Assessing the Performance of Sampling Designs for Measuring the Abundance of Understory Plants

Accurate estimation of responses of understory plants to disturbance is essential for understanding the efficacy of management activities. However, the ability to assess changes in the abundance of plants may be hampered by inappropriate sampling methodologies. Conventional methods for sampling understory plants may be precise for common species but may fail to adequately characterize abundance of less common species. We tested conventional (modified Whittaker plots and Daubenmire and point–line intercept transects) and novel (strip adaptive cluster sampling [SACS]) approaches to sampling understory plants to determine their efficacy for quantifying abundance on control and thinned-and-burned treatment units in Pinus ponderosa forests in western Montana, USA. For species grouped by growth-form and for common species, all three conventional designs were capable of estimating cover with a 50% relative margin of error with reasonable sample sizes (3–36 replicates for growth-form groups; 8–14 replicates for common species); however, increasing precision to 25% relative margin of error required sample sizes that may be infeasible (11–143 replicates for growth-form groups; 28–54 replicates for common species). All three conventional designs required enormous sample sizes to estimate cover of nonnative species as a group (29–60 replicates) and of individual less common species (62–118 replicates), even with a 50% relative margin of error. SACS was the only design that efficiently sampled less common species, requiring only 6–11% as many replicates relative to conventional designs. Conventional designs may not be effective for estimating abundance of the majority of forest understory plants, which are typically patchily distributed with low abundance, or of newly establishing nonnative plants. Novel methods such as SACS should be considered in investigations when cover of these species is of concern

The Topographic Signature of Ecosystem Climate Sensitivity in the Western United States

It has been suggested that hillslope topography can produce hydrologic refugia, sites where ecosystem productivity is relatively insensitive to climate variation. However, the ecological impacts and spatial distribution of these sites are poorly resolved across gradients in climate. We quantified the response of ecosystem net primary productivity to changes in the annual climatic water balance for 30 years using pixel‐specific linear regression (30‐m resolution) across the western United States. The standardized slopes of these models represent ecosystem climate sensitivity and provide a means to identify drought‐resistant ecosystems. Productive and resistant ecosystems were most frequent in convergent hillslope positions, especially in semiarid climates. Ecosystems in divergent positions were moderately resistant to climate variability, but less productive relative to convergent positions. This topographic effect was significantly dampened in hygric and xeric climates. In aggregate, spatial patterns of ecosystem sensitivity can be implemented for regional planning to maximize conservation in landscapes more resistant to perturbations

Mitigating the Impact of Field and Image Registration Errors through Spatial Aggregation

Remotely sensed data are commonly used as predictor variables in spatially explicit models depicting landscape characteristics of interest (response) across broad extents, at relatively fine resolution. To create these models, variables are spatially registered to a known coordinate system and used to link responses with predictor variable values. Inherently, this linking process introduces measurement error into the response and predictors, which in the latter case causes attenuation bias. Through simulations, our findings indicate that the spatial correlation of response and predictor variables and their corresponding spatial registration (co-registration) errors can have a substantial impact on the bias and accuracy of linear models. Additionally, in this study we evaluate spatial aggregation as a mechanism to minimize the impact of co-registration errors, assess the impact of subsampling within the extent of sample units, and provide a technique that can be used to both determine the extent of an observational unit needed to minimize the impact of co-registration and quantify the amount of error potentially introduced into predictive models

Vertical distribution of foliar biomass in western larch (Larix occidentals Nutt.)

Western larch (Larix occidentalis Nutt.) is an endemic pioneer species in Northwest North America and unique as a deciduous conifer and the most shade-intolerant, fastest-growing, and most fire-resistant species in the Northwest United States. To better understand its production ecology, we used a multilevel modeling approach to analyze the intrinsic dynamics of western larch vertical foliage distribution and compared it with other species. We found western larch allocates foliage into a more diffuse distribution as the crown lengthens, whereas shade-tolerant evergreens concentrate foliage into a more monolayered distribution higher within the crown as it lengthens. Crown foliar biomass scaled linearly with DBH, indicating western larch does not fill volume in the crown with foliage at an increasing rate like other conifers. Our model supports the hypothesis that foliar shade-intolerance and water stress jointly influence foliage allocation in this deciduous conifer. These results also highlight intrinsic foliage distribution as a factor potentially contributing to the inability of western larch to survive light-limiting conditions and its preference for mesic sites. The models developed here provide a basic framework that may be built upon to study the morphological response of western larch to modified stand conditions such as disturbance and silvicultural treatment.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Long-term precommercial thinning effects on Larix occidentalis (western larch) tree and stand characteristics

Precommercial thinning (PCT) is used to increase tree size and shorten harvest rotation time. Short-term results from PCT studies often show a trade-off between individual tree growth and net stand yield, while longer-term effects of PCT on tree growth and stand yield are less well documented. We used a 54-year old PCT study to test long-term effects of forest density and thinning schedules on stand yield and tree-level characteristics in even-aged Larix occidentalis (western larch) stands. The study has three target densities (494 trees haThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Critical analyses when modeling tree biomass to ensure additivity of its components

ABSTRACT It is presented the theme additivity of biomass of tree components. To evaluate and discuss this context, experimental information collected in forests of Acacia mearnsii De Wild. was used. Equations for components (stem and crown) and total biomass were fitted by means of two procedures: 1) generalized nonlinear least squares and 2) weighted-nonlinear seemingly unrelated regressions. Analyzing the performance of the estimators, it can be concluded that the two tested procedures are equivalent. On the other hand, this conclusion differs when evaluated the consistency and efficiency of the estimators. Fitting equations for the components and for the total biomass by an independent way is not realistic, because from a biological point of view the estimates of biomass are inconsistent, i.e., are not additive. The biomass estimates of the components and of the total, resulting from equations adjusted by means of systems of equations, provided narrower confidence intervals in relation to the equations adjusted independently, and is therefore more efficient. The second procedure presents better biological properties and statistics to estimate allometric equations for biomass of the components and for the total when compared with the independent estimation, thus it should be the method to be used

Dataset for the article: The topographic signature of ecosystem climate sensitivities in the western U.S.

The associated article for this dataset is currently under review. It has been suggested that hillslope topography can promote the persistence of hydrologic refugia, sites where ecosystem net primary productivity is relatively insensitive to climate variation. However, the mechanisms that promote the persistence of these locations and their spatial distributions are poorly resolved. We quantified the response of ecosystem NPP to variability in the annual climatic water balance for 30 years across the western U.S. The slope of this pixel-specific linear regression represents ecosystem-climate sensitivity and provides a means to identify ecosystems that are buffered from droughts. Environmental conditions produced by hillslope convergence significantly reduced ecosystem sensitivity to climate fluctuations across the entirety of the western U.S. We observed the greatest topographic effect in semi-arid climates, while vulnerability to drought was maximized in flat, arid landscapes. In aggregate, spatial patterns of ecosystem sensitivity can be implemented for regional planning to maximize conservation in landscapes that are more resistant to perturbations. Geographic location: Western U.S., all data is in Albers Equal Area Projection; Datum NAD83; 30.37591m resolution Associated data and attachments can be found at: https://doi.org/10.5281/zenodo.3367490 (In addition, File #1 is available via the Download button above, and Files #2 and #3 are available below.): 1.) Mean annual climatic water deficit (potential evapotranspiration - actual evapotranspiration) for 1986-2015, more information available at: Holden, Z. A., Jolly, W. M., Swanson, A., Warren, D. A., Jencso, K., Maneta, M., ... & Landguth, E. L. (2019). TOPOFIRE: A topographically resolved wildfire danger and drought monitoring system for the conterminous United States. Bulletin of the American Meteorological Society, (2019). [Deficit_30m_Masked.tif] 2.) The topographic position index calcaulted using a 1000m radius, more information available at Weiss, A. (2001, July). Topographic position and landforms analysis. In Poster presentation, ESRI user conference, San Diego, CA (Vol. 200). [TPI_30m_1000m_Radius_Masked.tif] 3.) The standardized slope (ecosystem sensitivity) of the NPP ~ Deficit regressions, more information available in the article in review