Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States

Vanderhoof, Melanie K.; Hawbaker, Todd J.; Merriam, Kyle E.; Berryman, E.; Cattau, Megan E.

doi:10.1002/eap.2237

Cited by 23 publications

(24 citation statements)

References 104 publications

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“…We also want to highlight the influence that successional stages might have on assessments of vegetation response to climatic stability/variability as successional changes leading to more stable vegetation indices as stands mature and canopy gaps fill up. Previous studies have documented positive trends in NDVI that align with successional transitions from vegetation types and late‐successional self‐thinning (Fiore et al, 2020) and postfire recovery (Vanderhoof et al, 2021). In our study system, younger stands generally experienced an increase in NDVI and NDMI in the earlier years followed by a plateau, although this pattern was also present in some of the more mature stands (Figures S6 and S7).…”

Section: Discussionmentioning

confidence: 82%

Applying climate change refugia to forest management and old‐growth restoration

Pradhan

Ettinger

Case

et al. 2023

Global Change Biology

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Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of latesuccessional forests have prompted efforts to restore old-growth forest structure.One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old-growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old-growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old-growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches.

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Section: Discussionmentioning

confidence: 82%

Applying climate change refugia to forest management and old‐growth restoration

Pradhan

Ettinger

Case

et al. 2023

Global Change Biology

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“…Surprisingly, fire never appeared in our sets of top predictors. However, fire can radically change vegetation phenology, wherein its effects last for multiple years, depending on the fire severity and speed of recovery (Miller et al, 2013;Vermeire and Russell, 2018;Wood et al, 2019;Vanderhoof et al, 2020;Gemitzi and Koutsias, 2021;Wang et al, 2021). If fire resulted in a change in land-cover type, pixels would have shifted vegetation class (such as from forest to grassland) in our approach.…”

Section: Further Study and Limitationsmentioning

confidence: 99%

Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments

et al. 2022

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Ecological processes are complex, often exhibiting non-linear, interactive, or hierarchical relationships. Furthermore, models identifying drivers of phenology are constrained by uncertainty regarding predictors, interactions across scales, and legacy impacts of prior climate conditions. Nonetheless, measuring and modeling ecosystem processes such as phenology remains critical for management of ecological systems and the social systems they support. We used random forest models to assess which combination of climate, location, edaphic, vegetation composition, and disturbance variables best predict several phenological responses in three dominant land cover types in the U.S. Northwestern Great Plains (NWP). We derived phenological measures from the 25-year series of AVHRR satellite data and characterized climatic predictors (i.e., multiple moisture and/or temperature based variables) over seasonal and annual timeframes within the current year and up to 4 years prior. We found that antecedent conditions, from seasons to years before the current, were strongly associated with phenological measures, apparently mediating the responses of communities to current-year conditions. For example, at least one measure of antecedent-moisture availability [precipitation or vapor pressure deficit (VPD)] over multiple years was a key predictor of all productivity measures. Variables including longer-term lags or prior year sums, such as multi-year-cumulative moisture conditions of maximum VPD, were top predictors for start of season. Productivity measures were also associated with contextual variables such as soil characteristics and vegetation composition. Phenology is a key process that profoundly affects organism-environment relationships, spatio-temporal patterns in ecosystem structure and function, and other ecosystem dynamics. Phenology, however, is complex, and is mediated by lagged effects, interactions, and a diversity of potential drivers; nonetheless, the incorporation of antecedent conditions and contextual variables can improve models of phenology.

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“…From annual image composites, we extracted values from TM-equivalent bands 1-5, and 7, and calculated nine spectral indices sensitive to plant photosynthesis and foliar moisture content (Figure 2, Table 1). Because spectral indices from the winter season may help to isolate the signals of mortality and growth of evergreen conifers [67][68][69], we also developed annual composites of the Normalized Difference Vegetation Index (NDVI) from December 1 focal yr to April 1 focal yr+1 (Table 1; Supplementary Materials). To develop predictors of bark beetle activity from yearly time series of the selected spectral bands and indices, we used the GEE implementation of LandTrendr (Landsat-based detection of trends in disturbance and recovery), a temporal segmentation algorithm that partitions LTS into homogeneous periods of spectral increase, stability, and decline [62,63] (Figure 2).…”

Section: Data Sources-landsat Time Seriesmentioning

confidence: 99%

“…Finally, NDVI during the winter period was retained as a predictor in each of the final RF models, as opposed to summer NDVI, which had low predictive ability. Thus, winter imagery is a valuable resource for mapping the mortality and regrowth of evergreen conifers in temperate forests [67][68][69].…”

Section: Implications For Remotely Sensed Detection Of Tree Mortalitymentioning

confidence: 99%

Effects of Bark Beetle Outbreaks on Forest Landscape Pattern in the Southern Rocky Mountains, U.S.A.

et al. 2021

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Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a crucial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data and Random Forest (RF) models, to develop 30-m maps of the presence (i.e., any occurrence) and severity (i.e., cumulative percent basal area mortality) of beetle-caused tree mortality 1997–2019 in subalpine forests throughout the Southern Rocky Mountains, USA. Using resultant maps, we also quantified spatial patterns of cumulative tree mortality throughout the region, an important yet poorly understood concept in beetle-affected forests. RF models using LTS products to predict presence and severity performed well, with 80.3% correctly classified (Kappa = 0.61) and R2 = 0.68 (RMSE = 17.3), respectively. We found that ≥10,256 km2 of subalpine forest area (39.5% of the study area) was affected by bark beetles and 19.3% of the study area experienced ≥70% tree mortality over the twenty-three year period. Variograms indicated that severity was autocorrelated at scales < 250 km. Interestingly, cumulative patch-size distributions showed that areas with a near-total loss of the overstory canopy (i.e., ≥90% mortality) were relatively small (<0.24 km2) and isolated throughout the study area. Our findings help to inform an understanding of the variable effects of bark beetle outbreaks across complex forested regions and provide insight into patterns of disturbance legacies, landscape connectivity, and susceptibility to future disturbance.

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Tracking rates of postfire conifer regeneration vs. deciduous vegetation recovery across the western United States

Cited by 23 publications

References 104 publications

Applying climate change refugia to forest management and old‐growth restoration

Applying climate change refugia to forest management and old‐growth restoration

Antecedent climatic conditions spanning several years influence multiple land-surface phenology events in semi-arid environments

Effects of Bark Beetle Outbreaks on Forest Landscape Pattern in the Southern Rocky Mountains, U.S.A.

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