\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Combined drought and bark beetle attacks deplete non-structural
carbohydrates and promote death of mature pine trees}



\author[1]{Nadir Erbilgin}%
\author[1]{Leila Zanganeh}%
\author[2]{Jennifer  Klutsch}%
\author[1]{Shih-hsuan Chen}%
\author[1]{Shiyang ZHAO}%
\author[1]{Guncha Ishangulyyeva}%
\author[3]{Stephen Burr}%
\author[4]{Monica Gaylord}%
\author[5]{Richard Hofstetter}%
\author[6]{Ken Keefover-Ring}%
\author[6]{Kenneth F. Raffa}%
\author[2]{Thomas Kolb}%
\affil[1]{University of Alberta}%
\affil[2]{Affiliation not available}%
\affil[3]{USDA Forest Service Alaska Region}%
\affil[4]{USDA Forest Service Flagstaff Forestry Sciences Laboratory}%
\affil[5]{Northern Arizona University}%
\affil[6]{University of Wisconsin Madison}%


\vspace{-1em}



  
  \date{May 22, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
How carbohydrate reserves change in conifers during drought and bark
beetle attacks are poorly understood. We investigated changes in
carbohydrate reserves and carbon-dependent terpene defenses in ponderosa
pine trees experimentally subjected to two levels of drought stress (via
root trenching) and two types of biotic challenge treatments
(pheromone-induced bark beetle attacks or inoculations with crushed
beetles that include beetle-associated fungi) for two consecutive years.
Our results showed that trenching did not influence carbohydrates
whereas both biotic challenges reduced amounts of starch and sugars of
trees. However, only the trenched-beetle attacked trees depleted
carbohydrates and died within the first year of bark beetle attacks.
While live trees contained higher carbohydrates than dying trees,
amounts of constitutive and induced terpenes produced did not vary
between live and beetle-attacked dying trees, respectively. Based on
these results we propose that reallocation of carbohydrates to terpenes
during the early stages of beetle attacks is limited in drought-stricken
trees, and that the combination of biotic and abiotic stress leads to
tree death. The process tree death is subsequently aggravated by beetle
girdling of phloem, occlusion of vascular tissue by bark beetle-vectored
fungi, and potential exploitation of host carbohydrates by beetle
symbionts as nutrients.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Climate change-induced dieback is a global problem affecting forest
ecosystems worldwide (Allen \emph{et al.} 2010; Anderegg \emph{et
al.}2012; Young \emph{et al.} 2017; Hartmann \emph{et al.} 2018). The
causal factors underlying forest dieback have been commonly attributed
to complex interactions between abiotic and biotic factors
(Simler-Williamson \emph{et al.} 2019). For instance, drought is often
viewed as a predisposing factor responsible for promoting outbreaks by
some insect species such as bark beetles (Coleoptera: Curculionidae,
Scolytinae) that attack the main stems of mature trees (Gaylord \emph{et
al.} 2013; Anderegg \emph{et al.} 2015; Netherer \emph{et al.} 2019;
Gely \emph{et al.} 2020; \selectlanguage{ngerman}Öhrn \emph{et al} . 2021). Although there are
proposed mechanisms underlying drought-induced tree mortality, i.e., a
failure of the plant's water transport-hydraulic-system and carbon
starvation due to prolonged stomatal closure and reduced photosynthesis
(McDowell \emph{et al.} 2008; Anderegg \emph{et al.} 2012; Meir \emph{et
al.} 2015; Adams \emph{et al.} 2017; Choat \emph{et al.} 2018;
Hartmann\emph{et al.} 2018), we have less understanding of the combined
effects of drought and insect attacks in the field (Kolb \emph{et al.}
2016; Stephenson \emph{et al.} 2019; Huang \emph{et al.} 2020).
Significant challenges in conducting field experiments include
experimental control of both water stress and bark beetle attacks on the
mature trees, and measurement of the cascading physiological changes
through tree death (Kolb \emph{et al.} 2016; Choat \emph{et al.} 2018).

Most studies focusing on tree mortality were either conducted during or
after observed mortality (retrospectively) (e.g., Camarero \emph{et
al.}2015; Gaylord \emph{et al.} 2013; 2015; Kolb \emph{et al.} 2016;
Öhrn\emph{et al} . 2021). Moreover, those studies primarily examined the
role of a single stress agent such as drought or herbivory (e.g.,
Meddens\emph{et al.} 2014; Erbilgin \emph{et al.} 2017) although their
effects can be interacting. Likewise, some studies utilized seedlings
under controlled conditions to improve standardization (i.e., Turtola
\emph{et al.} 2003; Lusebrink \emph{et al.} 2011) but it is well
recognized that plant ontogeny strongly affects many responses and thus
results obtained with seedlings may not be applicable to mature trees
(Boege \& Marquis, 2005; Erbilgin \& Colgan, 2012; Moreira \emph{et al.}
2017). As such, experimental demonstrations of both predisposing and
biotic factors leading to\selectlanguage{english}?and measuring the physiological mechanisms
responsible for\selectlanguage{english}?tree mortality in the field are sparse (Kolb \emph{et
al.} 2016; Huang \emph{et al.} 2020). This knowledge gap hinders our
ability to accurately understand the mechanism of tree mortality from
multiple and sometimes synergistic factors.

Drought can have profound impacts on tree responses to subsequent insect
attacks. These responses vary by feeding guild and are most impactful
with bark and wood boring insects (reviewed by Kolb \emph{et al.} 2016).
Briefly, prolonged droughts induce stomatal closure, which in turn
reduces photosynthesis, potentially leading to depletion of carbohydrate
reserves, i.e., non-structural carbohydrates (NSCs), comprised of
soluble sugars and starch (McDowell \emph{et al.} 2008; Anderegg\emph{et
al.} 2012; Mitchell \emph{et al.} 2013; Choat \emph{et al.}2018).
Hydraulic failure occurs due to disruption of water movement in the
xylem due to formation of air bubbles (embolism) during desiccation
(Adams \emph{et al.} 2017). Furthermore, NSC depletion may also reduce
water movement and retention, promoting cellular dehydration
(Sala\emph{et al.} 2012; Deans \emph{et al.} 2020). Reductions in
carbohydrate production and depletion of NSCs due to drought can
influence many functions in plants including biosynthesis of
carbon-dependent terpenes that serve antidessication and antiherbivory
functions (McDowell \emph{et al.} 2011; Huang \emph{et al.} 2020;
Hussain \emph{et al.} 2020).

Ponderosa pine (\emph{Pinus ponderosa} ) is one of the most widely
distributed conifer species in western North America, ranging from
southern Canada to Mexico, and from the Plains States to the Pacific
Coast. Two major threats to ponderosa pines, and other co-occurring pine
species, are drought and bark beetles (Negron \emph{et al.} 2009;
Bentz\emph{et al.} 2010; Raffa \emph{et al.} 2013; Creeden \emph{et
al.}2014). Over recent decades, several million ponderosa pine trees
were killed by a combination of these two stressors in various parts of
the species' range (Savage \emph{et al.} 1994; USDA Forest Service 2002;
Breshears \emph{et al.} 2005; Allen \emph{et al.} 2010; Pile \emph{et
al.} 2019).

Bark beetles' reproduction involves offspring completing their
development within the phloem layer beneath the outer bark of their host
trees. Pine phloem contains toxic carbon-dependent secondary metabolites
including monoterpenes, diterpene resin acids, and phenolics
(Francheshi\emph{et al.} 2005; Keeling \& Bohlmann 2006; Celedon \&
Bohlmann 2019; Erbilgin, 2019). Studies have reported that monoterpenes
and diterpenes are toxic to the bark beetles and their mutualistic fungi
(Kopper\emph{et al.} 2005; Chiu \emph{et al.} 2017; Ullah \emph{et al.}
2021). Numerous studies with simulated or actual herbivore attacks have
extensively shown mobilization and transport of stored NSCs in support
of the synthesis of defense metabolites in plants including conifers
(Goodsman \emph{et al} . 2013; Dietze \emph{et al.} 2014; Hartmann \&
Trumbore 2016; Adams \emph{et al} . 2017; Li \emph{et al} . 2018;
Roth\emph{et al} . 2018; Hussain \emph{et al} . 2020). Effects of
drought on bark beetles can be positive or negative depending on drought
intensity and duration (Lombardero \emph{et al.} 2000; Gaylord \emph{et
al.} 2013, 2015). Currently, we lack a clear understanding about the
importance of combined drought and bark beetle attacks on NSCs,
carbon-based defense metabolites, and their interactions in tree
mortality (Kolb \emph{et al.} 2016; Huang \emph{et al.} 2020).

An earlier study suggested a relationship between drought and ponderosa
pine terpene defenses (Kolb \emph{et al.} 2019), but how drought and
biotic challenges interact to influence NSCs and their relationships
with carbon-dependent defense metabolites (terpenes) has not been
jointly investigated and remains poorly understood. Thus, our primary
objective was to characterize the changes in NSC and terpene
concentrations in ponderosa pine trees that were experimentally exposed
to a factorial combination of drought stress (induced \emph{via} root
trenching), pheromone-induced bark beetle attacks, and crushing beetles
onto phloem/xylem interface in the experiment described in Kolb \emph{et
al} . (2019). We hypothesized that the combination of drought and bark
beetle attacks more rapidly deplete NSCs in tree stems that either
stress agent alone, thereby eliciting tree mortality. We addressed the
following five research questions: (1) Do drought stress, bark beetle
attacks, and the beetle crushing influence NSCs of ponderosa pine trees?
(2) Does drought impact the effect of biotic stressors on NSCs and
terpenes? (3) Do changes in NSCs result in changes in defense
metabolites? (4) Do concentrations of NSCs and defense metabolites vary
between live and dying ponderosa pine trees? (5) Can interactions
between NSCs and defense metabolites in dying ponderosa pine trees
explain their mortality?

\textbf{Materials and Methods}

Experimental approach

The study was conducted in a naturally regenerated ponderosa
pine-dominated stand at the Northern Arizona University's Centennial
Forest (35deg 11\selectlanguage{english}' 9.65'' N, 111deg 45\selectlanguage{english}' 38.25'' W; elevation 2,250 m). We
administered two levels of drought stress and two types of biological
challenge treatments. Drought stress was administered by cutting tree
roots beneath the drip line (hereafter trenched or untrenched). The
biological treatments were (1) bark beetle attacks (hereafter attacked),
(2) crushing beetles, including their microbial associates, onto the
phloem/xylem interface (hereafter inoculated), and (3) controls which
had neither bark beetle attacks nor inoculations.

The experiment was a randomized complete block with eight spatial blocks
within the stand. In each of the eight 1,300 m\textsuperscript{2}blocks,
six trees were randomly assigned to one of the following six treatments
(n=8 per treatment across eight blocks): (1) trenched-control, (2)
trenched-inoculated, (3) trenched-attacked, (4) untrenched-control, (5)
untrenched-inoculated, and (6) untrenched-attacked. The trees were
approximately 60 years of old, with a mean height of 8.0+-0.12 m (range
5.2-11.5 m) and a mean diameter at breast height of 24.2+-0.5 cm (range
20.0-31.9 cm). Neither height nor diameter of trees varied among
treatments (height: P=0.464; diameter: P=0.133).

Detailed descriptions of field experimental methods were provided in
Kolb \emph{et al.} (2019) which reported results for resin flow,
monoterpenes and sesquiterpenes in the phloem, xylem water potential,
and leaf gas exchange. In the current study, we focused on monthly
analyses of NSCs and diterpenes of xylem and thus only reported methods
relevant to these analyses. We also used the total monoterpene data from
Kolb \emph{et al} . (2019) in our analysis.

Drought treatments

We cut trenches beneath the drip line of 24 trees (n=3 per block) on May
20-21, 2013 using methods modified from Devine \& Harrington (2008).
Trenches were cut to 33 cm deep using a ditch witch and the interior
walls were lined with 0.15 mm thick polyethylene sheeting to restrict
root growth and water access. Each trench was then backfilled with soil.
We also removed snow within the same drip lines of trenched trees after
every major snowfall during the winter of 2013. As described in
Kolb\emph{et al} . (2019), the study measured tree predawn water
potential and the trenching treatment produced a level of water stress
consistent with moderate drought, similar to previous uses of this
method with ponderosa pine (McCullough \& Wagner, 1987). We briefly
summarized the results from Kolb \emph{et al} . (2019) under Result
section below.

Biological challenge treatments

We administered two biological challenge treatments and one control
treatment. The first treatment involved attaching bark beetle pheromones
(\emph{Dendroctonus brevicomis} lures; Synergy Semiochemicals Corp.
Burnaby, BC CAN) on selected trees at 1.5 m height on June 2, 2014 (app.
one year after trenching). We baited 16 trees, with one tree in each of
the trenched and untrenched treatments across eight blocks. We monitored
baited trees twice weekly and considered trees with pitch tubes (small
bark beetle boring holes filled with boring dust, frass, and resin) as
attacked. We counted all beetle attacks on each tree up to 3.5 m height.
Once the number of attacks on a tree reached 150, we removed baits from
that tree. Overall, the mean number of attacks per baited tree was 90+-9
m\textsuperscript{2} and did not vary between trenched and untrenched
trees (P=0.161).

The second treatment consisted of crushing beetles, in a 3:1 ratio
of\emph{D. brevicomis} to \emph{D. frontalis} , onto the phloem/xylem
interface to inoculate trees with the full complement of microbial
biota, primarily fungi but also including bacteria, mites, and nematodes
(Hofstetter \emph{et al.} 2015), associated with \emph{D. brevicomis}
,\emph{D. frontalis} , and \emph{D. valens} , the most dominant bark
beetle species affecting pine forests of the study region (Gaylord
\emph{et al.} 2006). We captured beetles in traps baited with \emph{D.
brevicomis} lure near the study site and stored beetles at -10degC until
use. We inoculated selected trees by chorusing recently captured bark
beetles into the phloem/xylem interface. Locations and densities of
inoculations mimic the location and number of attacks on a paired tree
in the attacked category within the same stress treatment and block. To
inoculate trees, we removed a plug of bark (4 mm dia.) and inserted one
beetle into the resulting cavity and crushed the beetle into the
phloem/xylem interface by replacing the bark plug. We conducted all
inoculations on the same day that attacks occurred on the attacked trees
within the same block (e.g., twice weekly). We inoculated a total of 16
trees, with one tree in each of the trenched and untrenched treatments,
across eight blocks from June 4 to August 5, 2014.

The control treatment had no manipulations. Furthermore, we took steps
to prevent bark beetle attacks on trees in the non-attacked treatments
(control, inoculated) by spraying the entire bole with 2.0\% carbaryl on
May 17, 2014 (DeGomez \emph{et al.} 2006). The carbaryl spray was
effective as we only observed a total of six attacks in 32 trees, and
these were unsuccessful (lack of pitch tubes, boring dust, and frass).
Every two weeks during the warm months (May to August) in 2014 and 2015,
we determined tree status as dead or alive; a tree was categorized as
dead when over 90\% of its canopy turned brown or red.

Tree defense measurements

We took several types of measurements to characterize defenses of all 48
trees periodically as described in Kolb \emph{et al.} (2019). We
collected phloem from each tree at 1.5 m height to determine composition
and concentrations of mono- and sesquiterpenes. We sampled phloem once a
month from May to October 2014 and from May to September 2015. All trees
were sampled on the same day by taking two phloem samples (1.25 cm dia.)
from opposite sides of the tree. Samples were kept in -20 degC until
analysis. Detailed descriptions of extraction and chemical analysis were
reported in Kolb \emph{et al.} (2019).

Non-structural carbohydrate and diterpene resin analyses of xylem

We collected increment cores (5 mm dia.) from all trees throughout the
experiment. Two cores were taken from opposite sides of each tree once a
month from July to November, 2014 and from May to September, 2015 (n=20
cores per tree). We used these cores to determine concentrations of NSCs
and diterpene resin acids in the xylem over time. At each sampling date
we selected the most current two consecutive rings from each of the two
cores as the single year core did not provide enough tissue to conduct
both NSC and diterpene analyses. For instance, in July 2014, we pooled
the complete growth ring from 2013 and the partial (until July) ring
from 2014. We freeze-dried these cores for six days (Labconco Corp.,
Kansas City, MO, USA) and ground them with a grinder (Tissue Lyzer II,
QIAGEN, GER) for 20-30 seconds at a frequency of 30
sec\textsuperscript{-1}. Ground samples were then separated into two
groups: One group was for NSC analysis (12-14 mg) and the other was for
diterpene analysis (25-27 mg).

Non-structural carbohydrate analysis

We adapted methods from Mullin \emph{et al} . (2021) for sugar and
starch analyses. Briefly, ground samples were extracted with 1.6 mL
ultra-pure water in a 2 mL glass tube. We placed tubes in a rack and
enclosed the rack in steam above a tray of boiling water for 60 min and
then closed the tube with its cap, and vortexed them for 30 sec. The
resulting extract was separated into two 0.5 mL aliquots for soluble
sugars and starch and stored at +4 degC.

For soluble sugars (glucose, fructose, sucrose), tubes containing a 0.5
mL aliquot were centrifuged at 18,213 rcf for 15 min and the resulting
supernatant was transferred into new 2 mL tubes containing 1.0 ml of
methanol and vortexed for 30 sec. Samples were incubated at room
temperature for 90 min and centrifuged at 18,213 rcf for 10 min.
Afterwards, 0.5 ml of extracts were transferred to 2 ml glass vials and
stored at \selectlanguage{english}-40 degC. Sugars were analyzed using an Ultra High-Performance
Liquid Chromatography (UHPLC, 1290 Infinity Agilent Tech., Santa Clara,
CA, USA) fitted with an InfinityLab Poroshell 120 HILIC-Z column (2.1 x
100 mm 2.7\selectlanguage{greek}µ\selectlanguage{english}m, Agilent Tech.) and an Evaporative Light Scattering
Detector (ELSD, 1290 ELSD II, Agilent Tech.). A gradient analysis was
performed using a binary solvent system of ultra-pure water with 0.02\%
v/v ammonium hydroxide (channel A) and acetonitrile (HPLC-grade) with
0.02\% v/v ammonium hydroxide (channel B) flowing at 0.2 ml
min\textsuperscript{-1}. We calculated quadratic standard curves from
three dilutions prepared from analytical standards to quantify glucose
(Chemical Purity: 99\%), fructose (CP: 99\%), and sucrose (CP: 99.5\%).
Soluble sugars were identified based on the retention time of the
analytical standards. Concentrations of soluble sugars were reported as
\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of dry weight.

Starch extraction was conducted using the second aliquot (0.5 mL) of
sample extract. We used a series of enzymatic digestions to convert
starch into gluconate-6-phosphate as adapted from Lahr \& Sala (2014)
and Cale \emph{et al.} (2019a). Extractions began with the steam bath
procedure described above. Following the steam bath, samples were
vortexed for 30 sec, then a 0.5 ml aliquot that included suspended
solids was transferred to a new 2 mL tube containing 0.5 mL of \selectlanguage{greek}α-\selectlanguage{english}amylase
solution (0.75 mg enzyme mL\textsuperscript{-1}; Sigma-Aldrich) to
convert starch to maltose and similar polysaccharides. The tubes were
immediately vortexed for 30 sec, incubated in a water bath at 50\selectlanguage{ngerman}° C for
16 hm and then centrifuged (18,213 rcf) for 20 min. The resulting 0.5 mL
of the supernatant was transferred into a new 2 mL tube containing with
0.5mL of amyloglucosidase solution 2.5 g enzyme (Sigma-Aldrich) in 50 mL
sodium acetate buffer (0.1 M, pH 4.5). The tubes were incubated in a 50
°C bath for 16 h to convert maltose and similar polysaccharides to
glucose and fructose and then centrifuged (18,213 rcf) for 15 min. We
transferred 0.02 mL of the final glucose extracts to 2 mL glass vials
with starch derived glucose, which were immediately quantified by
spectrophotometric analysis using the Synergy Microplate Reader H1
(BioTek, Winooski, VT, USA) at an absorbance of 340 nm. Using methods
reported in Mullin \emph{et al} . (2021), we quantified the
concentration of starch using two calibration curves. The first curve
estimated glucose concentrations from the sample absorbance at 340 nm,
and the second estimated starch concentration from glucose
concentration.

Diterpene resin acid extraction and analysis

Diterpenes were extracted from lyophilized ground tissue in 1 ml of
methanol, as adapted from Mullin \emph{et al} . (2021). Samples were
vortexed for 30 sec, then sonicated for 10 min, and left for 24 h in the
dark at room temperature, and then vortexed for 30 sec and centrifuged
(18,213 rcf) for 15 min. Extracts were transferred into 2 mL glass vials
and stored at \selectlanguage{english}-40 degC. Diterpenes were analyzed in an UHPLC, fitted with
a reverse-phase InfinityLab Poroshell 120 EC-C18 column (2.1 x 150 mm
1.9\selectlanguage{greek}µ\selectlanguage{english}m, Agilent Tech.) and a diode array detector (UV/Vis, 1290 DAD,
Agilent Tech.). We performed a gradient analysis with a binary solvent
system, a 1.7\% v/v glacial acetic acid in distilled deionized water
(channel A) and 100\% pure methanol (channel B) flowing at 0.3 mL
min\textsuperscript{-1} for 17 min with solvent gradients. A 5 \selectlanguage{greek}µ\selectlanguage{english}l
injection volume was used. The system began at 75\% B for 1 min, then
increasing to 85\% B over 9 min, held for 2 min, then decreased to 75\%
B over 14-17 min, and held for 3 min.

Diterpenes were quantified using analyte absorbance at wavelengths of
240, 268, and 282 nm (Kersten \emph{et al.} 2006) and applying standard
curves. The curves were generated from dilutions prepared from
analytical standards of dehydroabietic acid (CP: \textgreater{}99\%),
sandaracopiramic acid (CP: \textgreater{}90\%), levopiramic acid (CP:
\textgreater{}95\%), neoabietic acid (CP: \textgreater{}99\%), palustric
acid (CP: \textgreater{}92\%), and abietic acid (CP:
\textgreater{}75\%). All chemicals were obtained from CanSynth Chem.
Corporation (Toronto, ON, CAN), except for abietic acid from Sigma
Aldrich. Diterpene concentrations were reported as \selectlanguage{greek}µ\selectlanguage{english}g
mg\textsuperscript{-1} of dried weight.

Data analysis

Since data showed large year-to-year variation, we analyzed each year
separately (PerManova: F\textsubscript{(1.313)}=4.45, P=0.009). We first
tested the dispersion of chemical profiles of all trees between sampling
years (2014, 2015), and then between months within a year using NMDS
ordination with Bray-Curtis distance (\emph{metaMDS} function,
package\emph{vegan} v2.5-6). We used PERMANOVA to verify whether
chemical profiles changed over time with block set as strata
(\emph{adonis2}function, \emph{vegan} package v2.5-6 in R v4.0.3). An
overview of our approach for each question is detailed below. Due to
multiple permutations within our analyses, we summarized which
treatments were compared to evaluate each research question in Table 1.

\emph{1. Do treatments influence NSCs of ponderosa pines?} Since
increment cores were collected from the same trees over multiple times,
we used repeated measures analysis. We first checked the assumption of
sphericity using Mauchly's test by testing whether starch, total sugars,
and total NSCs change with month as a function of treatment
(\emph{anova\_test} function, package \emph{rstatix} v0.6.0). Results
showed the data met sphericity assumptions and the correlation structure
was avoided in final models. Therefore, linear mixed models were used to
test the interaction between treatments and months with blocks and trees
as nested random effects to identify whether treatments affected NSCs
(function \emph{lmer} , package \emph{lme4} v1.1-23). Residuals of NSC
analyses were normally distributed and had homogeneous variances. We
reported Type III tests using Satterthwaite's method and pairwise
comparison p-values are Tukey adjusted (package \emph{emmeans} v1.5.3).

\emph{Does trenching affect NSCs?}We compared starch, total sugars and
total NSCs between trenched-control (n=8) and untrenched-control (n=8)
trees using the same analysis as above.

\emph{Do bark beetle attacks affect NSCs?} We compared starch, total
sugars and total NSCs between untrenched-attacked (n=8) and
untrenched-control (n=8) trees using the same analysis as above.

\emph{Do microbial inoculations affect NSCs?} We compared starch, total
sugars and total NSCs between untrenched-inoculated (n=8) and
untrenched-control (n=8) trees using the same analysis as above.

\emph{2. Is drought-biotic stressor interaction significant for NSCs and
defense metabolites?} In this and the research questions 3-5 below, we
only focused on the phloem monoterpenes as there is currently no
evidence that sesquiterpenes affect bark beetle biology.

We tested whether trenching impacted the effect of biotic stress (either
bark beetle attacks or inoculation) on NSCs and terpenes. For each
carbohydrate and defense compound, we ran separate models for bark
beetle attack vs. control and inoculation vs. control treatments. Each
repeated measures model included a full 3-way interaction with month,
trenching and either beetle attack or inoculation treatment. Defense
concentrations were log-transformed to meet assumptions of normality and
homogeneity of variance but least squared means in original scale are
presented.

\emph{3. Do changes in NSCs result in changes in defense
metabolites?}Using the same statistical approach as in the first
question above, we tested whether the interaction of the NSCs, month and
treatments affected concentrations of the total diterpenes or total
monoterpenes with a repeated measures ANCOVA. Both monoterpenes and
diterpenes were natural log-transformed to meet normality and
homogeneity of variance assumptions. We removed the 3-way interaction
from the final analysis because it was not significant and instead used
a simpler model with fixed effects of NSCs, treatment, month, treatment
by NSCs, and treatment by month with the same repeated measures model
structure as above. Where there were significant interactions between
treatment and NSCs, we tested whether slopes were different using
Tukey's adjusted p-value (function \emph{lstrends} in package
\emph{lsmeans} v2.27-2).

\emph{4. Do concentrations of NSCs and terpenes vary between dying and
live trees?} We used the same type of analyses as described under the
first question above but only used the data from 2014 since six out of
eight trees attacked by bark beetles died that year. We compared six
dying trees with the two live trees in the trenched-attacked treatment
for concentrations of starch, total sugars, total NSCs, total
diterpenes, and total monoterpenes. We conducted overall pairwise
comparisons between treatments with Tukey's adjusted p-values and then
separately for each month with Sidak adjusted p-values
(\emph{emmeans}v1.5.3).

\emph{5. Can interactions between NSCs and terpenes explain tree
mortality?} We tested the correlation between average NSCs (starch,
total sugars, or total NSCs) and terpenes (total diterpenes or
monoterpenes) for the six dying trees in the trenched-attacked treatment
in a Pearson correlation analysis. We also conducted the same
correlation tests for live trees in the remaining six treatments
including those that survived in the trenched-attacked treatment. We
only used data from 2014 as all six dying trees in the trenched-attacked
treatment died in 2014.

\textbf{Results}

Overall, eight of the 48 total trees died during the two-year
experiment. Bark beetle attacks occurred over 10 weeks, starting early
June and ending in middle of August. Attacks peaked in late June and
declined through August. All eight of the dead trees were attacked by
bark beetles, with six of them being in the trenched-attacked treatment
and two in the untrenched-attacked treatment. Trees in the combined
treatment died sooner, with all of the mortality to trenched-attacked
trees occurring in 2014 and all of the mortality to untrenched-attacked
trees occurring in 2015.

As reported by Kolb \emph{et al} . (2019), predawn water potential over
the summer of 2013 averaged -0.97 MPa for trenched trees and -0.83 MPa
for untrenched trees. In the second year of the experiment (2014),
predawn water potential was approximately 0.5 MPa more negative for
trenched trees than untrenched trees between late May and early July
during the typical spring drought period of the region (Fig. 1 in
Kolb\emph{et al} . 2019). Predawn water potential of trees in the
trenched-attacked trees became much more negative than trees in all
other treatments for the remainder of summer in 2014, reaching an
average value of -2.5 MPa by middle of September compared with -0.5 MPa
in other treatments. Differences in light saturated net photosynthetic
rate among treatments in 2014 paralleled differences in predawn water
potential, with values of trenched trees 14\% lower than untrenched
trees in May (mean of 6.1 and 5.3 umol
m\textsuperscript{-2}s\textsuperscript{-1}, respectively) and 90\% lower
in late June (mean of 0.4 and 0.04 umolm\textsuperscript{-2}
s\textsuperscript{-1}, respectively). Trenching continued to cause water
stress during dry periods in the third year of the experiment (2015),
with values of trenched trees 0.2 MPa more negative than untrenched
trees in late June.

In general, chemical profiles of ponderosa pine trees changed with
treatment (Fig. 1, Fig. S1, Tables S1 \& S2), year (PerManova:
F\textsubscript{(1.313)}=4.45, P=0.009) and month (PerManova:
F\textsubscript{(8.313)}=7.11, P\textless{}0.001). Therefore, we tested
whether the NCSs differed among treatments for each month and each year.
The results showed that with the exception of September 2015, chemical
profiles varied among treatments in the remaining sampling times (Fig.
1, Figs. S1 \& S2, Table S3). Note that terpenes of trees challenged
with either bark beetle attacks or inoculated with crushed beetles
represent ``induced'' concentrations, whereas terpenes of trees without
any biological challenge treatments represent ``constitutive''
concentrations. Thus, the results should not be applied to define the
question of whether terpene concentrations predict which trees live or
die.

\emph{Do treatments influence NSCs} \emph{of ponderosa pine
trees?}Overall, results show the importance of cumulative stresses in
tree NSCs reduction in the xylem and mortality during drought as the
effects of trenching on NSCs were negligible in trees without any
additional biological treatment especially in the trenched-attacked
treatment (Fig. 1, Table S2, Fig. S1). For instance, bark beetle attacks
with trenching significantly lowered the total NSCs of trees relative to
the trenching without such attacks (Fig. 1).

\emph{Effects of trenching on NSCs.} Overall, chemical profiles did not
differ between trenched-control and untrenched-control trees (Fig 2a,
Table S4). We further tested if the NSCs were affected by trenching in
each month. The difference was only significant in October 2014 (Fig. 3,
Table S5) when starch, total sugars and total NSCs were higher in the
trenched-control than the untrenched control.

\emph{Effects of bark beetle attacks on NSCs.} For sugars, starch and
total NSCs, treatments and month were significant, but treatment-month
interaction was only significant for starch (Fig. 2b, Table S4). We then
tested if NSCs were a function of beetle attacks in each month and found
that bark beetle attacks significantly lowered sugars, starch, and total
NSCs in July, August, September, October, November in 2014 and in May,
June, August in 2015 (Fig. 3, Table S5).

\emph{Effects of crushed beetle inoculations on NSCs} . Although
treatment and month were significant for starch, total sugars, and total
NSCs, the interaction was not (Fig. 2c, Table S4). We then tested
whether NSCs were affected by inoculation in each month and found that
inoculation significantly reduced total sugars and total NSCs in July,
August, September, October in 2014 and in May, June, July, and August in
2015 and starch in July, August, and September in 2014 and in May, June,
July, and August in 2015 (Fig. 3, Table S5).

\emph{Trench-biotic stress interactions.} We did not find significant
interaction between trenching and biotic (beetle attacks or
inoculations) treatments for NSCs and diterpenes (p\textgreater{}0.05).
However, trenching did impact monoterpene concentrations in response to
inoculation (F\textsubscript{(1,,21)}=4.69, P=0.042).
Trenched-inoculated trees had significantly greater monoterpene
concentration (8.85\selectlanguage{ngerman}±1.89 \selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1}) than
trenched-control (2.80\selectlanguage{ngerman}±0.60 \selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1}) or
untrenched-control (3.82\selectlanguage{ngerman}±0.82 \selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1}) trees. Means of
trenched-inoculated and untrenched-inoculated (5.42\selectlanguage{ngerman}±1.16 \selectlanguage{greek}µ\selectlanguage{english}g
mg\textsuperscript{-1}) were statistically similar. Please note that
monoterpenes

\emph{NSCs and defense metabolite interactions. Relationship between
NSCs and diterpenes.} There was a significant negative relationship
between diterpenes and NSCs (Total NSCs: F (1,267)=36.22, P\textless{}
0.001, Fig. 4a; Total Sugars: F(1,270) =34.41, P\textless{}0.001, Fig.
4b; Starch: F (1,271) =25.49, P\textless{}0.001, Fig. 4c). However,
treatments did not affect these relationships (Fig. 4a).

\emph{Relationship between NSCs and monoterpenes} . We did not find any
relationship between monoterpenes and NSCs (Total NSCs: F(1,291)=0.082,
P=0.774, Fig. 4d; Total Sugars: F(1,293) =0.080, P=0.783, Fig. 4e;
Starch: F(1,265)=0.001, P=0.969, Fig. 4f). However, the relationship
between starch and monoterpenes varied by treatments (Fig. 4f). Trees in
the untrenched-attacked treatment had a significant negative
relationship between monoterpenes and starch; in contrast, we found a
significant positive relationship in the untrenched-inoculated and
trenched-inoculated trees (t=-4.54, P\textless{}0.001, and t=-3.75,
P=0.003, respectively). Moreover, although there was a marginal effect
of treatment on the relationship between total NSCs and monoterpenes, we
did not find a significant interaction for total sugars (significance of
interactions are provided in Fig. 4 caption).

\emph{Concentrations of NSCs and terpenes between dying and live trees
(2014 data only).} Treatment, month, and their interaction significantly
affected sugars, starch, or total NSCs (Suppl. Table S6). We then
compared the dying and live trees in the same trenched-attacked category
for each month and found that live trees had significantly higher total
sugars, starch, and total NSCs than dying trees in August, September,
October, and November in 2014 (Fig. 5).

We investigated similar relationships for diterpenes and monoterpenes of
dying and live trees in the same treatment category. Treatment, time and
their interaction were not significant effects for either terpenes
(Table S6), showing that the amount of diterpenes or monoterpenes
produced in the dying versus live trees were statistically similar (Fig.
5).

Comparisons of carbohydrates between the six dying trees in the
trenched-attacked treatment and live trees in the untrenched-control
treatment showed a significant effect of month (Table S7). In a pairwise
comparison between treatments for each month, we found that live trees
had significantly higher starch, total sugars, and total NSCs than dying
trees starting from July until November in 2014 (Fig. 6). We only used
the data in 2014 because all dying trees in the attacked-trenched
category died in 2014.

We investigated relationships between the six dying trees in the
trenched-attacked treatment and live trees in the untrenched-control
treatment for diterpenes and monoterpenes. Although the two treatments
did not vary significantly, the monthly comparisons showed that
constitutive tissue of live trees had significantly lower diterpenes in
August, September, October, and November than tissues of attacked trees
(Fig. 6, Table S7). Likewise, for monoterpenes, the overall interaction
was not significant but the monthly comparisons showed that live trees
had significantly lower monoterpenes in July, August, September, and
October than dying trees (Fig. 6).

\emph{Explanation of tree mortality by NSCs-terpene interactions.} We
investigated the relationship between NSCs and terpenes from 2014 for
dying trees in the trenched-attacked treatment and all treatments of
live trees averaged over months. We found significant negative
relationships of NSCs with either with diterpenes or monoterpenes (Fig.
7). For live trees, diterpenes or monoterpenes had a significant
negative relationship with starch, total sugars, or total NSCs. For
dying trees, only monoterpenes had a significant relationship with
starch (P \textless{} 0.05). Other relationships between carbohydrates
and terpenes were not significant. The low sample size for dying trees
may have impacted the lack of significance in correlations compared to
live trees.

\textbf{Discussion}

This is the first experimental demonstration of seasonal changes in both
carbohydrates and carbon-dependent defense metabolites through mortality
of any conifer species during drought and bark beetle attacks in the
field. Here, root trenching increased tree water stress which was
manifested in reductions in both xylem water potential and leaf gas
exchange, in agreement with previous studies with induced water stress
(McCullough \& Wagner 1987; Woodruff \& Meinzer 2011; Hartmann 2015;
Arango-Velez \emph{et al.} 2016). We showed that trenching did not
influence NSCs whereas both biotic challenge treatments reduced amounts
of starch and sugars of trees. Furthermore, live trees had higher NSCs
than dying trees, but the terpene concentrations did not vary between
them. Only the trenched-beetle attacked trees depleted carbohydrates and
died within the first year of bark beetle attacks.

We developed a new schematic representation of how mild drought alone or
in combination with biotic stress has influenced NSCs (Fig. 8). Overall,
our results show the importance of cumulative stress in tree
carbohydrate depletion and mortality during drought, especially when
considering that the effect of trenching alone on tree NSCs was
negligible prior to bark beetle attacks or microbial inoculations (Fig.
8, Box 1). In fact, six of eight trees in the trench-attacked treatment
died within 2-3 months of bark beetle attacks (2014) and at the time of
death they had less than 10\% of NSCs found in live trees. Since
increased water stress following trenching had no impact on tree NSC
amounts, our results suggest that trees stressed only by moderate
drought may recover by compensating for carbohydrate loss
(Gaylord\emph{et al.} 2015; Galiano \emph{et al.} 2017; Trugman \emph{et
al} . 2018; Gessler \emph{et al.} 2020; He \emph{et al.} 2020). However,
if such trees are further stressed by biotic agents, the cumulative
stressors (drought plus biotic agents) can lead to tree death (Fig. 8,
Boxes 2 \& 3) (Anderegg \emph{et al.} 2015; Camarero \emph{et al.} 2015;
Gaylord \emph{et al.} 2015).

When bark beetles successfully enter the host, they consume phloem
tissue to excavate oviposition and larval galleries, resulting in
girdling and thus disrupting carbon transport in the phloem within the
tree (Fig. 8, Box 3) (Paine \emph{et al.} 1997; Wiley \emph{et
al.}2016). Bark beetles also carry propagules of a diverse community of
fungal species (Frago \emph{et al} . 2012); some of them have been shown
to be at least moderately phytopathogenic (Krokene 2015). Once inside
the tree, fungal propagules germinate and fungal hyphae spread and
penetrate water conducting tissues in the xylem, blocking water
conduction from the soil to the canopy and thus reducing photosynthesis,
carbon assimilation, and NSC storage (Fig. 8, Box 2) (Lahr \& Krokene
2013; Arango-Velez \emph{et al.} 2016; Wiley \emph{et al.} 2016;
Adams\emph{et al.} 2017). Furthermore, hyphal growth and expansion
inside the tree can be a significant carbon sink as fungal growth
requires carbon (Fig. 8, Box 2) (Cale \emph{et al.} 2019b). This may
explain why both microbial inoculation and bark beetle attacks?without
trenching?led to roughly similar depletion levels of NSCs in trees.
However, inoculation of trenched trees did not result in any tree
mortality as the bark beetle attacks on the trenched trees did,
suggesting that the degree of stress imposed on trees appears to be
proportional to the presence of both bark beetles and associated
microbes. It is noteworthy for future assessments of tree defense
capacity that using crushed beetles as the inoculum source generates
higher variance to mean ratios of host chemistry than using standardized
fungal inoculum (e.g., Keefover-Ring\emph{et al} . 2016; Raffa \emph{et
al} . 2017). This result also suggests that single inoculation
treatments, while useful for simulating beetle entry to access tree
defensive capacity, cannot fully generate the effects of bark beetle
mass attacks on declining tree health and mortality.

The current study suggested two mechanisms to support our main
hypothesis, that continuous bark beetle attacks during tree water stress
can deplete NSCs in tree stems relative to the trenching or bark
beetle-alone treatments, and lead to tree mortality. Firstly, dying
trees had much lower NSCs than live trees. In addition to our above
explanation on the role of bark beetle-fungal activities in carbon
biosynthesis and transport, bark beetle attacks created stronger sinks
for carbohydrates than the trenching or inoculation alone treatments
(Fig. 8, Box 3). Consequently, the amounts of terpenes produced in dying
trees were similar to or higher than live trees (depending on the
comparison and sampling date). Particularly, while NSC amounts were
relatively stable in dying trees from July to November (2014), diterpene
amounts increased over time particularly from July to September. In
contrast, NSCs steadily increased in live trees but diterpenes sharply
declined. In fact, at the time of death (October-November 2014), the
dying trees had similar or higher concentrations of total diterpenes in
the xylem and total monoterpenes in the phloem than live trees in the
untrenched-control treatment despite having only 5.8\% of the total NSCs
present in the live trees. These results are expected as conifer trees
with low NSCs have been found to prioritize chemical defenses over
growth and respiration (Huang \emph{et al} . 2019). Our results suggest
that terpene production in dying trees acted as a carbon sink because of
the continuous allocation and remobilization of NSCs from storage to
terpene biosynthesis (Goodsman \emph{et al.} 2013; Roth \emph{et al} .
2018; Huang \emph{et al.} 2020). This likely reduced the NSC storage
pool in the tree and altered carbon allocation to other tree functions
(Sapes \emph{et al.} 2021) (Fig. 8, Box 3), potentially resulting in
carbon starvation in the tree stem (McDowell \emph{et al.} 2008;
McDowell \& Sevanto 2010).

Furthermore, lower NSC amounts within the trenched-attacked treatment
for dying trees compared to live trees further supports a role of
carbohydrates in tree survival (Fig. 8, Box 3). While six out of eight
trees in the trenched-attacked treatment died, the remaining two trees
were still alive at the end of the experiment. Although induced terpene
amounts did not vary between dying and live trees in the
trenched-attacked treatment, dying trees had considerably less sugars
and starch than live trees. Thus, the differences between dying and live
trees may be explained by the higher amounts of NSCs in the latter
(Galiano \emph{et al.} 2011; Poyatos \emph{et al.} 2013; Dietze \emph{et
al.} 2014; Camarero \emph{et al.} 2015). Similar to our results,
Wiley\emph{et al.} (2016) reported that phloem and xylem NSCs of
lodgepole pine (\emph{P. contorta} var. \emph{latifolia} ) trees were
affected by\emph{D. ponderosae} attacks, with attacked trees having
lower NSC amounts in both phloem and xylem than trees protected from
such attacks (\emph{via} experimental exclusion).

In conclusion, tree NSCs are critical for understanding the impacts of
drought and bark beetles on conifers because of the importance of
carbon-dependent terpenes as defenses against bark beetles. Using a
multi-year field experiment, we showed that bark beetle colonization on
drought-stressed trees reduced not only local carbohydrate availability
for essential tree functions, but also inhibited tree's ability to
replenish carbohydrate reserves. Furthermore, carbon-dependent terpenes
and spreading fungal biomass in tree tissues become sinks for NSCs.
Overall, this study enhances mechanistic understanding of how
drought-mediated bark beetle attacks kill trees and underscores the
importance of multiple stressors in altering tree carbohydrate
source-sink relationships.

\textbf{Acknowledgements --} This field work was supported by
McIntire-Stennis Program project accession no. 230732 from the USDA
National Institute of Food and Agriculture. John Kaplan, Ansley Roberts,
Teresa Reyes, and Patrick Dunn provided valuable help in the field; A
Roberts and T Reyes were supported by the Hooper Undergraduate Research
Program at Northern Arizona University and the National Science
Foundation Research Experience for Undergraduates Program, respectively.
The Northern Arizona University Centennial Forest provided the study
site. NSERC to NE supported all the work at the University of Alberta.
Non-structural carbohydrate and diterpene resin acid analyses were
conducted in Erbilgin lab
(https://sites.ualberta.ca/\textasciitilde{}erbilgin/).

\textbf{Authors Contribution --} SJB, MG, RH, and TK designed and
implemented the field experiment and collected phloem and increment core
samples; KK-R and KFR measured phloem monoterpenes; LZ, SZ, GI, S-HC
prepared increment cores and conducted chemical analysis; SZ, JGK, and
NE conducted statistical analyses; JGK, NE and S-HC prepared figures and
tables; NE wrote the entire manuscript; all authors contributed to
writing.

\textbf{Data Availability --} Upon acceptance of this manuscript, data
will be posted at the University of Alberta Dataverse
(https://dataverse.org/)

\textbf{References}

Adams HD, Zeppel MJB, Anderegg WRL, Hartmann H, Landsh\selectlanguage{ngerman}äusser SM, Tissue
DT. 2017. A multi-species synthesis of physiological mechanisms in
drought-induced tree mortality. \emph{Nature Ecology and
Evolution}\textbf{1,} 1285--1291.

Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier
M, Kitzberger \emph{et al.,} 2010. A global overview of drought and
heat-induced tree mortality reveals emerging climate change risks for
forests. \emph{Forest Ecology and Management} \textbf{259,} 660--684.

Anderegg WRL, Berry JA, Smith DD, Sperry JS, Anderegg LDL, Field CB.
2012. The roles of hydraulic and carbon stress in a widespread
climate-induced forest die-off. \emph{Proceedings of the National
Academy of Sciences} USA \textbf{109,} 233--237.

Anderegg WRL, Hicke JA, Fisher RS, Allen CD, Aukema J, Bentz B, Hood
S,\emph{et al.,} 2015. Tree mortality from drought, insects, and their
interactions in a changing climate. \emph{New Phytologist}
\textbf{208,}674--683.

Arango-Velez A, El-Kayal W, Copeland CCJ, Zaharia LI, Lusebrink I, Cooke
JEK. 2016. Differences in defense responses of \emph{Pinus contorta}
and\emph{Pinus banksiana} to the mountain pine beetle fungal
associate\emph{Grosmannia clavigera} are affected by water deficit.
\emph{Plant Cell Environment} \textbf{39,} 726-744.

Bentz BJ, Régnière J, Fettig CJ, Hansen EM, Hayes JL, Hicke JA, Kelsey
RG, \emph{et al.,} 2010. Climate change and bark beetles of the Western
United States and Canada: direct and indirect effects.
\emph{BioScience}\textbf{60,} 602--613.

Boege K, Marquis RJ. 2005. Facing herbivory as you group up: the
ontogeny of resistance in plants. \emph{Trends in Ecology \& Evolution}
.\textbf{20} , 441-448.

Breshears DD, Cobb NS, Rich PM, Price KP, Allen CD, Balice RG, Romme
WH,\emph{et al.,} 2005. Regional vegetation die-off in response to
global-change-type drought. \emph{Proceedings of the National Academy of
Sciences} \emph{USA} \textbf{102,} 15144--15148.

Cale AC, Klutsch GJ, Dykstra BC, Peters B, Erbilgin N. 2019a.
Pathophysiological responses of pine defensive metabolites largely lack
differences between pine species but vary with eliciting ophiostomatoid
fungal species. \emph{Tree Physiology} \textbf{39,} 1121--1135.

Cale JA, Ding R, Wang F, Rajabzadeh R, Erbilgin N. 2019b. Ophiostomatoid
fungi can emit the bark beetle pheromone verbenone and other
semiochemicals in media amended with various pine chemicals and
beetle-released compounds. \emph{Fungal Ecology} \textbf{39,} 285-295.

Camarero JJ, Gazol A, Sangüesa-Barreda G, Oliva J, Vicente-Serrano SM.
2015. To die or not to die: early warnings of tree dieback in response
to a severe drought. \emph{Journal of Ecology} \textbf{103,} 44--57.

Celedon JM, Bohlmann J. 2019. Oleoresin defenses in conifers: chemical
diversity, terpene synthases and limitations of oleoresin defense under
climate change. \emph{New Phytologist} \textbf{224,} 1444-1463.

Chiu CC, Keeling CI, Bohlmann J. 2017. Toxicity of pine monoterpenes to
mountain pine beetle. \emph{Scientific Reports} \textbf{7,} 8858.

Choat B, Brodribgb TJ, Broderse CR, Duursma RA, López R, Medlyn BE.
2018. Triggers of tree mortality under drought.
\emph{Nature}\textbf{558,} 531--539.

Creeden EP, Hicke JA, Buotte PC. 2014. Climate, weather, and recent
mountain pine beetle outbreaks in the western United States.\emph{Forest
Ecology and Management} \textbf{312,} 239-251.

DeGomez TE, Hayes CJ, Anhold JA,McMillin JD, ClancyKM, Bosu PP. 2006.
Evaluation of insecticides for protecting southwestern ponderosa pines
from attack by engraver beetles (Coleoptera: Curculionidae:
Scolytinae).\emph{Journal of Economic Entomology} \textbf{99,} 393-400.

Deans RM, Brodribb TJ, Busch FA, Farquhar GD. 2020. Optimization can
provide the fundamental link between leaf photosynthesis, gas exchange
and water relations. \emph{Nature Plants} \textbf{6,} 1116-1125

Devine WD, Harrington TB. 2008. Belowground competition influences
growth of natural regeneration in thinned Douglas-fir
stands.\emph{Canadian Journal of Forest Research} \textbf{38,}
3085--3097.

DiGuistini S, Wang Y, Liao NY, Taylor G, Tanguay P, Feau N, et al. 2011.
Genome and transcriptome analyses of the mountain pine beetle-fungal
symbiont Grosmannia clavigera, a lodgepole pine pathogen. Proceedings of
National Academy of Sciences, USA. \textbf{108} , 2504-2509.

Dietze MC, Sala A, Carbone MS, Czimczik CI, Mantooth JA, Richardson AD,
Vargas R. 2014. Nonstructural carbon in woody plans. \emph{Annual Review
of Plant Biology} \textbf{65,} 667-87.

Erbilgin N. 2019. Phytochemicals as mediators for host range expansion
of a native invasive forest insect herbivore. \emph{New
Phytologist}\textbf{221,} 1268--1278.

Erbilgin N, LJ Colgan. 2012. Differential effects of plant ontogeny and
damage type on phloem and foliage monoterpenes in jack pine (\emph{Pinus
banksiana} ). \emph{Tree Physiology} \textbf{32,} 946--957

Erbilgin N, Cale JA, Lusebrink I, Najar A, Klutsch JG, Sherwood P,
Bonello PE, Evenden ML. 2017. Water-deficit and fungal infection can
differentially affect the production of different classes of defense
compounds in two host pines of mountain pine beetle. \emph{Tree
Physiology} \textbf{37} , 338--350.

Frago E, Dicke M, Godfray HCJ. 2012. Insect symbionts as hidden players
in insect-plant interactions. \emph{Trends in Ecology and
Evolution}\textbf{27} , 705--711.

Galiano L, Martínez-Vilalta J, Lloret F. 2011\textbf{.} Carbon reserves
and canopy defoliation determine the recovery of Scots pine 4 yr after a
drought episode. \emph{New Phytologist} \textbf{190} , 750-759.

Galiano L, Timofeeva G Saurer M, Siegwolf R, Martínez-Vilalta J, Hommel
R, Gessler A. 2017. The fate of recently fixed carbon after drought
release: towards unravelling C storage regulation in \emph{Tilia
platyphyllos} and \emph{Pinus sylvestris} . \emph{Plant Cell
Environment}\textbf{40} , 1711-1724.

Gaylord ML, Kolb TE, Wallin KF, Wagner MR. 2006. Seasonality and lure
preference of bark beetles (Curculionidae: Scolytinae) and associates in
a northern Arizona ponderosa pine forest. \emph{Environmental
Entomology} \textbf{35} , 37-47.

Gaylord ML, Kolb TE, Pockman WT, Plaut JA, Yepez EA, Macalady AK, Pangle
RE, McDowell NG. 2013. Drought predisposes piñon-juniper woodlands to
insect attacks and mortality. \emph{New Phytologist} \textbf{198} ,
567--578.

Gaylord ML, Kolb TE, McDowell NG. 2015. Mechanisms of piñon pine
mortality after severe drought: a retrospective study of mature
trees.\emph{Tree Physiology} \textbf{35} , 806--816.

Gely C, Laurance SGW, Stork NE. 2020. How do herbivorous insects respond
to drought stress in trees? \emph{Biological Review} \textbf{95} ,
434--448.

Gessler A, Bottero A, Marshal J, Arend M. 2020. The way back: recovery
of trees from drought and its implication for acclimation. \emph{New
Phytologist} \textbf{228} , 1704--1709.

Goodsman DW, Lusebrink I, Landh\textbackslash{}euroausser SM, Erbilgin
N, Lieffers VJ. 2013. Variation in carbon availability, defense
chemistry and susceptibility to fungal invasion along the stems of
mature trees.\emph{New Phytologist} \textbf{197} , 586--594.

Hartmann H. 2015. Carbon starvation during drought-induced tree
mortality -- are we chasing a myth? \emph{Journal of Plant
Hydraulogy}\textbf{2} , e--005. https://doi.org/10.20870/jph.2015. e005.

Hartmann H, Trumbore S. 2016. Understanding the roles of nonstructural
carbohydrates in forest trees -- from what we can measure to what we
want to know. \emph{New Phytologist} \textbf{211} , 386-403

Hartmann H, Moura CF, Anderegg WR, Ruehr N, Salmon Y, Allen CD, Arndt
SK, \emph{et al.,} 2018. Research frontiers for improving our
understanding of drought-induced tree and forest mortality. \emph{New
Phytologist} \textbf{218} , 15-28.

He W, Liu H, Qi Y, Liu F, Zhu X. 2020. Patterns in nonstructural
carbohydrate contents at the tree organ level in response to drought
duration. \emph{Global Change Biol} ogy \textbf{26} , 3627-3638.

Hofstetter RW, Dinkins-Bookwalter J, Davis TS, Klepzig KD. 2015.
Symbiotic associations of bark beetles. In: Vega FE, Hofstetter RH (eds)
Bark beetles: biology and ecology of native and invasive species.
Academic Press, Elsevier Inc, San Diego, CA, pp 209--245.

Huang J, Hammerbacher A, Weinhold A, Reichelt M, Gleixner G, Behrendt T,
van Dam NM, Sala, A, Gershenzon J, Trumbore S, Hartmann H. 2019. Eyes on
the future - evidence for trade-offs between growth, storage and defense
in Norway spruce. \emph{New Phytologist} \textbf{222} : 144--158.

Huang J, Kautz M, Trowbridge AM, Hammerbacher A, Raffa KF, Adams HD,
Goodsman DW, \emph{et al.,} 2020. Tree defence and bark beetles in a
drying world: Carbon partitioning, functioning and modelling. \emph{New
Phytologist} \textbf{225} , 26--36.

Hussain A, Classens G, Guevara-Rozo S, Cale JA, Rajabzadeh R, Peters BR,
Erbilgin N. 2020. Spatial variation in soil available water holding
capacity alters carbon mobilization and allocation to chemical defenses
along jack pine stems. \emph{Environmental and Experimental
Botany}\textbf{171} , 103902.

Keefover-Ring K, Trowbridge A, Mason CJ, Raffa KF. 2016. Rapid induction
of multiple terpenoid groups by ponderosa pine in response to bark
beetle-associated fungi. \emph{Journal of Chemical Ecology} 42: 1-12

Keeling CI, Bohlmann J. 2006. Genes, enzymes and chemicals of terpenoid
diversity in the constitutive and induced defence of conifers against
insects and pathogens. \emph{New Phytologist} \textbf{170} , 657-675.

Kersten PJ, Kopper BJ, Raffa KF, Illman BL. 2006. Rapid analysis of
abietanes in conifers. \emph{Journal of Chemical Ecology} \textbf{22} ,
1367-1388.

Kolb TE, Fettig CJ, Ayres MP, Bentz J, Hicke JA, Mathiasen R, Stewart
JE, Weed AS. 2016. Observed and anticipated impacts of drought on forest
insects and diseases in the United States. \emph{Forest Ecology and
Management} \textbf{380} , 321--334.

Kolb TE, Keefover-Ring K, Burr SJ, Hofstetter R, Gaylord M, Raffa KF.
2019. Drought-mediated changes in tree physiological processes weaken
tree defenses to bark beetle attack. \emph{Journal of Chemical
Ecology}\textbf{45} , 888-900.

Kopper BJ, Illman BL, Kersten PJ, Klepzig KD, Raffa KF. 2005. Effects of
diterpene acids on components of a conifer bark beetle--fungal
interaction: tolerance by \emph{Ips pini} and sensitivity by its
associate \emph{Ophiostoma ips} . \emph{Environmental
Entomology}\textbf{34} , 486--493.

Krokene P. 2015. Conifer defense and resistance to bark beetles,'' in
Bark Beetles: Biology and Ecology of Native and Invasive Species. eds.
F. E. Vega and R. W. Hofstetter (Amsterdam, The Netherlands: Elsevier
Academic Press), 177--207.

Lahr EC, Krokene P. 2013. Conifer stored resources and resistance to a
fungus associated with the spruce bark beetle \emph{Ips typographus}
.\emph{PLoS ONE} \textbf{8} , e72405.

Lahr EC, Sala A. 2014. Species, elevation, and diameter affect whitebark
pine and lodgepole pine stored resources in the sapwood and phloem:
implications for bark beetle outbreaks. \emph{Canadian Journal of Forest
Research} \textbf{44} , 1312--1319.

Li W, HartmannH, AdamsHD, Zhang H, Jin C, Zhao C, Guan D, Wang A, Yuan
F, Wu J. 2018. The sweet side of global change--dynamic responses of
non-structural carbohydrates to drought, elevated CO\textsubscript{2}and
nitrogen fertilization in tree species. \emph{Tree
Physiology}\textbf{38} , 1706-1723.

Lombardero M, Ayres MP, Lorio PL, Ruel J. 2000. Environmental effects on
constitutive and inducible resin defences of \emph{Pinus taeda}
.\emph{Ecology Letters} \textbf{3} , 329-339.

Lusebrink I, Evenden ML, Guillaume Blanchet F, Cooke JEK, Erbilgin N.
2011. Effect of water stress and fungal inoculation on monoterpene
emission from an historical and a new pine host of the mountain pine
beetle. \emph{Journal of Chemical Ecology} \textbf{37} , 1013--1026.

McCullough DG, Wagner MR. 1987. Evaluation of four techniques to assess
vigor of water-stressed ponderosa pine. \emph{Canadian Journal of Forest
Research} \textbf{17} , 138-145.

McDowell NG, Sevanto S. 2010. The mechanisms of carbon starvation: how,
when, or does it even occur at all? \emph{New Phytologist} \textbf{186}
, 264--266.

McDowell NG, Pockman WT, Allen CD, Breshears DD, Cobb N, Kolb T, Plaut
J, \emph{et al.,} 2008. Mechanisms of plant survival and mortality
during drought: why do some plants survive while others succumb to
drought? \emph{New Phytologist} \textbf{178} , 719--739.

McDowell NG, Beerling DJ, Breshears DD, Fisher RA, Raffa KF, Stitt M.
2011. The interdependence of mechanisms underlying climate-driven
vegetation mortality. \emph{Trends in Ecology and Evolution}\textbf{26}
, 523-532.

Meddens AJH, Hicke JA, Macalady AK, Buotte PC, Cowles TR, Allen CD.
2014. Patterns and causes of observed piñon pine mortality in the
southwestern United States. \emph{New Phytologist} \textbf{206} , 91-97.

Meir P, Mencuccini M, Dewar RC. 2015. Drought-related tree mortality:
addressing the gaps in understanding and prediction. \emph{New
Phytologist} \textbf{207} , 28-33.

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. \emph{New Phytologist} \textbf{197,} 862--872.

Moreira Z, Glauser G, Abdala-Robert L. 2017. Interactive effects of
plant neighbourhood and ontogeny on insect herbivory and plant defensive
traits. \emph{Scientific Reports} \textbf{7,} 4047.

Mullin M, Klutsch JG, Cale JA, Hussain A, Zhao S, Whitehouse C, Erbilgin
N. 2021. Primary and secondary metabolite profiles of lodgepole pine
trees change with elevation, but not with latitude. \emph{Journal of
Chemical Ecology} \textbf{47} , 280-293

Negrón JF, McMillin JD, Anhold JA, Coulson D. 2009. Bark beetle-caused
mortality in a drought-affected ponderosa pine landscape in Arizona,
USA. \emph{Forest Ecology and Management} \textbf{257,} 1353-1362.

Netherer S, Panassiti B, Pennerstorfer J, Matthews B. 2019. Acute
drought is an important driver of bark beetle infestation in Austrian
Norway spruce stands. \emph{Frontiers Forest Global Change}
\textbf{2,}39 doi: 10.3389/ffgc.2019.00039.

Öhrn P, Berlin M, Elfstand M, Krokene P, Jönsson AM. 2021. Seasonal
variation in Norway spruce response to inoculation with bark
beetle-associated bluestain fungi one year after a severe
drought.\emph{Forest Ecology and Management} \textbf{496} : 119443

Paine TD, Raffa KF, Harrington TC. 1997. Interactions among scolytid
bark beetles, their associated fungi, and live host
conifers.\emph{Annual Review of Entomology} \textbf{42,} 179--206.

Pile LS, Meyer MD, Rojas R, Roe O, Smith MT. 2019\textbf{.} Drought
impacts and compounding mortality on forest trees in the Southern Sierra
Nevada. \emph{Forests} \textbf{10,} 237 doi:10.3390/f10030237.

Poyatos R, Aguadé D, Galiano L, Mencuccini M, Martínez-Vilalta J. 2013.
Drought-induced defoliation and long periods of near-zero gas exchange
play a key role in accentuating metabolic decline of Scots
pine.\emph{New Phytologist} \textbf{200,} 388--401.

Raffa KF, Powell EN, Townsend PA. 2013. Temperature-driven range
expansion of an irruptive insect heightened by weakly coevolved plant
defenses. \emph{Proceedings of the National Academy of SciencesUSA}
\textbf{110,} 2193-2198.

Raffa KF, Mason CJ, Bonello P, Cook S, Erbilgin N, Keefover-Ring K, et
al., 2017. Defense syndrome in lodgepole-whitebark pine ecosystems
related to degree of historical exposure to mountain pine
beetle.\emph{Plant Cell Environment} 40: 1791-1806

Roth M, Hussain A, Cale JA, Erbilgin N. 2018. Successful colonization of
lodgepole pine trees by mountain pine beetle increased monoterpene
production and exhausted carbohydrate reserves. \emph{Journal of
Chemical Ecology} \textbf{44,} 209-214.

Sala A, Woodruff D, Meinzer F. 2012. Carbon dynamics in trees: feast or
famine? \emph{Tree Physiology} \textbf{32,} 764-775

Sapes G, Demaree P, Lekberg Y, Sala A. 2021. Plant carbohydrate deplete
impairs water relations and spread via ectomycorrhizal
networks.\emph{New Phytologist} \textbf{229,} 3172-3183

Savage M. 1994. Anthropogenic and natural disturbance and patterns of
mortality in a mixed conifer forest in California. \emph{Canadian
Journal of Forest Research} \textbf{24,} 1149--1159.

Simler-Williamson AB, Rizzo DM, Cobb RC. 2019. Interacting effects of
global change on forest pest and pathogen dynamics. \emph{Annual Review
of Ecology, Evolution and Systematics.} \textbf{50,} 381--403.

Stephenson NL, Das AJ, Ampersee NJ, Bulaon BM, Yee JL. 2019. Which trees
die during drought? The key role of insect host-tree
selection.\emph{Journal of Ecology} \textbf{107,} 2383--2401.

Trugman AT, Detto M, Bartlett MK, Medvigy D, Anderegg WRL, Schwalm C,
Schaffer B, Pacala SW. 2018. Tree carbon allocation explains forest
drought-kill and recovery patterns. \emph{Ecology Letters}\textbf{21}
:1552--1560.

Turtola S, Manninen AM, Rikala R, Kainulainen P. 2003. Drought stress
alters the concentration of wood terpenoids in scots pine and Norway
spruce seedlings. \emph{Journal of Chemical Ecology}
\textbf{29,}1981--1995.

Ullah A, Klustch JG, Erbilgin N. 2021. Production of complimentary
defense metabolites reflects a co-evolutionary arms race between a host
plant and the mutualistic bark beetle-fungal complex. \emph{Plant Cell
Environment} -- In-Press. doi.org/10.1111/pce.14100

USDA Forest Service. 2002. Forest Insect and Disease Conditions on the
United States 2004. R3-02-01. USDA-Forest Service, Forest Service,
Forest Health Protection, August 2005. 142 pp.
http://www.fs.fed.us/r3/publications/documents/fidc2002.pdf, last
accessed 18 July, 2008.

Young DJN, Stevens JT, Earles JM, Moore J, Ellis A, Jirka AL, Latimer
AM. 2017. Long-term climate and competition explain forest mortality
patterns under extreme drought. \emph{Ecology Letters}\textbf{20,}
78-86.

Wiley E, Rogers BJ, Hodgkinson R, Landhäusser SM. 2016. Nonstructural
carbohydrate dynamics of lodgepole pine dying from mountain pine beetle
attack. \emph{New Phytologist} \textbf{209,} 550--562.

Woodruff DR, Meinzer FC. 2011. Water stress, shoot growth and storage of
non-structural carbohydrates along a tree height gradient in a tall
conifer. \emph{Plant Cell Environment} \textbf{34,} 1920-30.

Table 1. Treatments included in the five research questions listed in
the Methods and Materials. Treatments (C: Control, I: Inoculated, A:
Attacked). Only cells with ``X'' in a row were included in the analysis.
For question 4, only the trenched-attacked treatment was included. For
question 5, dying trees in the trenched-attacked treatment were compared
with live trees in all six treatments including those that survived in
the trenched-attacked treatment.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Research questions investigated\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Trenched\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Trenched\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Trenched\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Untrenched\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Untrenched\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Untrenched\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
C\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
I\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
A\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
C\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
I\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
A\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{1. Do treatments influence NSCs of ponderosa pines?}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\emph{Does trenching affect carbohydrates?}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\emph{Do bark beetle attacks affect carbohydrates?}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\emph{Does microbial inoculations affect carbohydrates?}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{2. Is drought-biotic stressor interaction significant for NSCs and
terpene concentrations-bark beetle attacks}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\emph{Is drought-biotic stressor interaction significant for NSCs and
terpene concentrations-inoculations}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{3. Do changes in NSCs result in changes in defense
metabolites?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{4. Do concentrations of carbohydrates and terpenes vary between
dying and live trees within the same treatment?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\emph{Do concentrations of carbohydrates and terpenes vary between dying
and control live trees?}\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
\emph{5. Can interactions between carbohydrates and terpenes explain
tree mortality?}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
X\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}



\textbf{Figure Captions}

\textbf{Figure 1.} Mean (\selectlanguage{ngerman}±SE) (\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of dried
weight) monthly variation of starch, total sugars, total non-structural
carbohydrates (NSC), and diterpenes of \emph{Pinus ponderosa} trees in
six treatments from July to November 2014 and May to September 2015.

\textbf{Figure 2.} Means (\selectlanguage{ngerman}±SE) (\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of dried
weight) of starch, total sugars, and total non-structural carbohydrates
(NSCs) of \emph{Pinus ponderosa} trees in six treatments. Trees included
in each comparison were reported in Table 1.

\textbf{Figure 3.} Monthly means (\selectlanguage{ngerman}±SE) (\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of
dried weight) of starch, total sugars, and total non-structural
carbohydrates (NSCs) of \emph{Pinus ponderosa} trees in different
comparisons. * denotes that concentrations vary in a given month (95\%
confidence level adjusted with Sidak method for two estimates). Suppl.
Table S4 shows statistical results.

\textbf{Figure 4.} Relationship between concentrations of total
diterpenes and non-structural carbohydrates (NSCs) of \emph{Pinus
ponderosa} trees by treatments. Regression lines for: (a) NSC, (b) total
sugars, and (c) starch are from repeated measures ANCOVAs on the log of
total diterpenes. Top figures: Significance of interaction between NSCs
and total diterpenes were as follows: (a) Total NSCs:
F\textsubscript{(5,256)}=1.96, P=0.085, (b) Total sugars:
F\textsubscript{(5,258)}=2.18, P=0.057, and (c) Starch:
F\textsubscript{(5,254)}=1.34, P=0.247. Bottom figures. Significance of
interaction between NSCs and total monoterpenes were as follows: (d)
Total NSCs: F\textsubscript{(5,255)}=2.07, P=0.069, (e) Total sugars:
F\textsubscript{(5,254)}=1.58, P=0.166, (f) Starch:
F\textsubscript{(5,286)}=4.98, P=0.0002. Degrees of freedom were
calculated with Satterthwaite's method.

\textbf{Figure 5.} Monthly means (\selectlanguage{ngerman}±SE) (\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of
dried weight) of carbohydrates, total diterpenes, and total monoterpenes
of dying and live \emph{Pinus ponderosa} trees in the trenched-attacked
treatment. Data are from 2014. * shows months where differences among
treatments are significant (95\% confidence level adjusted with Sidak
method for two estimates).

\textbf{Figure 6.} Monthly means (\selectlanguage{ngerman}±SE) (\selectlanguage{greek}µ\selectlanguage{english}g mg\textsuperscript{-1} of
dried weight) of carbohydrates, total diterpenes, and total monoterpenes
of dying \emph{Pinus ponderosa} trees in the trenched-attacked treatment
and live trees in the untrenched-control treatment. Data are from 2014.
* shows months where differences among treatments are significant (95\%
confidence level adjusted with Sidak method for two estimates).

\textbf{Figure 7.} Relationship between carbohydrate and terpene
concentrations from 2014 for dying \emph{Pinus ponderosa} trees in the
trenched-attacked category and all treatment categories of live trees
averaged over months. Solid (dying trees) and dashed (live trees) trend
lines indicate significant Pearson correlations. Dying trees n=8 and
live trees n=42 (except diterpene comparisons n=40). Total
non-structural carbohydrates (NSC) are the sums of starch and total
sugar concentrations.

\textbf{Figure 8.} Schematic representation of how mild drought alone or
in combination with pathogenic microbial infection and bark beetle
attacks affect carbohydrates and carbon-dependent defense metabolites
(terpenes) in pines.

\selectlanguage{english}
\FloatBarrier
\end{document}

