10 research outputs found
Teaching Critical Thinking in Statistics for Natural Resource Education
Graduate education in natural resource fields requires high level critical thinking in specialized areas of interest to the student. This challenge is typically embraced by graduate students who are excited to be learning in the areas of their choice. Most graduate programs in natural resources require students to take a course in statistics or data analysis and natural resources research relies heavily on these tools. But many students have limited experience with quantitative science and that experience may not have been recent. This poses a challenge when teaching courses in statistics. In this presentation I will outline the challenges to teaching and the barriers to learning that can be present for some students in natural resources. I will suggest some approaches to teaching statistics that have been successful in the classroom and outline how different kinds of learning activities can be used together to improve student learning of statistics
Spatial Patterns in Forest Understories: Relationships to Overstory Thinning Intensity and Understory Plant Diversity
Amount, spatial distribution, and species composition of understory plant communities have been shown to respond to changes in overstory structure. While response of the amount and composition of understory vegetation to thinning has been investigated in several ecosystems, spatial distributions have received less attention. We investigated spatial statistical techniques to examine associations of patch size of clonal shrubs and annual ruderals as they relate to overstory conditions after thinnings. We assessed the interpretation of empirical semivariograms in describing spatial pattern and whether semivariogram parameters can be useful when comparing impacts of different thinning regimes. We simulated vegetation patterns to test the ability of empirical semivariograms to describe patch sizes and suggest a nonparametric semivariogram range parameter as a metric of patch size. We applied results from the simulations to data from a long-term thinning study, in which intensity and spatial patterns of thinnings varied. We used range parameters from semivariograms of percent cover to compare response of patch sizes among thinning treatments and life forms. Initial results indicated that empirical semivariograms quantified both patch sizes and distance between patches. Nonparametric semivariogram estimates of patch size showed differences among thinning treatments, suggesting that spatial patterns of overstory conditions are influencing spatial distributions of understory vegetation. Patches of selected clonal shrubs were smallest in the treatment with spatially variable thinnings. Overall patch size of clonal shrubs was less strongly associated with thinning treatments than patch size of annual ruderals, likely reflecting differences in mobility between species that mainly regenerate by sprouting versus seeds. We conclude that spatial pattern of understory vegetation is responsive to thinning treatments and empirical semivariograms can provide useful information for developing silvicultural prescriptions
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Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA
Forest understory vegetation is influenced by broad-scale variation in climate, intermediate-scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%C[subscript U]) and multi-scale controls using a large-scale experiment including treatments of low (LS), moderate (MS) and variable (VS) disturbance severity replicated in second-growth Douglas-fir (Pseudotsuga meziesii)–western hemlock (Tsuga heterophylla) forests spanning climate and topographic gradients. We developed hierarchical models using a multi-step selection process, assessing changes residual spatial autocorrelation associated with progressively broader spatial scales of influence and interaction. To examine the role of plant traits in mediating multi-scale controls, we contrasted effects for early- (%C[subscript ES]) and late-seral (%C[subscript LS]) species cover. At neighborhood scales, decreases in %C[subscript U] with overstory density were accelerated with increases in the relative importance of hemlock in the overstory in the in all but the LS treatment. At intermediate scales, %C[subscript U] was lower in areas with higher potential radiation in undisturbed control treatments but that trend was reversed in the harvested, disturbed areas. When separated, effects of multi-scale controls differed between %C[subscript ES] and %C[subscript LS]. Rates of increases in %C[subscript ES] with reductions in density increased with disturbance severity and decreased with increases in %C[subscript LS]. At broader scales, %C[subscript ES] increased with climatic moisture deficit where potential radiation was high, and %C[subscript LS] low. Similarly to %C[subscript U], %C[subscript LS] was related to a three-way interaction between overstory density, disturbance and hemlock abundance. %C[subscript LS] declined with increases in climatic moisture deficit where overstory density and the relative abundance of hemlock was high, and decreased with local increases in %C[subscript ES]. Multi-scale controls explained a portion of the observed spatial autocorrelation for %C[subscript ES] but not %C[subscript LS], suggesting the spatial patterning of %C[subscript LS] is related primarily to unmeasured processes. Results show how understory responses to overstory density and disturbance severity vary across the landscape with moisture and potential radiation, at fine scales with neighborhood structure, and with species traits. Hence, understory responses to climate change likely depend on overstory composition and structure, disturbance and species traits
Designing long-term large-scale forestry experiments with research objectives at multiple scales
ABSTRACT. A number of large-scale manipulative studies (LSMEs) have been installed in recent decades. They were designed to test opera tionally practical silvicultural treatments on large tracts of forest land and over long periods of time. The interdisciplinary nature of LSMEs and the associated variety of research objectives provide special chal lenges in study design and implementation that usually do not occur in the setup of traditionally smaller-scaled research studies. We present and discuss these issues, including the development of a prioritized list of objectives with explicit spatial and temporal scales and clear defi nitions of the scope of inference for each objective. In this context we discuss the variation within large experimental units; the choice of replications; treatment definitions, including multiple manipulations over time; and the choice, scale, and timing of measurements. Above all, it appears that agreeing on a clear hierarchy of study objectives will prevent future conflicts between different study components and will provide guidance for the evaluation of treatment and measurement choices
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Salmonberry and salal annual aerial stem production: the maintenance of shrub cover in forest stands
Annual sprouting of aerial stems and ramets enables populations of salmonberry (Rubus spectabilis Pursh), salal (Gaultheria shallon Pursh), and probably other forest shrubs to maintain dense covers (>20 000 stems/ha). We studied annual stem production of salmonberry on cut (all stems cut within 15 cm of the ground) and uncut (stems were not treated) plots for 8 years and salal for 5 years in the understories of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), alder, and riparian stands, as well as clearcuts, which are all common stand types in western Oregon. Mean salmonberry stem production on uncut plots ranged from 4.7 stems·m–2·year–1 (95% CI 2.9–7.4) in alder stands
and clearcuts to 1.6 stems·m–2·year–1 (95% CI 1.0–2.6) in conifer stands. Mean salal production was greater, ranging from 58 stems·m–2·year–1 (95% CI 25–135) to 8.6 stems·m–2·year–1 (95% CI 3.7–20.1) on uncut plots in clearcuts and unthinned Douglas-fir stands, respectively. Annual production of both species was somewhat greater on cut plots. Most stems produced in early spring die by December, but enough are recruited to replace mortality of older stems. Stem density was maintained for 8 years for salmonberry and 5 years for salal on both cut and uncut plots. Based on length of rhizomes and bud density we estimate that only 1–5% of the buds in the rhizomes are needed to support this annual stem production. Although these species sprout vigorously after their aerial stems are killed, disturbance is not necessary for maintaining a dense cover. It appears that, once established, salal, salmonberry, and probably other clonal forest shrubs can maintain a dense cover that can interfere with establishment of trees and other shrubs in canopy gaps or
other openings
Genetic transformation: A powerful tool for dissection of adaptive traits in trees
Plant transformation and regeneration systems have become indispensable parts of gene discovery and functional characterization over the last two decades. Adoption of transformation methods in studies of plant adaptation to natural environments has been slow. This is a result of poor genomic knowledge and inefficient transformation systems for species dominating terrestrial ecosystems, and logistical difficulties in conducting field tests of genetically engineered organisms. In trees, where long generation cycles, high background polymorphism, large sizes and outcrossing systems of mating make production of near-isogenic lines and large experiments difficult, transformation is an attractive alternative for establishing direct linkages between genes and adaptively significant phenotypes. Here, we outline the capabilities, challenges, and prospects for transformation to become a significant tool for studying the ecophysiological adaptation of trees to the environment. Focusing on poplars (genus Populus) as model system, we describe how transformation-based approaches can provide insights into the genes that control adaptive traits. The availability of the poplar genome sequence, along with its large expressed sequences tag (EST) databanks, facile transformation and rapid growth, enable reverse genetic approaches to be used to test virtually any hypothesis of gene function. © New Phytologist (2005)
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The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire.
Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research