Reconstructing past forest composition and abundance by using archived Landsat and national forest inventory data

Thapa, Bina; Wolter, Peter T.; Sturtevant, Brian R.; Townsend, Philip A.

doi:10.1080/01431161.2019.1711245

Cited by 11 publications

(4 citation statements)

References 88 publications

(177 reference statements)

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“…In brief, forest composition was derived from Thapa et al. (2020) to represent the relative basal area (reported as a percentage of the total basal area) for both preferred and the full host complement for each respective defoliator, measured at two time periods (1985 and 2005). Four land cover structure variables (area‐weighted mean non‐forest patch size (ha), Shannon index of forest cover diversity, percent forest, and forest edge density (m/ha)) were derived from a time‐series of land cover maps (Wolter et al., 2012), averaged across the time period 1975–2000.…”

Section: Methodsmentioning

confidence: 99%

“…Independent variables consisted of both forest composition and land cover structure variables. In brief, forest composition was derived from Thapa et al (2020) to represent the relative basal area (reported as a percentage of the total basal area) for both preferred and the full host complement for each respective defoliator, measured at two time periods (1985 and 2005).…”

Section: Landscape Partitioningmentioning

confidence: 99%

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Confronting the cycle synchronisation paradigm of defoliator outbreaks in space and time—Evidence from two systems in a mixed‐species forest landscape

Cooke,

Robert,

Sturtevant

et al. 2023

Journal of Ecology

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Defoliators cause extensive damage in boreal and temperate forests of the world. Considerable effort has been invested to understand their individual population dynamics, and despite ample theorising, there is little empirical evidence on factors causing spatial synchrony of pest eruptions at landscape scales. We report on the landscape‐level effect of forest configuration and composition on the intensity of outbreaks of spruce budworm and forest tent caterpillar in a mixedwood boreal forest in northern Minnesota (USA) and adjacent Ontario (Canada), and how this is related to the degree of spatial synchrony in each species' outbreak cycling. Using a large spatiotemporal tree‐ring reconstruction of outbreak impacts across these two systems, we evaluate two contrasting theories governing defoliator outbreaks: harmonic oscillation (a.k.a. ‘clockwork’) and relaxation oscillation (a.k.a. ‘catastrophe’), each with consequences linked to top‐down versus bottom‐up influences on outbreak behaviour in time and space. We find synchrony varies temporally, among outbreak cycles and in direct proportion to cycle peak intensity; however, cycle peak intensities are distributed bimodally in time, and so, therefore, are synchrony coefficients. Spatially, the area where each pest species currently cycles with the greatest peak intensity and synchrony is where their preferred host trees are currently found in greatest proportion. Despite overall synchrony in cycling, we found, in both systems, a persistent negative spatial correlation among successive eruptive pulses of defoliation. Many of these eruptions failed to spread spatially and to coalesce with other spot eruptions to form extensive area‐wide outbreaks. Eruptions often fail to spread at the hardwood‐conifer interface, resulting in outbreak pulses that systematically bounce back and forth between landscape types, particularly when systems were cycling at low amplitude. These over‐dispersed spatial patterns of pulse impact are consistent with a contagious theory of eruption and outbreak spread. They could be considered consistent with harmonic oscillation theory only for populations cycling at different frequencies, with cycling frequency determined by host forest landscape structure. Synthesis. We find that defoliator outbreak dynamics across systems include spatiotemporal signatures of each theoretical paradigm—suggesting a hybrid approach will better characterise outbreak behaviour. Host concentration influences which paradigm dominates the spatial dynamics in any given forest landscape context. Because of the synchronising effect of host concentration on forest insect spatial dynamics, mixedwoods appear to be less prone to intense, synchronised defoliator attack than forests of pure hardwood or pure conifer.

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Section: Methodsmentioning

confidence: 99%

Section: Landscape Partitioningmentioning

confidence: 99%

Confronting the cycle synchronisation paradigm of defoliator outbreaks in space and time—Evidence from two systems in a mixed‐species forest landscape

Cooke,

Robert,

Sturtevant

et al. 2023

Journal of Ecology

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“…In this calibration process, certain assumptions regarding both the spatial and biophysical accuracy of FIA field plot data as well as the allometry used to determine CBD were adopted (Keane et al 2006). With respect to FIA, recent work in Minnesota, USA, provides evidence to question some of the common assumptions regarding the combined use of Landsat and FIA for mapping biophysical forest structure information, especially spatial accuracy and suboptimal subplot design with regard to 30-m satellite sensor data (Thapa et al 2020). Regardless of the sources of mapping error, it is understood that the absolute accuracy of the LANDFIRE CBD data product varies regionally (Keane et al 2006;Scott 2008;Krasnow et al 2009) and should not replace locally derived fuel products if they exist at finer spatial scales (Keane et al 2006), which is the pretext for this research.…”

Section: Introductionmentioning

confidence: 99%

Modeling sub-boreal forest canopy bulk density in Minnesota, USA, using synthetic aperture radar and optical satellite sensor data

2021

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Background National estimates of canopy bulk density (CBD; kg m−3) for fire behavior modeling are generated and supported by the LANDFIRE program. However, locally derived estimates of CBD at finer scales are preferred over national estimates if they exist, as the absolute accuracy of the LANDFIRE CBD product is low and varies regionally. Active sensors (e.g., lidar or radar) are better suited for this task, as passive sensors are ill equipped to detect differences among key vertical fuel structures, such as coniferous surface fuels (≤2 m high) and canopy fuels above this threshold—a key categorical fuel distinction in fire behavior modeling. However, previous efforts to map CBD using lidar sensor data in the Superior National Forest (SNF) of Minnesota, USA, yielded substandard results. Therefore, we use a combination of dormant-season synthetic aperture radar (SAR) and optical satellite sensor data to (1) expand detectability of coniferous fuels among mixed forest canopies to improve the accuracy of CBD modeling and (2) better understand the influence of surface fuels in this regard. Response variables included FuelCalc output and indirect estimates of maximum burnable fuel based on canopy gap fraction (CGF) measured at ground level and 2 m above ground level. Results SAR variables were important predictors of CBD and total fuel density (TFD) in all independent model calibrations with ground data, in which we define TFD as the sum of CBD and primarily live coniferous surface fuel density (SFD) 0 to 2 m above ground. Exploratory estimates of TFD appeared biased to the presence of sapling-stage conifer fuel on measures of CGF at the ground level. Thus, modeling efforts to calibrate SFD with satellite sensor data failed. Both CGF-based and FuelCalc-based field estimates of CBD yielded close unity with satellite-calibrated estimates, although substantial differences in data distributions existed. Estimates of CBD from the widest CGF zenith angle range (0 to 38°) correlated best with FuelCalc-based CBD estimates, while both resulted in maximum biomass values that exceeded those considered typical for the SNF. Model results from the narrowest zenith angle range (0 to 7°) produced estimates of CBD that were more in line with values considered typical. LANDFIRE’s estimates of CBD were weakly, but significantly (P = 0.05), correlated to both narrow- and wide-angle CGF-based estimates of CBD, but not with FuelCalc-based estimates. Conclusions The combined use of field estimates of CBD, based on indirect measures of CGF according to Keane et al. (Canadian Journal of Forest Research 35:724–739, 2005), with SAR and optical satellite sensor data demonstrates the potential of this method for mapping CBD in the Upper Midwest, USA. Results suggested that the presence of live, coniferous surface fuels neither confounds remote detection nor precludes mapping of CBD in this region using SAR satellite sensor data, as C- and L-band idiosyncrasies likely limit the visibility of these smaller understory fuels from space. Nevertheless, research using direct measures of burnable SFD for calibrations with SAR satellite sensor data should be conducted to more definitively answer this remote detection question, as we suspect substantial bias among measures of CGF from ground level when estimating SFD as the difference between TFD and CBD.

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“…Of these systems, we expected GM defoliation to be most intuitive and readily mapped via satellite sensor data due to GM's generalist broadleaf diet . We anticipated SBW defoliation to be the most challenging to map using satellite sensor data due to the combination of host's canopy position, multi-year needle longevity, and tree species diversity within the study region (Bhattarai et al, 2020;Thapa et al, 2020). Given these two remote detection extremes, we posited that JPBW defoliation detection would represent intermediate difficulty due to unique biophysical conditions of the jack pine host, including high host concentration, dominant vertical canopy position, and relatively short needle longevity compared to SBW.…”

Section: Defoliating Insects Have Pronounced Effects On Forest Health...mentioning

confidence: 99%

Spatio-temporal characterization of insect defoliation through landsat images

Thapa

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Effective modeling of forest susceptibility to defoliating insect outbreaks requires better understanding of outbreak dynamics, which includes detailed knowledge of the preand post-outbreak forest status as well as subsequent feedback mechanisms. In this paper, we strive to fill the forest status need by combining archived Landsat sensor data (pre-and post-outbreak) with different formats and dates of the U.S. Forest Service's Forest Inventory and Analysis (FIA) data (periodic [1970s, 1990s] and annual [2003][2004][2005][2006]). Specifically, we explore the utility of these FIA ground data for calibrating models of forest species and type abundance for mapping past forest composition in the Border Lakes Ecoregion (BLE) of Upper Midwest of the US. Model calibration results between Landsat reflectance and FIA ground data for both total forest basal area and balsam fir (Abies balsamea) relative basal area, a preferred host of the spruce budworm (SBW, Choristoneura fumiferana), were poor to moderate (R 2 adj 0.39 and 0.48, respectively). Results for aspen

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Reconstructing past forest composition and abundance by using archived Landsat and national forest inventory data

Abstract: Reconstructing past forest composition and abundance by using archived Reconstructing past forest composition and abundance by using archived Landsat and national forest inventory data Landsat and national forest inventory data

Cited by 11 publications

References 88 publications

Confronting the cycle synchronisation paradigm of defoliator outbreaks in space and time—Evidence from two systems in a mixed‐species forest landscape

Confronting the cycle synchronisation paradigm of defoliator outbreaks in space and time—Evidence from two systems in a mixed‐species forest landscape

Modeling sub-boreal forest canopy bulk density in Minnesota, USA, using synthetic aperture radar and optical satellite sensor data

Spatio-temporal characterization of insect defoliation through landsat images

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