concepts
.
Prentice-Hall
,
Englewood Cliffs, NJ
.
Martínez-Vilalta
J
Piñol
J
(
2002
)
Drought-induced mortality and hydraulic architecture in pine populations of the NE Iberian Peninsula
.
For Ecol Manag
 
161
:
247
256
.
Mattson
WJ
Haack
RA
(
1987
)
The role of drought in outbreaks of plant-eating insects
.
Bioscience
 
37
:
110
118
.
Matusick
G
(
2012
)
Drought and heat triggers sudden and severe dieback in a dominant Mediterranean-type woodland species
.
Open J For
 
02
:
183
186
.
McDowell
N
Pockman
WT
Allen
CD
et al
(
2008
)
Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought?
New Phytol
 
178
:
719
739
.
Metcalf
CJE
McMahon
SM
Clark
JS
(
2009
)
Overcoming data sparseness and parametric constraints in modeling of tree ­mortality: a new nonparametric Bayesian model
.
Can J For Res
 
39
:
1677
1687
.
Mitchell
PJ
O'Grady
AP
Tissue
DT
White
DA
Ottenschlaeger
ML
Pinkard
EA
(
2013
)
Drought response strategies define the relative contributions of hydraulic dysfunction and carbohydrate depletion during tree mortality
.
New Phytol
 
197
:
862
872
.
Murray
TJ
Tissue
DT
Ellsworth
DS
Riegler
M
(
2012
)
Interactive effects of pre-industrial, current and future [CO(2)] and ­temperature on an insect herbivore of Eucalyptus
.
Oecologia
 
171
:
1025
1035
.
Niinemets
Ü
(
2010
)
Responses of forest trees to single and multiple environmental stresses from seedlings to mature plants: past stress history, stress interactions, tolerance and acclimation
.
For Ecol Manage
 
260
:
1623
1639
.
Ogle
K
Barber
J
(
2008
)
Bayesian data—model integration in plant physiological and ecosystem ecology
. In:
Lüttge
U
Beyschlag
W
Murata
J
(eds)
Progress in botany
 .
Springer
,
Berlin
, pp
281
311
.
Ogle
K
Whitham
TG
Cobb
NS
(
2000
)
Tree-ring variation in pinyon predicts likelihood of death following severe drought
.
Ecology
 
81
:
3237
3243
.
Pinkard
EA
Eyles
A
O'Grady
AP
(
2011
)
Are gas exchange responses to resource limitation and defoliation linked to source:sink relationships?
Plant Cell Environ
 
34
:
1652
1665
.
Raffa
KF
Aukema
BH
Bentz
BJ
Carroll
AL
Hicke
JA
Turner
MG
Romme
WH
(
2008
)
Cross-scale drivers of natural disturbances prone to anthropogenic amplification: the dynamics of bark beetle eruptions
.
BioScience
 
58
:
501
.
Zvereva
EL
Kozlov
MV
(
2006
)
Consequences of simultaneous elevation of carbon dioxide and temperature for plant–herbivore interactions: a metaanalysis
.
Glob Chang Biol
 
12
:
27
41
.