environmental changes
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Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental changes, noise, illumination, etc.), efficiently analyzing DTs has raised considerable challenges for the state-of-the-art approaches. For 20 years, many different techniques have been introduced to handle the above well-known issues for enhancing the performance. Those methods have shown valuable contributions, but the problems have been incompletely dealt with, particularly recognizing DTs on large-scale datasets. In this article, we present a comprehensive taxonomy of DT representation in order to purposefully give a thorough overview of the existing methods along with overall evaluations of their obtained performances. Accordingly, we arrange the methods into six canonical categories. Each of them is then taken in a brief presentation of its principal methodology stream and various related variants. The effectiveness levels of the state-of-the-art methods are then investigated and thoroughly discussed with respect to quantitative and qualitative evaluations in classifying DTs on benchmark datasets. Finally, we point out several potential applications and the remaining challenges that should be addressed in further directions. In comparison with two existing shallow DT surveys (i.e., the first one is out of date as it was made in 2005, while the newer one (published in 2016) is an inadequate overview), we believe that our proposed comprehensive taxonomy not only provides a better view of DT representation for the target readers but also stimulates future research activities.

Abstract Traditional medicine is cheaper and easily available to local people, to care for most frequent diseases in the Northern parts of Pakistan. Our study aimed at inventorying medicine from local plants, documenting their uses, and assessing their market value in 2015-2018 during spring, summer, and winter seasons. A total of 15 trips were made, 5 in each season. Semi-structured interviews with 165 inhabitant’s age range between 20-80 years were conducted, analyzed the data is analyzed using Relative frequency of citation(RFC), Use Value(UV), Fidelity Level(FL), Informants consensus factor(ICF), and Jaccard index(JI) to find the most frequent and well-known used species in the area. A total of 86 species belonging to 39 vascular plant families, 33 genera were documented as medicinally important. Family Asteraceae was observed as the dominant family among all the families with 10 species, the leaf was the most used parts and decoction 36% was the most preferred preparation type. Herb was the predominant life form (67%). The maximum UV (0.92) was demonstrated by J. adhatoda L. species, while A. sativum L. shows maximum RFC (0.58), the highest ICF value represented by diarrhea and dermatitis 0.92, and high FL value is recorded 100%. According to our collections, wild species were 45%, invasive species were 38% and cultivated 17% recorded, dicots species were recorded more 81%. Seven 7 medicinal species is being economically important and export to the local and international market of the world, whereas P. integrima L. species were the most exported species according to the local dealers. The investigated area is rural and the local people depend on the area's plants for their health needs, and other uses like a vegetable, fuelwood, fodder, etc. The current result of RFC, UV, ICF, FL, and JI shows that medicinal flora needs to be pharmacologically and phytochemically investigated to prove their efficacy. The documentation of medicinal knowledge is important to preserve this precious old knowledge before it is lost forever, due to technological and environmental changes in the world.

Many biological processes follow circadian rhythmicity and are controlled by the circadian clock. Predictable environmental changes such as seasonal variation in photoperiod can modulate circadian rhythms, allowing organisms to adjust to the time of the year. Modification of circadian clocks is especially relevant in crops to enhance their cultivability in specific regions by changing their sensibility to photoperiod. In tomato, the appearance of mutations in EMPFINDLICHER IM DUNKELROTEN LICHT 1 (EID1, Solyc09g075080) and NIGHT LIGHT-INDUCIBLE AND CLOCK-REGULATED GENE 2 (LNK2, Solyc01g068560) during domestication delayed its circadian rhythms, and allowed its expansion outside its equatorial origin. Here we study how variation in circadian rhythms in tomato affects its perception of photoperiod. To do this, we create near isogenic lines carrying combinations of wild alleles of EID1 and LNK2 and perform transcriptomic profiling under two different photoperiods. We observe that EID1, but not LNK2, has a large effect on the tomato transcriptome and its response to photoperiod. This large effect of EID1 is likely a consequence of the global phase shift elicited by this gene in tomato's circadian rhythms.

The mechanisms responsible for the development of various structural and functional features of the microbial food web (MFW) and their dynamics at spatial and temporal scales, which are important for predicting their responses to future environmental changes, are largely unknown. More than 3000 datasets of environmental and microbial variables collected over a decade on a seasonal and large spatial scale in the Adriatic Sea were analyzed. The sets of environmental variables were classified into four clusters (representing different environmental states) using Neural Gas analysis and the differences in MFW structure between the clusters were analyzed. Different variants of MFW evolve in the different clusters in terms of the abundance of MFW components, their ratios, growth and grazing rates, predator preference in prey selection, the strength of predator-prey interaction, and the relative importance of top-down and bottom-up control. However, these clusters are neither spatially nor temporally fixed; rather, the area studied represents a mosaic of different environmental conditions that alternate from one state to another on a time scale. In each of the environmental states, a distinct structure of MFW develops that shows consistent and repeatable changes that strictly follow the switching in environmental conditions from one state to another.

Trait-based analyses provide powerful tools for developing a generalizable, physiologically grounded understanding of how forest communities are responding to ongoing environmental changes. Key challenges lie in (1) selecting traits that best characterize the ecological performance of species in the community and (2) determining the degree and importance of intraspecific variability in those traits. Recent studies suggest that globally evident trait correlations (trait dimensions), such as the leaf economic spectrum, may be weak or absent at local scales. Moreover, trait-based analyses that utilize a mean value to represent a species may be misleading. Mean trait values are particularly problematic if species trait value rankings change along environmental gradients, resulting in species trait crossover. To assess how plant traits (1) covary at local spatial scales, (2) vary across the dominant environmental gradients, and (3) can be partitioned within and across taxa, we collected data on 9 traits for 13 tree species spanning the montane temperate—boreal forest ecotones of New York and northern New England. The primary dimension of the trait ordination was the leaf economic spectrum, with trait variability among species largely driven by differences between deciduous angiosperms and evergreen gymnosperms. A second dimension was related to variability in nitrogen to phosphorous levels and stem specific density. Levels of intraspecific trait variability differed considerably among traits, and was related to variation in light, climate, and tree developmental stage. However, trait rankings across species were generally conserved across these gradients and there was little evidence of species crossover. The persistence of the leaf economics spectrum in both temperate and high-elevation conifer forests suggests that ecological strategies of tree species are associated with trade-offs between resource acquisition and tolerance, and may be quantified with relatively few traits. Furthermore, the assumption that species may be represented with a single trait value may be warranted for some trait-based analyses provided traits were measured under similar light levels and climate conditions.

The northern Bering and Chukchi seas are biologically productive regions but, recently, unprecedented environmental changes have been reported. For investigating the dominant phytoplankton communities and relative contribution of small phytoplankton (<2 µm) to the total primary production in the regions, field measurements mainly for high-performance liquid chromatography (HPLC) and size-specific primary productivity were conducted in the northern Bering and Chukchi seas during summer 2016 (ARA07B) and 2017 (OS040). Diatoms and phaeocystis were dominant phytoplankton communities in 2016 whereas diatoms and Prasinophytes (Type 2) were dominant in 2017 and diatoms were found as major contributors for the small phytoplankton groups. For size-specific primary production, small phytoplankton contributed 38.0% (SD = ±19.9%) in 2016 whereas 25.0% (SD = ±12.8%) in 2017 to the total primary productivity. The small phytoplankton contribution observed in 2016 is comparable to those reported previously in the Chukchi Sea whereas the contribution in 2017 mainly in the northern Bering Sea is considerably lower than those in other arctic regions. Different biochemical compositions were distinct between small and large phytoplankton in this study, which is consistent with previous results. Significantly higher carbon (C) and nitrogen (N) contents per unit of chlorophyll-a, whereas lower C:N ratios were characteristics in small phytoplankton in comparison to large phytoplankton. Given these results, we could conclude that small phytoplankton synthesize nitrogen-rich particulate organic carbon which could be easily regenerated.

There is a high diversity of bees in the tropics, including honey bees and stingless bees, which are the main sources for honey and other ecosystem services. In Indonesia, beekeeping practices have been developed for centuries, and they have been part of many cultural practices in many traditional communities. The objective of this research was to study the beekeeping status and managed bee diversity in Indonesia and to investigate beekeepers’ perspectives on the factors and obstacles related to beekeeping. Direct interview and online interview were conducted to gain data on bees and beekeepers. In total, 272 beekeepers were interviewed across 25 provinces. Samplings of honey bees and stingless bees were also done during direct interviews for further identification and, when possible, pollen identification. All data and specimens were then sent to IPB Bogor for compilation and identification. We recorded 22 species of bees, including 3 species of honey bees and 19 species of stingless bees, that are reared by Indonesian beekeepers, with Apis cerana and Tetragonula laeviceps as the most common species. Our research also found that the majority of beekeepers fall into the category of the younger generation (30–39 years old) with educational background mostly from senior high school. Based on the beekeepers’ perspectives, there are several obstacles to beekeeping, especially the occurrence of death of bee foragers attributed to climate, food source, and pesticides. In conclusion, there is a need to develop a strategy for beekeeping and bee conservation in Indonesia, especially for adaptation and mitigation from environmental changes with a particular focus on climate and land-use change.

Environmental and land-use changes put severe pressure on wild plant habitats. The present study aims to assess the biodiversity of wild plant habitats and the associated spatiotemporal environmental changes in the coastal region of Dakahlia Governorate following an integrated approach of remote sensing, GIS, and samples analysis. Thirty-seven stands were spatially identified and studied to represent the different habitats of wild plants in the Deltaic Mediterranean coastline region. Physical and chemical characteristics of soil samples were examined, while TWINSPAN classification was used to identify plant communities. Two free Landsat images (TM and OLI) acquired in 1999 and 2019 were processed to assess changes via the production of land use and cover maps (LULC). Moreover, NDSI, NDMI, and NDSI indices were used to identify wild plant habitats. The floristic composition indicated the existence of 57 species, belonging to 51 genera of 20 families. The largest families were Asteraceae, Poaceae, and Chenopodiaceae. The classification of vegetation led to the identification of four groups. Canonical Correspondence Analysis (CCA) revealed that electrical conductivity, cations, organic carbon, porosity, chlorides, and bicarbonates are the most effective soil variables influencing vegetation. The results of the spectral analysis indicated an annual coverage of bare lands (3.56 km2), which is strongly related to the annual increase in vegetation (1.91 km2), water bodies (1.22 km2), and urban areas (0.43 km2). The expansion of urban and agricultural regions subsequently increased water bodies and caused occupancy of bare land, resulting in the development of wild plant habitats, which are mostly represented by the sparse vegetation class as evaluated by NDVI. The increase in mean moisture values (NDMI) from 0.03 in 1999 to 0.15 in 2019 might be explained by the increase in total areas of wild plant habitats throughout the study period (1999–2019). This may improve the adequacy of environments for wild habitats, causing natural plant proliferation.