Stem‐mapped forest stands offer important opportunities for investigating the fine‐scale spatial processes occurring in forest ecosystems. These stands are areas of the forest where the precise locations and repeated size measurements of each tree are recorded, thereby enabling the calculation of spatially‐explicit metrics of individual growth rates and of the entire tree community. The most common use of these datasets is to investigate the drivers of variation in forest processes by modeling tree growth rate or mortality as a function of these neighborhood metrics. However, neighborhood metrics could also serve as important covariates of many other spatially variable forest processes, including seedling recruitment, herbivory and soil microbial community composition. Widespread use of stem‐mapped forest stand datasets is currently hampered by the lack of standardized, efficient and easy‐to‐use tools to calculate tree dynamics (e.g. growth, mortality) and the neighborhood metrics that impact them. We present the forestexplorR package that facilitates the munging, exploration, visualization and analysis of stem‐mapped forest stands. By providing flexible, user‐friendly functions that calculate neighborhood metrics and implement a recently‐developed rapid‐fitting tree growth and mortality model, forestexplorR broadens the accessibility of stem‐mapped forest stand data. We demonstrate the functionality of forestexplorR by using it to investigate how the species identity of neighboring trees influences the growth rates of three common tree species in Mt Rainier National Park, WA, USA. forestexplorR is designed to facilitate researchers to incorporate spatially‐explicit descriptions of tree communities in their studies and we expect this increased diversity of contributors to develop exciting new ways of using stem‐mapped forest stand data.
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Fine-scale spatial heterogeneity shapes compensatory responses of a subalpine forest to severe bark beetle outbreak
Context: Growth releases of individuals that survive disturbances are important compensatory response mechanisms that contribute to ecological resilience. However, the role of fine-scale spatial heterogeneity in shaping compensatory growth responses is poorly understood for many broad-scale disturbances. Objectives: We quantified how fine-scale spatial structure affects individual and aggregate tree growthleading up to and following a severe mountain pine beetle (MPB; Dendroctonus ponderosae) outbreak. We asked: (1) How does individual tree growth vary with tree- and neighborhood-scale characteristics? (2) How do within-stand aggregate growth and overstory recruitment vary with neighborhood-scale characteristics? Methods: We used a spatially explicit long-term monitoring dataset of a subalpine lodgepole pine (Pinus contorta var. latifolia) forest (in Colorado, USA) in which every tree ≥ 5 cm diameter was measured and mapped prior to (1989, 2004) and following (2018) a severe MPB outbreak (2003–2011). We used spatial regression to characterize drivers of growth. Results: Overall, we found strong evidence for post-outbreak compensatory responses across spatial scales. Neighborhood characteristics shaped both individual and aggregate growth, with the magnitude of growth strongly mediated by pre-outbreak neighborhood structure and neighborhood mortality. Variation in tree-scale growth, combined with the spatial arrangement of surviving trees, resulted in highly variable emergent patterns of aggregate growth and recruitment. Conclusion: Our findings highlight the importance of fine-scale landscape configuration in shaping forest resilience. Quantifying compensatory responses in a spatially explicit framework at different scales is critical for modeling post-disturbance forest dynamics, which is increasingly important as climate warms and forest disturbance regimes change.
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- Award ID(s):
- 1853520
- PAR ID:
- 10471096
- Publisher / Repository:
- Landscape Ecology
- Date Published:
- Journal Name:
- Landscape Ecology
- Volume:
- 38
- Issue:
- 1
- ISSN:
- 0921-2973
- Page Range / eLocation ID:
- 253 to 270
- Subject(s) / Keyword(s):
- Growth release Mountain pine beetle Spatial model Conifer forest Rocky Mountains Resilience
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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