Contributing factors for drought in United States forest ecosystems under projected future climates and their uncertainty

Luce, Charles H.; Vose, James M.; Pederson, Neil; Campbell, John L.; Millar, C. I.; Kormos, Patrick R.; Woods, Ross

doi:10.1016/j.foreco.2016.05.020

Cited by 55 publications

(34 citation statements)

References 105 publications

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“…Although previous work has had success using SWE to predict remotely sensed NDVI [Trujillo et al, 2012], vegetation water stress has been shown to result from a spatiotemporally variable combination of (soil moisture) supply and (atmospheric) demand in snow-dominated systems where productivity may be seasonally or even sporadically limited by moisture [Emanuel et al, 2010;Luce et al, 2016;Novick et al, 2016]. In contrast to SWE, the SAI explicitly incorporates a measure of each of these conditions, and as a result, the SAI predicted 11% more of the NDVI variability in undisturbed areas throughout the SRME.…”

Section: Discussionmentioning

confidence: 99%

“…Combining the aforementioned remotely sensed data sets, this study investigates relationships between forest productivity as measured via Normalized difference vegetation index (NDVI; dependent variable) and seasonal snow accumulation, potential evapotranspiration (PET), a snow aridity index, and cumulative forest mortality (independent variables). We hypothesize that the snow aridity index may represent a particularly robust predictor of vegetation productivity since it incorporates the air temperature‐dependent impacts of increased vapor pressure deficit and reduced snowfall fraction that are among the most well‐established effects of climatic change [ Luce et al ., ; Novick et al ., ]. Moreover, moisture availability is likely to be determined to a greater degree by precipitation relative to evapotranspiration (ET) in snow‐dominated ecosystems [ Vose et al ., ].…”

Section: Introductionmentioning

confidence: 99%

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On the use of a snow aridity index to predict remotely sensed forest productivity in the presence of bark beetle disturbance

Knowles

Lestak

Molotch

2017

Water Resources Research

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We used multiple sources of remotely sensed and ground based information to evaluate the spatiotemporal variability of snowpack accumulation, potential evapotranspiration (PET), and Normalized Difference Vegetation Index (NDVI) throughout the Southern Rocky Mountain ecoregion, USA. Relationships between these variables were used to establish baseline values of expected forest productivity given water and energy inputs. Although both the snow water equivalent (SWE) and a snow aridity index (SAI), which used SWE to normalize PET, were significant predictors of the long-term (1989-2012) NDVI, SAI explained 11% more NDVI variability than SWE. Deviations from these relationships were subsequently explored in the context of widespread forest mortality due to bark beetles. Over the entire study area, NDVI was lower per unit SAI in beetle-disturbed compared to undisturbed areas during snow-related drought; however, both SAI and NDVI were spatially heterogeneous within this domain. As a result, we selected three focus areas inside the larger study area within which to isolate the relative impacts of SAI and disturbance on NDVI using multivariate linear regression. These models explained 66%-85% of the NDVI and further suggested that both SAI and disturbance effects were significant, although the disturbance effect was generally greater. These results establish the utility of SAI as a measure of moisture limitation in snow-dominated systems and demonstrate a reduction in forest productivity due to bark beetle disturbance that is particularly evident during drought conditions resultant from low snow accumulation during the winter.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the use of a snow aridity index to predict remotely sensed forest productivity in the presence of bark beetle disturbance

Knowles

Lestak

Molotch

2017

Water Resources Research

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“…Given that the 20th century was unusually wet across the eastern USA, our understanding of the synchrony of forest mortality from late 20th century studies is likely to be limited, because prior centuries experienced more frequent and intense droughts across this region (Pederson et al, ). Although the eastern USA is projected to become wetter, it is also likely to experience more consecutive dry days in summer (Luce et al, ) that could increase the impacts of drought, imparting long‐term legacies on forests. Drought has been shown to alter the rate of forest succession (Dovčak, Frelich, & Reich, ) and create colonization windows that affect species establishment (Bartha, Meiners, Pickett, & Cadenasso, ).…”

Section: A Review Of Documented Forest Mortality Probably Driven By Cmentioning

confidence: 99%

“…(b) Observations of elevated regional tree mortality events across eastern North America grouped by years of observed mortality. Numbers show the location of the mortality event linked to the reference in Table 1 become wetter, it is also likely to experience more consecutive dry days in summer (Luce et al, 2016) that could increase the impacts of drought, imparting long-term legacies on forests. Drought has been shown to alter the rate of forest succession (Dovčak, Frelich, & Reich, 2005) and create colonization windows that affect species establishment (Bartha, Meiners, Pickett, & Cadenasso, 2003).…”

Section: Ta B L E 1 (Continued)mentioning

confidence: 99%

Redefining temperate forest responses to climate and disturbance in the eastern United States: New insights at the mesoscale

Druckenbrod

Martín-Benito

Orwig

et al. 2019

Global Ecol Biogeogr

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Aim Climate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso‐ and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales. Location Eastern USA. Time period Last century to present. Major taxa studied Temperate broadleaf forests. Methods We review regional literature of past tree mortality studies associated with climate to identify mesoscale climate‐driven disturbance events. Using a dynamic vegetation model, we then simulate how these forests respond to a typical climate‐driven disturbance. Results By identifying compound disturbance events from both a literature review and simulation modelling, we find that synchronous patterns of drought‐driven mortality at mesoscales have been overlooked within these forests. Main conclusions As ecologists, land managers and policy‐makers consider the intertwined drivers of climate and disturbance, a focus on spatio‐temporal scales equivalent to those of the drivers will provide insight into long‐term forest change, such as drought impacts. Spatially extensive studies should also have a long temporal scale to provide insight into pathways for forest change, evaluate predictions from dynamic forest models and inform development of global vegetation models. We recommend integrating data collected from spatially well‐replicated networks (e.g., archaeological, historical or palaeoecological data), consisting of centuries‐long, high‐resolution records, with models to characterize better the mesoscale response of forests to climate change in the past and in the future.

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“…Instead, managers may aim for basal areas that are closer to the low end of the HRV distribution (lower basal areas) while also falling within FRV1. In this sense, approximating the HRV remains a reasonable null criterion rather than aiming for projected targets with high climatic and ecological uncertainty (Mellert et al 2015, Luce et al 2016).…”

Section: Managing For Resiliencementioning

confidence: 99%

Use of landscape simulation modeling to quantify resilience for ecological applications

et al. 2018

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Goals of fostering ecological resilience are increasingly used to guide U.S. public land management in the context of anthropogenic climate change and increasing landscape disturbances. There are, however, few operational means of assessing the resilience of a landscape or ecosystem. We present a method to evaluate resilience using simulation modeling. In this method, we use historical conditions (e.g., in North America, prior to European settlement), quantified using simulation modeling, to provide a comparative reference for contemporary conditions, where substantial departures indicate loss of resilience. Contemporary ecological conditions are compared statistically to the historical time series to create a resilience index, which can be used to prioritize landscapes for treatment and inform possible treatments. However, managing for resilience based on historical conditions is tenuous in the Anthropocene, which is characterized by rapid climate change, extensive human land use, altered disturbance regimes, and exotic species introductions. To account for the future variability of ecosystems resulting from climate and disturbance regime shifts, we augment historical simulations with simulations of ecosystem dynamics under projected climate and land use changes to assess the degree of departure from benchmark historical conditions. We use a mechanistic landscape model (FireBGCv2) applied to a large landscape in western Montana, USA, to illustrate the methods presented in this paper. Spatially explicit ecosystem modeling provides the vehicle to generate the historical and future time series needed to quantify potential resilience conditions associated with past and potential future conditions. Our methods show that given selection of a useful set of metrics, managers could use simulations like ours to evaluate potential future management directions.

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Contributing factors for drought in United States forest ecosystems under projected future climates and their uncertainty

Cited by 55 publications

References 105 publications

On the use of a snow aridity index to predict remotely sensed forest productivity in the presence of bark beetle disturbance

On the use of a snow aridity index to predict remotely sensed forest productivity in the presence of bark beetle disturbance

Redefining temperate forest responses to climate and disturbance in the eastern United States: New insights at the mesoscale

Use of landscape simulation modeling to quantify resilience for ecological applications

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