Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach

Abstract

a b s t r a c tEfforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broadscale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other datasets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts.Published by Elsevier B.V.

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

“… Relationships between mortality and NDVI‐based EWS metrics are strongest with finer spatial‐scale and longer temporal‐scale imagery. Relationships with NDVI trends are detectable over longer time windows compared to jumps, as the former captures gradually declining vigor and the latter inciting events. Relationships between mortality and EWS metrics are strongest in annually measured sites because longer remeasurement intervals add uncertainty as to the timing of mortality. Relationships are strongest in aspen‐dominated sites, and particularly those that are pure aspen (such as CIPHA). This is because (i) aspen's deciduous leaf habit results in more interannual variability in productivity (Welp et al., ) and leaf condition, as observed by NDVI, that responds more quickly to environmental stress compared to conifers (Gamon et al., ; Norman, Koch, & Hargrove, ); (ii) aspen are pioneer species and have comparatively high mean mortality rates, especially in later succession (Figure b) (Stephenson et al., ; Vanderwel, Zeng, Caspersen, Kunstler, & Lichstein, ); (iii) aspen die‐off begins in the upper canopy (Anderegg & Callaway, ; Frey, Lieffers, Hogg, & Landhausser, ), which can be detected with multispectral imagery (Huang & Anderegg, ); (iv) aspen are clonal, meaning patches of genetically identical trees die together, and relatively quickly as a strategy for effective resprouting (Frey et al., ); (v) and finally, aspen have documented sensitivity to defoliation and drought, including mortality (Bell, Bradford, & Lauenroth, ; Chen et al., ; Hogg, Brandt, & Kochtubajda, ; Worrall et al., ). …”

Lagged mortality among tree species four years after an exceptional drought in east Texas

“…Forest Inventory and Analysis plots are re-measured every five to ten years depending on location yet annual subsets of plots (panels) can provide valuable documentation of broad disturbances such as droughts in forests (Shaw et al 2005). However, these technologies are limited in their ability to capture detailed inventory measurements such as species, stem diameter, stem density, and understory effects (Norman et al 2016). Remote sensing technologies such as airborne or spaceborne imagery and LiDAR can document broad-scale forest changes in near real time .…”

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

“…To test whether drought was a significant contributor across all mortality events, we examined, at the location of each event, departures from two climate indices independent of the original mortality observations, using climate records from PRISM Climate Group (): mean summer precipitation (June, July, August; JJA) and August standardized precipitation–evapotranspiration index (SPEI) for the same 3‐month time‐scale (notated as SPEI3). SPEI is a multiscalar drought index that includes the effect of temperature and precipitation and is commonly used to assess the response of forests to climatic variability (Norman, Koch, & Hargrove, ). These climate indices show that summer precipitation did, in fact, decrease below ≥ 1 SE of the 120‐year mean starting 5 years before the observed mortality (Figure a).…”