Is the Effect of Forest Structure on Bird Diversity Modified by Forest Productivity?

Currently, the most common strategy when managing forests for biodiversity at the landscape scale is to maintain structural complexity within stands and provide a variety of seral stages across landscapes. Advances in ecological theory reveal that biodiversity at continental scales is strongly influenced by available energy (i.e., climate factors relating to heat and light and primary productivity). This paper explores how available energy and forest structural complexity may interact to drive biodiversity at a regional scale. We hypothesized that bird species richness exhibits a hump-shaped relationship with energy at the regional scale of the northwestern United States. As a result, we hypothesized that the relationship between energy and richness within a landscape is positive in energy-limited landscapes and flat or decreasing in energy-rich landscapes. Additionally, we hypothesized that structural complexity explains less of the variation in species richness in energy-limited environments and more in energy-rich environments and that the slope of the relationship between structural complexity and richness is greatest in energy-rich environments. We sampled bird communities and vegetation across seral stages and biophysical settings at each of five landscapes arrayed across a productivity gradient from the Pacific Coast to the Rocky Mountains within the five northwestern states of the contiguous United States. We analyzed the response of richness to structural complexity and energy covariates at each landscape. We found that (1) richness had a hump-shaped relationship with available energy across the northwestern United States, (2) the landscape-scale relationships between energy and richness were positive or hump shaped in energy-limited locations and were flat or negative in energy-rich locations, (3) forest structural complexity explained more of the variation in bird species richness in energy-rich landscapes, and (4) the slope of the relationship between forest structural complexity and richness was steepest in energy-limited locations. In energy-rich locations, forest managers will likely increase landscape-scale bird diversity by providing a range of forest structural complexity across all seral stages. In low-energy environments, bird diversity will likely be maximized by managing local high-energy hotspots judiciously and adjusting harvest intensities in other locations to compensate for slower regeneration rates

A comparison of Power Doppler with conventional sonographic imaging for the evaluation of renal artery stenosis

BACKGROUND: Power Doppler (PD) has improved diagnostic capabilities of vascular sonography, mainly because it is independent from the angle of insonation. We evaluated this technique in a prospective comparison with conventional imaging, consisting in Duplex and Color Doppler, for the evaluation of Renal Artery (RA) stenosis. METHODS: Sensitivity, specificity and predictive values of PD and conventional imaging were assessed in a blinded fashion on eighteen patients, 9 with angiographic evidence of unilateral RA stenosis (hypertensive patients) and 9 with angiographically normal arteries (control group). PD images were interpreted with an angiography-like criteria. RESULTS: In the control group both techniques allowed correct visualization of 16 out of the 18 normal arteries (93% specificity). Only in five hypertensive patients RA stenosis was correctly identified with conventional technique (56% sensitivity and 86% negative predictive value); PD was successful in all hypertensive patients (100% sensitivity and negative predictive value), since the operators could obtain in each case of RA stenosis a sharp color signal of the whole vessel with a clear "minus" at the point of narrowing of the lumen. All results were statistically significant (p < 0.01). CONCLUSIONS: This study demonstrates that PD is superior to conventional imaging, in terms of sensitivity and specificity, for the diagnosis of RA stenosis, because it allows a clear visualization of the whole stenotic vascular lumen. Especially if it is used in concert with the other sonographic techniques, PD can enable a more accurate imaging of renovascular disease with results that seem comparable to selective angiography

Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data

Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a

Number of individuals captured for each of 21 small mammal species captured >1 time in 50 clearcut treatment stands with retention and nine rotation-aged forests, northwest Oregon and southwest Washington, USA, 2017–2019.

(DOCX)</p

Black-backed Woodpecker occupancy is extensive in green conifer forests of the southern Cascade Mountains, Oregon

Black-backed Woodpeckers (Picoides arcticus) are widely considered a burned forest specialist across much of their range. Several recent studies have examined their occurrence in "green" coniferous forests that have not been recently burned, but Black-backed Woodpecker occupancy and factors influencing occupancy in these forest types remain largely unexamined. We worked on the east slope of the southern Oregon Cascade Mountains and used playback call surveys with repeated visits to 90 transects in 2014 and 2015 to estimate occupancy probabilities by forest type while controlling for detection probability. We detected Black-backed Woodpeckers on 86% of survey transects in green forests composed primarily of mixed conifer, lodgepole pine (Pinus contorta), or ponderosa pine (P. ponderosa). We examined associations between occupancy probability and structural covariates in unburned forests, and found that occupancy did not vary with annual precipitation, large snag density, or snag basal area. Modeled mean occupancy across all transects was 0.87 (95% CI: 0.78-0.93). Detection probability varied during each survey season, with transect-level detection probability reaching a maximum of 0.79 (95% CI: 0.70-0.85) in mid-June. Given high occupancy of green forests by Black-backed Woodpecker in our study area, we suggest that additional study of vital rates in green forests is critical for supporting conservation and management decisions for this species

Coefficient estimates and 95% confidence intervals from linear mixed effects models (Gaussian response) predicting small mammal species and functional richness by structural retention treatment with a treatment by sampling year interaction, northwest Oregon and southwest Washington, USA, 2017–2019.

Reference treatment for all models is Riparian Aggregate (RA). (DOCX)</p

Code used to fit community occupancy model in JAGS to small mammal detection data and create Fig 4.

Results of goodness-of-fit test and plot of percent confidence in species detection. (DOCX)</p

S1 Fig -

Aerial photos depicting the arrangements of live-trapping grids (white crosses) within the different treatment types: (a) Upland Aggregated, (b) Riparian Aggregated, (c) Split, and (d) Dispersed with snags, northwest Oregon and southwest Washington, USA, 2017–2019. Sampling in the Split with Snags treatment was identical to sampling in the Split treatment. Minor differences in the configuration of grids placed in retention patches due to patch shape is apparent in panels (c) and (d). (DOCX)</p

S4 Fig -

Effect size (dots) and 95% confidence intervals (horizontal lines) for random intercepts estimated for each experimental treatment stand (a and c) and experimental block (b and d) for species richness (a and b) and functional richness (b and d) from the stand-scale models, northwest Oregon and southwest Washington, USA, 2017–2019. (DOCX)</p