Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.     

Prion Strain Differences in Accumulation of PrPSc on Neurons and Glia Are Associated with Similar Expression Profiles of Neuroinflammatory Genes: Comparison of Three Prion Strains

Misfolding and aggregation of host proteins are important features of the pathogenesis of neurodegenerative diseases including Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia and prion diseases. In all these diseases, the misfolded protein increases in amount by a mechanism involving seeded polymerization. In prion diseases, host prion protein is misfolded to form a pathogenic protease-resistant form, PrPSc, which accumulates in neurons, astroglia and microglia in the CNS. Here using dual-staining immunohistochemistry, we compared the cell specificity of PrPSc accumulation at early preclinical times post-infection using three mouse scrapie strains that differ in brain regional pathology. PrPSc from each strain had a different pattern of cell specificity. Strain 22L was mainly associated with astroglia, whereas strain ME7 was mainly associated with neurons and neuropil. In thalamus and cortex, strain RML was similar to 22L, but in substantia nigra, RML was similar to ME7. Expression of 90 genes involved in neuroinflammation was studied quantitatively using mRNA from thalamus at preclinical times. Surprisingly, despite the cellular differences in PrPSc accumulation, the pattern of upregulated genes was similar for all three strains, and the small differences observed correlated with variations in the early disease tempo. Gene upregulation correlated with activation of both astroglia and microglia detected in early disease prior to vacuolar pathology or clinical signs. Interestingly, the profile of upregulated genes in scrapie differed markedly from that seen in two acute viral CNS diseases (LaCrosse virus and BE polytropic Friend retrovirus) that had reactive gliosis at levels similar to our prion-infected mice.     

Quantifying and Understanding Voltage Losses Due to Nonradiative Recombination in Bulk Heterojunction Organic Solar Cells with Low Energetic Offsets

Open‐circuit voltage (V_OC) losses in organic photovoltaics (OPVs) inhibit devices from reaching V_OC values comparable to the bandgap of the donor–acceptor blend. Specifically, nonradiative recombination losses (?V_nr) are much greater in OPVs than in silicon or perovskite solar cells, yet the origins of this are not fully understood. To understand what makes a system have high or low loss, an investigation of the nonradiative recombination losses in a total of nine blend systems is carried out. An apparent relationship is observed between the relative domain purity of six blends and the degree of nonradiative recombination loss, where films exhibiting relatively less pure domains show lower ?V_nr than films with higher domain purity. Additionally, it is shown that when paired with a fullerene acceptor, polymer donors which have bulky backbone units to inhibit close π–π stacking exhibit lower nonradiative recombination losses than in blends where the polymer can pack more closely. This work reports a strategy that ensures ?V_nr can be measured accurately and reports key observations on the relationship between ?V_nr and properties of the donor/acceptor interface.     

How are nitrogen availability,fine‐root mass,and nitrogen uptake related empirically? Implications for models and theory

Understanding the effects of global change in terrestrial communities requires an understanding of how limiting resources interact with plant traits to affect productivity. Here, we focus on nitrogen and ask whether plant community nitrogen uptake rate is determined (a) by nitrogen availability alone or (b) by the product of nitrogen availability and fine‐root mass. Surprisingly, this is not empirically resolved. We performed controlled microcosm experiments and reanalyzed published pot experiments and field data to determine the relationship between community‐level nitrogen uptake rate, nitrogen availability, and fine‐root mass for 46 unique combinations of species, nitrogen levels, and growing conditions. We found that plant community nitrogen uptake rate was unaffected by fine‐root mass in 63% of cases and saturated with fine‐root mass in 29% of cases (92% in total). In contrast, plant community nitrogen uptake rate was clearly affected by nitrogen availability. The results support the idea that although plants may over‐proliferate fine roots for individual‐level competition, it comes without an increase in community‐level nitrogen uptake. The results have implications for the mechanisms included in coupled carbon‐nitrogen terrestrial biosphere models (CN‐TBMs) and are consistent with CN‐TBMs that operate above the individual scale and omit fine‐root mass in equations of nitrogen uptake rate but inconsistent with the majority of CN‐TBMs, which operate above the individual scale and include fine‐root mass in equations of nitrogen uptake rate. For the much smaller number of CN‐TBMs that explicitly model individual‐based belowground competition for nitrogen, the results suggest that the relative (not absolute) fine‐root mass of competing individuals should be included in the equations that determine individual‐level nitrogen uptake rates. By providing empirical data to support the assumptions used in CN‐TBMs, we put their global climate change predictions on firmer ground.     

Colistin heteroresistance in Enterobacter cloacae is regulated by PhoPQ‐dependent 4‐amino‐4‐deoxy‐l‐arabinose addition to lipid A

The Enterobacter cloacae complex (ECC) consists of closely related bacteria commonly associated with the human microbiota. ECC are increasingly isolated from healthcare‐associated infections, demonstrating that these Enterobacteriaceae are emerging nosocomial pathogens. ECC can rapidly acquire multidrug resistance to conventional antibiotics. Cationic antimicrobial peptides (CAMPs) have served as therapeutic alternatives because they target the highly conserved lipid A component of the Gram‐negative outer membrane. Many Enterobacteriaceae fortify their outer membrane with cationic amine‐containing moieties to prevent CAMP binding, which can lead to cell lysis. The PmrAB two‐component system (TCS) directly activates 4‐amino‐4‐deoxy‐l ‐arabinose (l ‐Ara4N) biosynthesis to result in cationic amine moiety addition to lipid A in many Enterobacteriaceae such as E. coli and Salmonella. In contrast, PmrAB is dispensable for CAMP resistance in E. cloacae. Interestingly, some ECC clusters exhibit colistin heteroresistance, where a subpopulation of cells exhibit clinically significant resistance levels compared to the majority population. We demonstrate that E. cloacae lipid A is modified with l ‐Ara4N to induce CAMP heteroresistance and the regulatory mechanism is independent of the PmrAB_Ecl TCS. Instead, PhoP_Ecl binds to the arnB_Ecl promoter to induce l ‐Ara4N biosynthesis and PmrAB‐independent addition to the lipid A disaccharolipid. Therefore, PhoPQ_Ecl contributes to regulation of CAMP heteroresistance in some ECC clusters.     

Apps can help bridge restoration science and restoration practice

Scientists need to find innovative ways to communicate their findings with restoration practitioners in an era of global change. Apps are a promising bridge between restoration science and practice because they apply broad scientific concepts to specific situations. For example, habitat connectivity promotes ecological function, but practitioners lack ways to incorporate connectivity into decision‐making. We created an app where users calculate how habitat restoration or loss affects connectivity. By providing our app as an example and discussing the benefits and challenges in creating apps for practitioners, we encourage other restoration ecologists to similarly create apps that bridge science with practice.     

Global DNA methylation (LINE-1) associated with exposure to arsenic-contaminated environment and with type of arsenical skin lesions in Thailand

The effects of chronic arsenic exposure mode on DNA methylation and skin lesion type are unclear. These relationships were investigated in an arsenic-contaminated area of southern Thailand. Cases with arsenical skin lesions (n = 131) and lesion-free controls (n = 163) were selected from an arsenic-contaminated sub-district, as well as 105 controls from a non-contaminated area. Type and severity of skin lesions and salivary global DNA methylation (LINE-1) were determined. Arsenic exposure was characterized as occupational, domestic and current (toe-nail arsenic). Associations were explored using logistic regression. Cases and controls had lower LINE-1 methylation and higher toenail arsenic than external controls (74.65% and 74.61% vs 76.05%, p < 0.001 for each). Cases were more likely to have been exposed domestically (OR_total 1.76, 95% ci 1.00, 3.11; and 2.22, 95% ci 1.22, 4.03; P_trend = 0.005 for exposure <36 and ≥36 years). More severe spotty hyperpigmentation was related to higher LINE-1 methylation (P_trend=0.006). LINE-1 methylation was positively associated with toenail arsenic only among non-symptomatic exposed subjects (OR 1.31, 95% ci 1.06, 1.64; p = 0.014). Exposure to an arsenic-contaminated environment results in global DNA hypomethylation. However, among symptomatic subjects, increased global DNA methylation was associated with increased severity of spotty hyperpigmentation.     

Adapting Stand‐Alone Renewable Energy Technologies for the Circular Economy through Eco‐Design and Recycling

Renewable energy (RE) technologies are looked upon favorably to provide for future energy demands and reduce greenhouse gas (GHG) emissions. However, the installation of these technologies requires large quantities of finite material resources. We apply life cycle assessment to 100 years of electricity generation from three stand‐alone RE technologies—solar photovoltaics, run‐of‐river hydro, and wind—to evaluate environmental burden profiles against baseline electricity generation from fossil fuels. We then devised scenarios to incorporate circular economy (CE) improvements targeting hotspots in systems’ life cycle, specifically (1) improved recycling rates for raw materials and (ii) the application of eco‐design. Hydro presented the lowest environmental burdens per kilowatt‐hour of electricity generation compared with other RE technologies, owing to its higher efficiency and longer life spans for main components. Distinct results were observed in the environmental performance of each system based on the consideration of improved recycling rates and eco‐design. CE measures produced similar modest savings in already low GHG emissions burdens for each technology, while eco‐design specifically had the potential to provide significant savings in abiotic resource depletion. Further research to explore the full potential of CE measures for RE technologies will curtail the resource intensity of RE technologies required to mitigate climate change.     

Global patterns in fine root decomposition: climate,chemistry, mycorrhizal association and woodiness

Fine root decomposition constitutes a critical yet poorly understood flux of carbon and nutrients in terrestrial ecosystems. Here, we present the first large‐scale synthesis of species trait effects on the early stages of fine root decomposition at both global and local scales. Based on decomposition rates for 279 plant species across 105 studies and 176 sites, we found that mycorrhizal association and woodiness are the best categorical traits for predicting rates of fine root decomposition. Consistent positive effects of nitrogen and phosphorus concentrations and negative effects of lignin concentration emerged on decomposition rates within sites. Similar relationships were present across sites, along with positive effects of temperature and moisture. Calcium was not consistently related to decomposition rate at either scale. While the chemical drivers of fine root decomposition parallel those of leaf decomposition, our results indicate that the best plant functional groups for predicting fine root decomposition differ from those predicting leaf decomposition.     

Multi-patch deterministic and stochastic models for wildlife diseases

Spatial heterogeneity and host demography have a direct impact on the persistence or extinction of a disease. Natural or human-made landscape features such as forests, rivers, roads, and crops are important to the persistence of wildlife diseases. Rabies, hantaviruses, and plague are just a few examples of wildlife diseases where spatial patterns of infection have been observed. We formulate multi-patch deterministic and stochastic epidemic models and use these models to investigate problems related to disease persistence and extinction. We show in some special cases that a unique disease-free equilibrium exists. In these cases, a basic reproduction number ?(0) can be computed and shown to be bounded below and above by the minimum and maximum patch reproduction numbers ?(j), j=1, …, n. The basic reproduction number has a simple form when there is no movement or when all patches are identical or when the movement rate approaches infinity. Numerical examples of the deterministic and stochastic models illustrate the disease dynamics for different movement rates between three patches.