Forest Drought Resistance at Large Geographic ScalesP. G. Brodrick1,2 , L. D. L. Anderegg1,3 , and G. P. Asner1,2

1Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA, 2Center for Global Discovery andConservation Science, Arizona State University, Tempe, AZ, USA, 3Department of Integrative Biology, University ofCalifornia Berkeley, Berkeley, CA, USA

Abstract Forest conservation and carbon sequestration efforts are on the rise, yet the long‐term stabilityof these efforts under a changing climate remains unknown. We generate nearly three decades ofremotely sensed canopy water content throughout California, which we use to determine patterns ofdrought stress. Linking these patterns of drought stress with meteorological variables enables us to quantifyspatially explicit biophysical drought resistance in terms of magnitude and duration. These maps revealsignificant spatial heterogeneity in drought resistance and demonstrate that almost all forests have lessresistance to severe, persistent droughts. By identifying the spatial patterning of biophysical droughtresistance, we quantify an important component of long‐term ecosystem stability that can be used for forestconservation, management, and policy decisions.

Plain Language Summary As hot droughts become more frequent and more severe, it isimportant for long‐term forest management to understand which forests are at risk and which have thecapacity to withstand these events. To address this challenge, we generated and analyzed maps of canopywater content through time and compared them to maps of meteorology. This analysis revealed that somelocations were able to endure significantly more drought before succumbing to significant canopywater loss, which indicates drought resistance. Our findings also highlighted that the effects of a recent,severe drought have persisted multiple years after the drought subsided. These findings are an importantfirst step toward assessing spatially explicit forest stability in the face of a changing climate.

1. Introduction

Ecosystems faced with climate change demonstrate either long‐term stability or vulnerability. The rise ofconservation and carbon sequestration efforts has amplified the need to understand the geography of refu-gia, locations with high long‐term ecological stability, particularly in the face of extreme events that cancause rapid ecosystem shifts. Hot droughts, which are increasingly likely in the future, will significantlyimpact forests around the globe (Allen et al., 2010; Anderegg et al., 2015; Anderegg, Anderegg, et al.,2013; Anderegg, Kane, et al., 2013; Diffenbaugh et al., 2015). Yet mapping forest resistance and resilience,primary components of ecosystem stability, remains challenging. One strategy is to leverage the relationshipbetween biodiversity and ecosystem stability (Isbell et al., 2015; Tilman & Downing, 1994). Using thisapproach, identifying biodiversity hotspots (Myers et al., 2000) and/or mapping functional diversity acrosslandscapes (Asner et al., 2017; Díaz & Cabido, 2001) can help prioritize conservation or sequestration activ-ities. However, directly assessing spatially explicit resistance remains an open challenge.

Ecological resistance is the degree to which a biological variable is changed following a perturbation (Pimm,1984). In the context of drought, at the plant scale, alterations to the plant water balance are typical pertur-bations, while plant water stress, physiological damage, or plant mortality are the biological response(Anderegg, Anderegg, et al., 2013; Anderegg, Kane, et al., 2013; Choat et al., 2018). The plant water balancecan be altered by supply, influenced by precipitation and groundwater, or demand, influenced by tempera-ture, vapor pressure, and sunlight (Stephenson, 1990). This theory scales to the landscape, where hotdroughts invoke greater physiological responses in forests by influencing both water supply and demand(Allen et al., 2015; Clark et al., 2016), particularly when the deviations from normal are extreme (Mitchellet al., 2014). Thus, drought resistant ecosystems must be able to withstand coupled extremes of precipitationand temperature.

Requisite to the identification of drought refugia is the resolution of spatial and temporal indicators ofdrought‐induced biological response. Early efforts linking meteorology with forest response have included

©2019. The Authors.This is an open access article under theterms of the Creative CommonsAttribution‐NonCommercial‐NoDerivsLicense, which permits use and distri-bution in any medium, provided theoriginal work is properly cited, the useis non‐commercial and no modifica-tions or adaptations are made.

RESEARCH LETTER10.1029/2018GL081108

Data accessibility: Data to reproducethe results are available at the link pro-vided in the supporting information,with a registered DOI.

Key Points:• Meteorology and physiological

forest drought response are relatedwhen considered over multiple years

• Forest physiological responses maysignificantly lag behind severemeteorological drought

• Forest biophysical droughtresistance is spatially heterogeneousand can be mapped at large scales

Supporting Information:• Supporting Information S1

Correspondence to:P. G. Brodrick,brodrick@alumni.stanford.edu

Citation:Brodrick, P. G., Anderegg, L. D. L., &Asner, G. P. (2019). Forest droughtresistance at large geographic scales.Geophysical Research Letters, 46.https://doi.org/10.1029/2018GL081108

Received 26 OCT 2018Accepted 19 JAN 2019Accepted article online 25 JAN 2019

BRODRICK ET AL. 1

spatially explicit but temporally static relationships (Paz‐Kagan et al., 2017; Young et al., 2017) or temporallydynamic but spatially limited relationships (Bell et al., 2018; Chen et al., 2010). The simultaneous examina-tion of vegetation response to drought through both time and space requires a robust indicator of forest phy-siological response to drought.

One such indicator is canopy water content (CWC), the product of leaf area index (LAI), leaf mass per area,and leaf water content. CWC is a measure of the total amount of liquid water held within canopy foliage.CWC can be estimated using laser‐guided high‐fidelity imaging spectroscopy data, by analyzing a broadrange of spectral features (Gao & Goetz, 1990; Green et al., 2006; Ustin et al., 1998). The CarnegieAirborne Observatory was used to collect such data for this study (Asner et al., 2012). At the landscape level,remotely sensed CWC has been linked to site‐specific water balance (Paz‐Kagan et al., 2018) and is related toground‐level measurements of foliage dieback (Martin et al., 2018), suggesting that changes in LAI are adominant contributor to changes in CWC. Analyzed through time, changes in CWC provide an indicationof forest vulnerability (Asner et al., 2016) and mortality (Brodrick & Asner, 2017) in response to drought.

The U.S. state of California is a biodiversity hotspot (Myers et al., 2000), and its forests include the largest,tallest, and oldest trees on Earth. California has widely variable land tenure, including active forestry pro-jects, and faces consistent influence from forest fires (Steel et al., 2015) and bark beetles (Raffa et al.,2008). Between 2012 and 2015, the state was struck by a one in 10,000‐year drought (Robeson, 2015) andhas experienced multiple less severe droughts over the past several decades. Consequently, California forestsprovide an excellent regional case to examine drought resistance. Using a newly generated multidecadalrecord of CWC, along with corresponding meteorological data, we ask (1) what meteorological indicatorscorrespond with increased forest vulnerability and (2) how resistant are different forests to severe drought.Together, answers to these questions provide a pathway toward quantifying ecosystem stability and forestrefugia, helping to inform forest management, conservation, and policy decisions.

2. Methods

In August 2015, July 2016, and August 2017, the Carnegie Airborne Observatory collected high‐fidelity ima-ging spectroscopy and light detection and ranging data over 2.28 million ha of California (Figure S1). Thesedata were then used to estimate CWC, the amount of liquid water in forest canopies above 2 m in height. Adeep learning model was developed to link CWCmeasurements with satellite‐based environmental data, asin Asner et al. (2016), with spatial and temporal validation performance exceeding an R2 of 0.8 (Figure S2).This trained deep learning model was then used with new environmental data from 1990 to 2017 to deter-mine dry‐season (July–August) CWC for the entire state at a 30‐m ground‐level spatial resolution. We thencollected precipitation, temperature, vapor pressure deficit, climate water deficit (CWD; Thornthwaite,1948), and Palmer Drought Severity Index data (Abatzoglou et al., 2014; Daly et al., 2008) for the correspond-ing time period; aggregated these data over the period preceding the CWC maps (1 August to 31 July); andexamined deviations from the long‐term median through time (Figures S3–S5).

Both precipitation and temperature play important roles in determining the impact of drought on vegeta-tion.While some existing drought metrics like CWD account for this, we found them to be a poor match withCWC (see section 3). Consequently, we create a new combined precipitation and temperature metric (PT)that amplifies the precipitation median deviation by the square of the temperature deviation from the med-ian, calculated as

PT ¼ Zprecip t þ Ztemp� �2 ∀ Ztemp > t

Zprecip ∀ Ztemp ≤ t;

((1)

where Z indicates the z score (the deviation from the median relative to the standard deviation), and t is aspecified threshold. We set the threshold to 1.0 and explore sensitivities in the supporting information(Figures S10, S12, and S14).

To examine longer‐term effects, we introduce two new metrics, the duration and the magnitude of signifi-cant deviation (denoted with the subscripts dur and mag, respectively), which we calculated for CWC as wellas each meteorological variable. We calculate duration as the number of years where the variable of interestexceeds a threshold of deviation from the median within a 4‐year window, and magnitude as the total

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amount (summed over the same period) of deviation from the median.Wealso examine a slight variation, considering only consecutive years ofdeviation, which we denote as c.dur and c.mag for duration andmagnitude, respectively.

Finally, we investigate drought resistance by examining the relationshipbetween meteorological deviations and physiological drought response.Highly resistant ecosystems can endure drought without significantalteration. Thus, we define the duration of drought resistance as the num-ber of years that an area can withstand PT levels more than one standarddeviation below the median prior to CWC falling more than 10% belowthe median (sensitivities to these thresholds are examined in FiguresS11 and S13). We also define the magnitude of drought resistance as theintegral of PT deviation from the median over the drought resistance timeperiod. Drought resistance duration and magnitude are both illustrated ina conceptual diagram in Figure 1, and an example calculation is per-formed in Figure S7.

Significant additional methodological detail, the code used to analyze alldata and produce all figures, CWC data for the 1990–2017 time series,and Google Earth Engine code to download the meteorological data from

publicly available sources are all available in the supporting information.

3. Results3.1. Linking Meteorological Drought to Physiological Response

Forest CWC varies interannually for numerous reasons including fire, forest management, leaf area, andtree mortality. Dry‐season CWC from 1990 to 2017 did not simply covary with annualized meteorologicalmetrics as shown by the statewide, average relationships between CWC and precipitation, temperature,and CWD through time (Figure 2). Associations are weak, and while some to explain a few specific events(e.g., the precipitation deficit in 2001), none are strongly correlated with CWC through time.Furthermore, the 2012–2015 drought, documented as one of the most severe droughts in California in cen-turies, does not stand out as particularly significant in either the meteorological or CWC signals.Consequently, an alternative metric was needed to quantify forest responses to meteorological drought.

Deviations of CWC and meteorological factors from their long‐term median through time (Figures S3–S5)indicated that the duration of CWC deviations is important for understanding forest responses to climate.To examine this, we used the temporal variables of duration and magnitude described above. We found thatPTdur and CWCdur are well correlated through time, with an R2 of 0.83 (Figures 3a and 3b). Furthermore, theeffects of the 1990–1993, 2001–2003, 2007–2009, and particularly the 2012–2015 droughts are all notable inCWCdur (Figure 3a). High values of PTdur indicate multiyear water deficits, and the correlation with CWCdur

suggests that forests in California respond to long‐term accumulated water stress. Additionally, we exam-ined persistent drought by relating PTc.dur and CWCc.dur (Figures 2c and 2d). This demonstrates that notonly was the 2012–2015 event significant and sustained, but that there was no reprieve for multiple years.Notably, the signals between CWC and PT were stronger than between CWC and other meteorological vari-ables including temperature, precipitation, vapor pressure deficit, Palmer Drought Severity Index, and CWDfor both multiyear and consecutive multiyear droughts (Figures S8 and S9).

These results reveal a link between sustained meteorological drought and the subsequent forest canopy phy-siological response. Our meteorological indicator, PT, is easily calculated from publicly available data andlinks with CWC changes at the scale of California—a state with heterogeneous forests and a complex historyof land tenure and fire management. We found similar results by repeating the analysis from Figures 2 and 3in individual ecoregions of California. PT consistently matched well with CWC changes in each ecoregion,further supporting its robustness (figures not shown). Our newmetric PT is both simple and intuitive, draw-ing on concepts from the literature suggesting that both supply (precipitation) and demand (temperature)

Figure 1. Conceptual diagram of forest drought resistance. A meteorologi-cal indicator of drought (PT) is shown in black, while a metric of treephysiological response to drought (CWC) is shown in blue. The duration ofdrought resistance is the amount of time (years) that an area canwithstand PT levels more than one standard deviation below the medianprior to CWC falling more than 10% below the median. The magnitude ofdrought resistance is the integral of PT deviation from the median over thedrought resistance time period.

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drive forest vulnerability. While tree mortality is often driven by factors such as fire and bark beetle out-breaks, these are also influenced by precipitation and temperature and thus are captured by PT.

While on average, PTdur and PTc.dur relate well with CWCdur and CWCc.dur, these correlations do not alwayshold. The most striking mismatch occurred in 2016 and 2017, evidenced by the two points in the upper leftcorner of Figure 3d. Despite drought relief in the 2015–2016 and 2016–2017 (Figure S4), CWC levels in 2016and 2017 remained suppressed. To investigate this mismatch, wemapped the number of consecutive years ofnegative CWC deviation in 2017 (Figure 4). A strong concentration of successive CWC deviation in thesouthern Sierra Nevada is apparent, as well as smaller pockets throughout the northern portionsof California.

Figure 2. Weak correlations between state‐wide forest average canopy water content (CWC, L/m2) and different meteor-ological indicators: precipitation (mm), climate water deficit (CWD, mm), and temperature (°C). CWC is derived fromdata collected by the Carnegie Airborne Observatory (Asner et al., 2016), and meteorological data are from the PRISMClimate Group (Daly et al., 2008). All p values are below 0.05.

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The 2012–2015 drought generated a pulse of tree mortality, culminating in the death of an estimated 129mil-lion trees by 2017 (Moore et al., 2018). The lingering influence of this tree mortality drives much of the multi-year CWC suppression mapped in Figure 4. The regions of the southern Sierra Nevada with the mostconcentrated multiyear CWC loss are coincident with aerial survey reports of significant tree mortality from2015 and 2016 (Moore et al., 2017). The scattered pockets with sustained CWC loss in northern California,however, are not particularly highlighted in aerial surveys, likely because the absolute number of trees inthese areas is low. Unlike mortality counts, CWC deviation is relative and thus is independent of the numberof trees in a particular location. Observed CWC lags may also result from long‐term leaf area reductions thatcan occur withoutmortality, consistent with the pervasive legacy effects of drought seen in the growth of sur-viving trees (Anderegg et al., 2015; Trugman et al., 2018). Several areas of sustained CWC deviation inFigure 4 also coincide with recent fires, demonstrating the influence of nonmeteorological factors on CWC.

3.2. Spatially Explicit Drought Resistance

California's climate is characterized by periods of multiyear drought that may be punctuated by brief wetperiods (Woodhouse et al., 1998). To quantify resistance to long periods of severe drought, we map the totalmeteorological deviation that each forest was able to withstand over a 4‐year period before succumbing tosuppressed CWC levels (Figures 5a and 5b). We map this resistance both in terms of the maximum magni-tude of PT (4‐year sum, PTmag) prior to CWC deviation (Figure 5a) and by the maximum number of years(PTdur) prior to CWC deviation (Figure 5b). As prolonged drought can be particularly consequential for for-est ecosystems (Figures 3 and 4), we also map resistance (both magnitude, PTc.mag, and duration, PTc.dur) toconsecutive years of drought (Figures 5c and 5d).

Figure 3. The influence of multiyear drought (a) and consecutive multiyear drought (c) on canopy water content (CWC).The state‐wide mean number of preceding years within a 4‐year window where either CWC or meteorological droughtsignificantly departed from the mean is shown in (a). The same is shown in (c) for consecutive, rather than total years.These relationships are decoupled from time in (b) and (d) (both p values are less than 0.01). CWC is shown in black, andthe precipitation‐temperature (PT) metric is shown in green.

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Resistance varies significantly throughout the state, with redwood forestsin the northwest generally displaying greater resistance to long‐termdrought than the mixed conifer forests of the Sierra Nevada. Resistancemagnitude and duration show fairly consistent patterns overall, thoughresistance magnitude in some areas of the northwest and the southeastSierra Nevada is relatively higher than the corresponding resistance dura-tion, highlighting the importance of considering both drought magnitudeand duration. Forests throughout California showed substantially lessresistance to consecutive drought than to total drought, both in terms ofmagnitude and duration. This is particularly evident in the lower eleva-tions of the Sierra Nevada, consistent with the widespread mortalityobserved in that region throughout the 2012–2015 drought.

4. Discussion

Preparing for the risk of drought‐induced tree mortality is a critical com-ponent of forest management, particularly as the frequency, duration, andseverity of hot droughts continues to increase. In California, the use of ter-restrial carbon sequestration as a cap‐and‐trade offset within theCalifornia Air Resources Board Compliance Offsets Program (CaliforniaEnvironmental Protection Agency, 2015) makes understanding the resis-tance and resilience to drought‐induced tree mortality a pressing matter.We support this understanding by quantifying relationships betweenmeteorological drought and forest physiological response (Figure 3) atlarge scales. We argue that areas that experienced sustained meteorologi-cal drought, but that did not demonstrate substantial deviations in CWC,exhibit drought resistance.

Here we defined drought resistance as the amount, both in magnitude and duration, of meteorologicaldrought that forests can withstand before CWC falls significantly below the long‐term median (Figure 1).Such resistance can be caused primarily by two factors, biological resistance or access to an alternate watersupply. Biological resistance encompasses plant physiological and morphological adaptations to long‐termdroughts. Examples include adaptations with indirect effects on CWC, such as sclerophylly (De Micco &Aronne, 2012) and decreased stomatal conductance (Tosens et al., 2012), as well as those that directly alterCWC, such as reduced transpiration through decreased LAI (Basu et al., 2016; Jump et al., 2017). Notably,LAI reduction strategies (either through leaf shedding, decreased leaf production, decreased leaf size, or par-tial woody dieback) reduce CWC levels (Martin et al., 2018; Nydick et al., 2018) and so would only bedetected as resistant if the LAI was reduced by less than 10%. Future investigations coupling field measure-ments of LAI and hyperspectral imagery could refine the characterization of drought resistance. We notethat drought response strategies are species specific as are the corresponding CWC changes (Brodrick &Asner, 2017). The second explanation for resistance is access to alternate (not direct precipitation) sourcesof water. These water supplies could include significant utilization of fog, groundwater, standing water, run-off, and/or snowmelt availability.

Collectively, we refer to these forms of spatially explicit resistance as biophysical resistance. Irrespective ofthe cause, areas that demonstrate high biophysical resistance have the ability to withstand multiple yearsof drought. The combined nature of this metric has both benefits and drawbacks. Benefits center on the factthat the metric is all‐encompassing and thus if initial conditions do not change it is reasonable to assumethat an area will maintain a similar level of resistance in the future. The drawback comes from the assump-tion of the static initial condition, which will fail in circumstances such as species compositional shifts orsubstantive alterations to groundwater aquifers. The presented biophysical resistance is also bound by theclimate conditions of the last three decades. While this period contains one of the most severe and sustaineddroughts in recent history, if droughts increase in frequency and severity (Diffenbaugh et al., 2015), we mayultimately underestimate long‐term resistance. Additionally, over the 30‐year record explored, spatial

Figure 4. Themapped number of years of consecutive canopywater content(CWC) loss in 2017. This map corresponds to the last point in time inFigure 3c, where a strong deviation occurred between meteorologicaldrought and CWC loss (Figure 3d), and demonstrates lagged drought effects.

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variability and species‐specific differences in plant responses to rising CO2 levels may complicate patterns offorest drought resistance. Further investigation into these effects is warranted.

Biophysical resistance is important for assessing widespread ecosystem stability, but it does not quantify resi-lience, the ability of a system to undergo stress and subsequently recover (Holling, 1973). A recent studymapped the contributions of climatic variables to ecosystem resilience (Seddon et al., 2016) and demon-strated that precipitation, temperature, and cloudiness influenced vegetation sensitivity in California

Figure 5. The magnitude (a) and duration (b) of resistance to drought in forested areas throughout California. Resistanceis calculated as either the total amount (a) or the number of years (b) of significant meteorological drought withina 4‐year period where canopy water content did not fall critically below the median. The magnitude and duration ofresistance to consecutive years of drought is shown in (c) and (d), respectively.

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forests, consistent with our findings. Plants with reduced levels of CWC, particularly those that utilize LAIreduction strategies, may be able to return to normal after a drought. To quantify forest resilience, however,additional work is needed to distinguish between recovery and species turnover, which requires additionalinformation beyond CWC. Future efforts could map LAI through both space and time to disentangle differ-ent aspects of CWC changes, or even use a time series of spatially explicit functional diversity (Asner et al.,2017), coupled with CWC changes through time, to identify resilience and consequently stability.

Despite these limitations, our spatially explicit measures of biophysical drought resistance are a critical steptoward mapping ecosystem stability. As California seeks to set a standard for carbon offsets based on terres-trial sequestration, the long‐term ecosystem stability of forests is a vital consideration.We contend that refin-ing forest management and conservation practices based on spatial patterns of resistance and resilience hasthe potential to make the carbon sequestration efforts significantly more robust.

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AcknowledgmentsThe authors would like to thank theCarnegie Airborne Observatory staff forassistance with data collection. Thismanuscript is a product of The Leaf toLandscape Project, in collaborationwith the US National Park Service andUSGS. Data collection was funded bythe David and Lucile PackardFoundation, the US National ParkService – Sequoia and Kings CanyonNational Parks, the USGS's SouthwestClimate Science Center, US ForestService Region‐5, and the CaliforniaDepartment of Forestry and FireProtection. Analysis was supported bythe Avatar Alliance Foundation and theCarnegie Institution for Science.L. D. L. A. received funding from theNSF (DBI‐1711243) and a Climate andGlobal Change postdoctoral fellowshipfrom the NOAA. The CarnegieAirborne Observatory has been madepossible by grants and donations toG. P. Asner from the Avatar AllianceFoundation, Margaret A CargillFoundation, David and LucilePackard Foundation, Gordon and BettyMoore Foundation, GranthamFoundation for the Protection of theEnvironment, W M Keck Foundation,John D and Catherine T MacArthurFoundation, Andrew MellonFoundation, Mary Anne Nyburg Bakerand G Leonard Baker Jr, and William RHearst III. Data and code links areavailable in the supporting information.Author contributions: P. G. B. designedthe study. G. P. A. led the datacollection campaign, with assistancefrom P. G. B. P. G. B. analyzed the data.All authors discussed and organized theresults. P. G. B. wrote the manuscriptwith contributions from L. D. L. A. andG. P. A.

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