Agriculturally Intensified Landscapes Are Associated With Reduced Body Condition of Lady Beetles

Context: Agricultural intensification is contributing to a global species decline. Underlying mechanisms include toxic effects of pesticides on non-target organisms and reductions in habitat and food availability. However, the effects of agricultural intensification on body condition, particularly of ecosystem service providing arthropods, are poorly understood.Objectives: Here, we investigated whether variations in the body condition of common lady beetle species (Coleoptera: Coccinellidae) can be explained by the composition and configuration of the surrounding landscape. Assuming strong seasonal variation in food availability in intensively farmed regions, we included the entire period of lady beetle activity in our study.Methods: Lady beetles were collected from April to September 2011 in 30 landscapes in southern Wisconsin, USA. We examined how body size, body density, and lipid content of the beetles responded to the percentage of intensive cropland, habitat diversity, and edge density in the surrounding landscape.Results: The strongest predictor of body condition was the percentage of intensive cropland. For every 10% increase in cropland, body density decreased by about 3.9% and fat content by 6.4%. Landscape diversity and edge density correlated with body condition of individual species.Conclusions: In agriculturally intensified landscapes, lady beetles with reduced body condition may produce fewer offspring, have lower survival rates, and exert less effective pest control. Thus, our results suggest a mechanistic link between landscape patterns and observed declines in lady beetle populations. Our results also show that the expansion of monocultures affects even common cropland-associated species such as Harmonia axyridis, suggesting a long-term decline in biocontrol services in simplified agricultural landscapes.

Pattern Avoidance Over a Hypergraph

A classic result of Marcus and Tardos (previously known as the Stanley-Wilf conjecture) bounds from above the number of $n$-permutations ($\sigma \in S_n$) that do not contain a specific sub-permutation. In particular, it states that for any fixed permutation $\pi$, the number of $n$-permutations that avoid $\pi$ is at most exponential in $n$. In this paper, we generalize this result. We bound the number of avoidant $n$-permutations even if they only have to avoid $\pi$ at specific indices. We consider a $k$-uniform hypergraph $\Lambda$ on $n$ vertices and count the $n$-permutations that avoid $\pi$ at the indices corresponding to the edges of $\Lambda$. We analyze both the random and deterministic hypergraph cases. This problem was originally proposed by Asaf Ferber. When $\Lambda$ is a random hypergraph with edge density $\alpha$, we show that the expected number of $\Lambda$-avoiding $n$-permutations is bounded (both upper and lower) as $\exp(O(n))\alpha^{-\frac{n}{k-1}}$, using a supersaturation version of F\"{u}redi-Hajnal. In the deterministic case we show that, for $\Lambda$ containing many size $L$ cliques, the number of $\Lambda$-avoiding $n$-permutations is $O\left(\frac{n\log^{2+\epsilon}n}{L}\right)^n$, giving a nontrivial bound with $L$ polynomial in $n$. Our main tool in the analysis of this deterministic case is the new and revolutionary hypergraph containers method, developed in papers of Balogh-Morris-Samotij and Saxton-Thomason.

Quantifying Landscape Degradation Following Construction of a Highway Using Landscape Metrics in Southern Iran

Rapid expansion of roads is among the strongest drivers of the loss and degradation of natural habitats. The goal of the present study is to quantify landscape fragmentation and degradation before and after the construction of the Isfahan-Shiraz highway in southern Iran. To this end, the ecological impacts of the highway on forests, rangelands, and protected areas were evaluated. Impacts of the construction of the highway were studied within a 1,000-m buffer around the road, which was then overlaid on maps of forests, rangelands, and protected areas. Class area, number of patches, largest patch index, edge density, landscape shape index, mean patch size, and patch cohesion index were used to gauge changes in the spatial configuration of the landscape; the ecological impacts of the highway were quantified using effective mesh size (MESH), division index, and splitting index. The results indicated that after the construction of the highway, 6,406.9 ha of forest habitat, 16,647.1 ha of rangeland habitat, and 912 of the Tang-e Bostanak Protected Area will be lost. The effective MESH metric showed that after the construction of the highway, the area of forest, rangeland habitats and protected area will decrease by 20,537, 49,149, and 71,822 ha, respectively. Our findings revealed drastic habitat loss and landscape fragmentation associated with construction of the highway, serving as references for conservation planning and development.

A novel measurement of marginal Alfvén Eigenmode stability during high power auxiliary heating in JET

The interaction of Alfvén Eigenmodes (AEs) and energetic particles is one of many important factors determining the success of future tokamaks. In JET, eight in-vessel antennas were installed to actively probe stable AEs with frequencies ranging 25-250 kHz and toroidal mode numbers |n| < 20. During the 2019-2020 deuterium campaign, almost 7500 resonances and their frequencies f, net damping rates γ < 0, and toroidal mode numbers were measured in almost 800 plasma discharges. From a statistical analysis of this database, continuum and radiative damping are inferred to increase with edge safety factor, edge magnetic shear, and when including non-ideal effects. Both stable AE observations and their associated damping rates are found to decrease with |n|. Active antenna excitation is also found to be ineffective in H-mode as opposed to L-mode; this is likely due to the increased edge density gradient's effect on accessibility and ELM-related noise's impact on mode identification. A novel measurement is reported of a marginally stable, edge-localized Ellipticity-induced AE probed by the antennas during high-power auxiliary heating (ICRH and NBI) up to 25 MW. NOVA-K kinetic-MHD simulations show good agreement with experimental measurements of f, γ, and n, indicating the dominance of continuum and electron Landau damping in this case. Similar experimental and computational studies are planned for the recent hydrogen and ongoing tritium campaigns, in preparation for the upcoming DT campaign.

Long-Term Land Use and Landscape Pattern Changes in a Marshland of Hungary

This paper presents the trends of landscape change in the marshes on the southern shore of Lake Balaton, a wetland profoundly transformed by human activities. The study does not only deal with alterations in the areal proportions of land use classes but also quantitatively analyses landscape pattern, comparing landscape metrics on different dates. Based on the findings, proposals for rehabilitation are made. Through the restoration of wetland habitats, the provision level of ecosystem services can be raised. Landscape change was investigated from 1783 to 2020. For this purpose, archive maps were digitized, CORINE land cover datasets corrected by Sentinel-2 imagery were employed and from the vector data, the proportions of land use classes were calculated. For landscape pattern perimeter, area, neighbourhood and diversity metrics were used, calculated by ArcGIS vLATE plugin. It was pointed out that in land cover, the share of wetlands considerably declined over the centuries but in recent decades somewhat expanded. In the 20th century, grasslands were the predominant land use class, but with the spread of other categories, land use has become more complex. Landscape metrics show an increased fragmentation of natural habitats, a higher number of patches and edge density, leading to higher landscape diversity. Rehabilitation proposals include the establishment of rainwater retention reservoirs, the conversion of arable land which cannot be cultivated profitably to close-to-natural classes (first of all, grasslands) and the plantation of gallery forests of native tree species along canals. In comparison with other regions, similar temporal trends and spatial distributions are observed. For instance, the internationally well-known transformation of the Doñana wetland started later but was more intensive than in Hungary.

Quantifying how urban landscape heterogeneity affects land surface temperature at multiple scales

Background Landscape metrics have been widely applied to quantifying the relationship between land surface temperature and urban spatial patterns and have received acceptable verification from landscape ecologists but some studies have shown their inaccurate results. The objective of the study is to compare landscape metrics and texture-based measures as alternative indices in measuring urban heterogeneity effects on LST at multiple scales. Results The statistical results showed that the correlation between urban landscape heterogeneity and LST increased as the spatial extent (scale) of under-study landscapes increased. Overall, landscape metrics showed that the less fragmented, the more complex, larger, and the higher number of patches, the lower LST. The most significant relationship was seen between edge density (ED) and LST (r = − 0.47) at the sub-region scale. Texture measures showed a stronger relationship (R2 = 34.84% on average) with LST than landscape metrics (R2 = 15.33% on average) at all spatial scales, meaning that these measures had a greater ability to describe landscape heterogeneity than the landscape metrics. Conclusion This study suggests alternative measures for overcoming landscape metrics shortcomings in estimating the effects of landscape heterogeneity on LST variations and gives land managers and urban planners new insights into urban design.

THE COMPARISON OF TWO TYPES COMPOSITE RESIN PACKABLE NANOHYBRID WITH TOTAL ETCH BONDING IN CLASS V RESTORATION MICROLEAKAGE

At dental clinic, there are some obstacles which occasionally may occur. A dentist runs out of the same brand of the composite resin and bonding material during tooth restoration, so they would have to be paired with material of the diffrent brand. Certain things that may occur during tooth restoration is polymerization shrinkage which forms a gap that could reducing edge density. This research is using packable nanohybrid type A composite resin and packable nanohybrid type B resin composite with total etch bonding on Class V restoration with the thin cervical section of enamel. Aim: This research is to explain the differences between two types of packable nanohybrid composite resins with total etch bonding in Class V microleakage. Methods: This research will use an experimental laboratory method with 32 maxillary premolars that have been prepared in Class V, which divided into 2 groups, group A and group B. Methylene blue will be used for the measurements, whereas the microscope will be used for the observation. Furthermore, data analysis would be conducted using the Mann Whitney U Test Method. Results: The research showed that there was a significant difference between group A and group B, which is p <0.05. Conclusion: According to this research, it can be seen that group B showed less leakage compared to group A.

Explaining classification performance and bias via network structure and sampling technique

Social networks are very important carriers of information. For instance, the political leaning of our friends can serve as a proxy to identify our own political preferences. This explanatory power is leveraged in many scenarios ranging from business decision-making to scientific research to infer missing attributes using machine learning. However, factors affecting the performance and the direction of bias of these algorithms are not well understood. To this end, we systematically study how structural properties of the network and the training sample influence the results of collective classification. Our main findings show that (i) mean classification performance can empirically and analytically be predicted by structural properties such as homophily, class balance, edge density and sample size, (ii) small training samples are enough for heterophilic networks to achieve high and unbiased classification performance, even with imperfect model estimates, (iii) homophilic networks are more prone to bias issues and low performance when group size differences increase, (iv) when sampling budgets are small, partial crawls achieve the most accurate model estimates, and degree sampling achieves the highest overall performance. Our findings help practitioners to better understand and evaluate their results when sampling budgets are small or when no ground-truth is available.