Assessing performance of conservation-based Best Management Practices: Coarse vs. fine-scale analysis

Background/Questions/Methods
Animal agriculture in the Spring Creek watershed of central Pennsylvania contributes sediment to the stream and ultimately to the Chesapeake Bay. Best Management Practices (BMPs) such as stream bank buffers are intended to intercept sediment moving from heavy-use areas toward the stream. The placement of BMPs on a farm is generally based on untested assumptions about flow paths. Most often, a straight-line distance from the heavy-use area to the stream is assumed to be correct. Our objective was to compare the straight-line path to hydrologic flow paths calculated from fine-, medium- and coarse-grained Digital Elevation Models (DEMs; 1m, 10m, 30m) for 471 mapped heavy-use points within 100m of the stream. The 30m DEMs are the most widely available and require the least processing time. We anticipated that the flow path distance would be longer than the straight-line distance in all cases, that the finest resolution would lead to the most accurate measurement, but that the difference might not be great enough to justify the increased costs. Understanding the changes in path length and direction calculated using more complex methods and higher-resolution source data will enable us to make recommendations on methods to be used in developing conservation management plans.

Results/Conclusions
The medium-(10m DEM) and fine-resolution data (1m DEM) had the smallest differences between the hydrologic flow path and straight-line path: median differences in path length of 20 m for both the 1m and 10m DEMs, and 51m for the 30m DEM. Hydrologic flow paths were significantly longer than straight-line paths for all three scales; BMP placement based on straight-line distances may not be the most effective. Although the overall difference was significantly positive, calculations on the 30m DEMs sometimes produced straight-line paths that were longer than the hydrologic flow paths, apparently due to inaccuracies in the data. Where fine-scale DEMs are available, BMPs might be more effectively situated by considering the corresponding drainage pathways. The very different results produced at the three scales demonstrate that using the finest-grained elevation data may substantially improve placement of BMPs intended to mitigate for heavy animal use areas. The use of 30m DEMs for this purpose should be avoided. Fine-grained data such as 1m-resolution LiDAR-derived DEMs are available for Pennsylvania through PAMAP, and can be incorporated in the planning stages of BMP placement ultimately resulting in reducing agricultural sediment and nutrient loadings into local watersheds and the Chesapeake Bay

Predator traits determine food-web architecture across ecosystems

Predator–prey interactions in natural ecosystems generate complex food webs that have a simple universal body-size architecture where predators are systematically larger than their prey. Food-web theory shows that the highest predator–prey body-mass ratios found in natural food webs may be especially important because they create weak interactions with slow dynamics that stabilize communities against perturbations and maintain ecosystem functioning. Identifying these vital interactions in real communities typically requires arduous identification of interactions in complex food webs. Here, we overcome this obstacle by developing predator-trait models to predict average body-mass ratios based on a database comprising 290 food webs from freshwater, marine and terrestrial ecosystems across all continents. We analysed how species traits constrain body-size architecture by changing the slope of the predator–prey body-mass scaling. Across ecosystems, we found high body-mass ratios for predator groups with specific trait combinations including (1) small vertebrates and (2) large swimming or flying predators. Including the metabolic and movement types of predators increased the accuracy of predicting which species are engaged in high body-mass ratio interactions. We demonstrate that species traits explain striking patterns in the body-size architecture of natural food webs that underpin the stability and functioning of ecosystems, paving the way for community-level management of the most complex natural ecosystems

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification