Evaluating the sensitivity of process domains for logjams to spatial and temporal sample size in river networks of the Southern Rockies, USA

Modification of river corridors, particularly deforestation and the removal of large wood, has greatly altered the abundance and influences of large wood on most rivers in the temperate latitudes. The conceptual framework of large wood process domains can assist in both directing research and facilitating large wood-related management and restoration in rivers. Large wood process domains are spatially or temporally distinct portions of a river network or region with distinct processes of wood recruitment, transport, and storage. Previous research has shown wood to be unevenly distributed across space and time. We use a dataset of logjam distribution density in 304 spatially distinct reaches of mountain streams in the Colorado Front Range, and up to 11 years of repeat measurements at some reaches, to (i) statistically evaluate whether a priori designated process domains for logjam distribution density are distinctly different and (ii) evaluate the sensitivity of process domain delineatio..., We analyzed data using R software and packages (R Core Team, 2022). Statistical differences between population medians were assessed with t-tests and the Wilcoxon Rank Sum test when data did not meet the assumptions of normality or equal variance. We used multivariate linear models to describe relationships between spatial characteristics and logjam storage. To select the best variables to describe logjam density, we used the MuMin package in R (Barton, 2018). We explored using a mixed model to reflect the nested nature of the data, but opted for simple regression models to more easily facilitate model iteration. Statistical tests were assessed at the α = 0.05 level for significance.

To address the influence of the number of reaches on the conclusions, we created subsets of the spatially extensive dataset by randomly resampling the complete spatial dataset (n = 304) to create subsets of data of different sample sizes. One hundred random subsamples of the complete spatial dataset were t..., # Data from: Evaluating the sensitivity of process domains for logjams to spatial and temporal sample size in river networks of the Southern Rockies, USA

Data describing logjam distribution density (number of jams per 100 m of channel length) for the Southern Rocky Mountains. Each reach was previously defined. Data were compiled from Beckman (2013), Jackson and Wohl (2015), Livers (2016), Triantafillou & Wohl (2024), Wohl and Beckman (2014), Wohl and Jaeger (2009), Wohl and Scamardo (2020), Wohl and Iskin (2022), and Wohl (unpublished data).

## Description of the data and file structure

spatial.csv: A csv with the spatially extensive data. Data cover 304 reaches from 38 catchments.

spatial_key.csv: A table with variable definitions associated with 'spatial.csv,' including category, variable name, units if applicable, description of methods, and format.

temporal.csv: A csv with the temporally extensive data. Data are from the North Saint Vrain catchment and its tributaries and cover...,