rKIN: Kernel-based method for estimating isotopic niche size and overlap.

The isotopic niche of consumers represents biologically relevant information on resource and habitat use. Several tools have been developed to quantify niche size and overlap. Nonetheless, methods adapted by spatial ecologists to quantify animal home ranges can be modified for use in stable isotope ecology when data are not normally distributed in bivariate space. We offer a tool that draws on existing spatial metrics, such as minimum convex polygon (MCP) and standard ellipse area (SEA), and add novel metrics using kernel utilization density (KUD) estimators to measure isotopic niche size and overlap. We present examples using empirical and simulated data to demonstrate the performance of the package kernel isotopic niches in r (rKIN) under various scenarios. Results of niche size from MCP, SEA and KUD were highly correlated but divergent among datasets. Overall, the KUD method produced the largest niche sizes and was more sensitive to the distribution of the isotopic data. Pairwise estimates of overlap were highly variable, likely because MCP and SEA inherently include or exclude unused areas in the resulting niche estimate. Four bandwidth methods (reference, normal scale, plug-in and biased cross-validation) produced comparable estimates of niche size and overlap at various sample sizes (10-40). Niche size and overlap were consistent across sample sizes >15. Use of rKIN will allow isotope ecologists to quantify niche shifts, expansions or contractions, as well as assess the performance of several estimation methods. The package also can be applied to other data types (e.g. principal component analysis, multi-dimensional scaling) so long as axes and measurement units are identical and can be converted to Cartesian coordinates.

Adaptive Positron Emission Tomography Radiation Therapy in Patients With Locally Advanced Vulvar Cancer: A Prospective Study.

Purpose: In this prospective trial, we aim to determine whether fluorodeoxyglucose positron emission tomography and computed tomography (PET/CT)-based adaptive radiation therapy (ART) improves dosimetry outcomes for patients treated with definitive radiation for locally advanced vulvar cancer. Methods and Materials: Patients were enrolled in 2 sequential institutional review board-approved prospective protocols for PET/CT ART from 2012 to 2020. Patients were planned with pretreatment PET/CT to 45 to 56 Gy in 1.8 Gy/fraction, followed by a boost to gross disease (nodal and/or primary) to a total of 64 to 66 Gy. Intratreatment PET/CT was obtained at 30 to 36 Gy, and all patients were replanned to the same dose goals with revised organ at risk (OAR), gross tumor volume, and planned target volume contours. Radiation therapy consisted of either intensity modulated radiation therapy or volumetric modulated arc therapy. Toxicity was graded by Common Terminology Criteria for Adverse Events, version 5.0. Local control, disease-free survival, overall survival, and time to toxicity were estimated using the Kaplan-Meier method. Dosimetry metrics for OARs were compared using the Wilcoxon signed rank test. Results: Twenty patients were eligible for analysis. Median follow-up among surviving patients was 5.5 years. Local control, disease-free survival, and overall survival at 2 years were 63%, 43%, and 68%, respectively. ART significantly reduced the following OAR doses: bladder, maximum dose (Dmax; median reduction [MR], 1.1 Gy; interquartile range [IQR], 0.48-2.3 Gy; P < .001) and D2cc (MR, 1.5 Gy; IQR, 0.51-2.1 Gy; P < .001); bowel, Dmax (MR, 1.0 Gy; IQR, 0.11-2.9 Gy; P < .001), D2cc (MR, 0.39 Gy; IQR, 0.023-1.7 Gy; P < .001), and D15cc (MR, 0.19 Gy; IQR, 0.026-0.47 Gy; P = .002); and rectal, mean dose (MR, 0.66 Gy; IQR, 0.17-1.7 Gy; P = .006) and D2cc (MR, 0.46 Gy; IQR, 0.17-0.80 Gy; P = .006). No patients experienced any grade ≥3 acute toxicities. There were no reported late grade ≥2 vaginal toxicities. Lymphedema at 2 years was 17% (95% confidence interval, 0%-34%). Conclusions: Doses to bladder, bowel, and rectum were significantly improved with ART, though the median magnitudes were modest. Which patients benefit most from adaptive treatment is a matter for future investigation.

Functional and numerical responses of shrews to competition vary with mouse density.

For decades, ecologists have debated the importance of biotic interactions (e.g., competition) and abiotic factors in regulating populations. Competition can influence patterns of distribution, abundance, and resource use in many systems but remains difficult to measure. We quantified competition between two sympatric small mammals, Keen's mice (Peromyscus keeni) and dusky shrews (Sorex monticolus), in four habitat types on Prince of Wales Island in Southeast Alaska. We related shrew density to that of mice using standardized regression models while accounting for habitat variables in each year from 2010-2012, during which mice populations peaked (2011) and then crashed (2012). Additionally, we measured dietary overlap and segregation using stable isotope analysis and kernel utilization densities and estimated the change in whole community energy consumption among years. We observed an increase in densities of dusky shrews after mice populations crashed in 2012 as expected under competitive release. In addition, competition coefficients revealed that the influence of Keen's mice was dependent on their density. Also in 2012, shrew diets shifted, indicating that they were able to exploit resources previously used by mice. Nonetheless, increases in shrew numbers only partially compensated for the community energy consumption because, as insectivores, they are unlikely to utilize all food types consumed by their competitors. In pre-commercially thinned stands, which exhibit higher diversity of resources compared to other habitat types, shrew populations were less affected by changes in mice densities. These spatially and temporally variable interactions between unlikely competitors, observed in a relatively simple, high-latitude island ecosystem, highlight the difficulty in assessing the role of biotic factors in structuring communities.

Estimating leaf area index in Southeast Alaska: a comparison of two techniques.

The relationship between canopy structure and light transmission to the forest floor is of particular interest for studying the effects of succession, timber harvest, and silviculture prescriptions on understory plants and trees. Indirect measurements of leaf area index (LAI) estimated using gap fraction analysis with linear and hemispheric sensors have been commonly used to assess radiation interception by the canopy, although the two methods often yield inconsistent results. We compared simultaneously obtained measurements of LAI from a linear ceptometer and digital hemispheric photography in 21 forest stands on Prince of Wales Island, Alaska. We assessed the relationship between these estimates and allometric LAI based on tree diameter at breast height (LAIDBH). LAI values measured at 79 stations in thinned, un-thinned controls, old-growth and clearcut stands were highly correlated between the linear sensor (AccuPAR) and hemispheric photography, but the latter was more negatively biased compared to LAIDBH. In contrast, AccuPAR values were more similar to LAIDBH in all stands with basal area less than 30 m(2)ha(-1). Values produced by integrating hemispheric photographs over the zenith angles 0-75° (Ring 5) were highly correlated with those integrated over the zenith angles 0-60° (Ring 4), although the discrepancies between the two measures were significant. On average, the AccuPAR estimates were 53% higher than those derived from Ring 5, with most of the differences in closed canopy stands (unthinned controls and old-growth) and less so in clearcuts. Following typical patterns of canopy closure, AccuPAR LAI values were higher in dense control stands than in old-growth, whereas the opposite was derived from Ring 5 analyses. Based on our results we advocate the preferential use of linear sensors where canopy openness is low, canopies are tall, and leaf distributions are clumped and angles are variable, as is common in the conifer forests of coastal Alaska.