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In 1855, as a result of decades of controversy, the Smithfield Livestock Market was relocated from the historic center of London to Islington in north London. Taking on board post-humanist critique...

Introduction The objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally been studied in-depth. The central question of this study is how the combination of cattle and sheep movements affects the potential for disease spread on the combined network. Materials and methods Our analysis considers static and temporal representations of networks based on recorded animal movements. We computed network-based node importance measures of two single-species networks, and compared the top-ranked premises with the ones in the multi-species network. We propose the use of a measure based on contact chains calculated in a network weighted with transmission probabilities to assess the importance of premises in an outbreak. To ground our investigation in infectious disease epidemiology, we compared this suggested measure with the results of disease simulation models with asymmetric probabilities of transmission between species. Results Our analysis of the temporal networks shows that the premises which are likely to drive the epidemic in this multi-species network differ from the ones in both the cattle and the sheep networks. Although sheep movements are highly seasonal, the estimated size of an epidemic is significantly larger in the multi-species network than in the cattle network, independently of the period of the year. Finally, we demonstrate that a measure based on contact chains allow us to identify around 30% of the key farms in a simulated epidemic, ignoring markets, whilst static network measures identify less than 10% of these farms. Conclusion Our results ascertain the importance of combining species networks, as well as considering layers of temporal livestock movements in detail for the study of disease spread.

While there is increasing evidence of the sustainability benefits of diversified systems in the organic cropping sector, this has been much less investigated with organic livestock farming. To fill this knowledge gap, we surveyed a sample of 128 European organic multi-species livestock farms located across seven countries – Austria, Belgium, France, Germany, Italy, Sweden and Switzerland – and covering a large range of livestock species combinations. We recorded 1574 variables as raw data out of which we calculated 107 indicators describing farm structure, management and several sustainability dimensions: resource use efficiency and conservation, animal, land and work productivities, animal and human welfare. After technical validation of the data, we withdrew 26 farms and the database covers 102 farms. This database is well suited to unveil relationships between various dimensions of organic multi-species livestock farm sustainability and their structure and management. It can help reveal sustainable strategies for organic multi-species livestock farming systems and understand levers or barriers to their development.

We use the General Equilibrium Ecosystem Model (GEEM) parameterized to Wyoming sagebrush to explore the impact of two common simplifications in bio-economic policy frameworks on species conservation decisions. First, we compare conservation policies based on 2-species food web models to those based on a more complex food web. We find that using the simpler model can miss opportunities for more conservation benefits in the presence of species interactions. Second, we define the impact of species dispersal costs on population distributions in a heterogenous landscape and explore conservation policies to reduce those costs to enable species to move away from disturbed areas. Conservation actions that reduce dispersal costs for all species reflect species interactions and thresholds that determine which species disperse.

This perspective summarizes the genesis, development, and potential future directions of the multispeciesJOR Spinehistopathology series.

Zonguldak ilinde uzun süre bir (BTO; sığır) veya birden fazla (karışık) hayvan türü (KTO; sığır, koyun ve keçi) ile farklı seviyelerde otlatma baskısına maruz kalan meraların değerlendirilmesi için 2015 ve 2016 yıllarında iki çalışma yapılmıştır. Otlatma baskısı muameleleri şu şekilde oluşturulmuştur: büyük baş hayvan birimi (BBHB) ha-1

Individual‐ and species‐level heterogeneity in contact rates can alter the ability of a pathogen to invade a host community. Many pathogens have multiple modes of transmission—by direct or indirect contact. It is important to identify the role of heterogeneity in different types of transmission when managing the risk of disease spillover at the interface among different host species. We developed a network‐based analysis to explore how individual‐ and species‐level heterogeneity shape multi‐mode contact networks. We applied this network‐based approach to contact data from proximity loggers collected in a multi‐species host community that contributes to the spillover of the disease bovine tuberculosis (bTB) to cattle populations in Michigan, USA. We used this approach to (a) quantify how individual‐ and species‐level heterogeneity influence direct and indirect contacts in this system, (b) explore how management interventions to control spillovers, such as the installation of deer fences, can alter observed contact networks and c) predict the role that wildlife species have in maintaining bTB in the community. We found that individual‐ and species‐level heterogeneity disproportionately influenced indirect and direct contact networks, with individual‐level heterogeneity having a greater effect on indirect contact networks and species‐level heterogeneity having a greater effect on direct contact networks. We also found that the installation of deer fences significantly reduced deer‐specific indirect contacts. We used the results from our network analysis to show that white‐tailed deer (Odocoileus virginianus) could act as the sole reservoir host for bTB in this community with important implications for understanding past bTB dynamics and managing the persistence of bTB in the future. Synthesis and applications. Analyses of epidemiological networks rarely account for multiple modes of contact, which can lead to an incomplete understanding of how individual‐ and species‐level heterogeneity affect disease transmission. The multi‐mode, multi‐species network analysis we develop in this study illustrates that individual‐ and species‐level heterogeneity can play significantly different roles depending on the type of contact network considered. This has important implications when managing disease at the wildlife–livestock interface, where strategies may need to be multi‐pronged to account for the variable role of heterogeneity on different modes of contact.

Although the system dynamics (SD) modeling approach has been used frequently to model various systems, there is little research on the development of hybrid SD–individual-oriented (IO) modeling. The aim of this study is to demonstrate the use of an array variable for the hybrid SD–IO modeling approach using the SD platform, and to provide a detailed modeling process of an algae–daphnid system consisting of two freshwater algal species and Daphnia. Our study showed that the array variable in the SD approach is useful for modeling multiple individuals and as a function to control the switch and integration variable for the hybrid modeling approach. The proposed method can improve the usability of hybrid modeling by enabling hybrid SD–IO modeling without requiring extensive knowledge of programming. Given the ongoing development and advancement of the SD modeling approach, this modeling technique will be a useful method to study complex systems.

The artificial bee colony (ABC) algorithm has the problem of slow convergence and may be trapped into local optimum. In this paper, a multi-species ABC (MABC) algorithm is proposed based on the multi-swarm model. The MABC algorithm uses dynamic segmentation of the swarm and a co-evolution strategy. The strategy of dynamic segmentation divides the colony into multiple sub-species, and the species communicate with each other using the co-evolution strategy. The combined global communication pattern and local communication pattern are applied among sub-species. In order to test the performance of the algorithm, experiments are conducted on the CEC’05 Test Functions. To test the performance of the algorithm in crowd simulation for evacuation, we simulate it through a crowd simulation system for evacuation, and the MABC algorithm improves the efficiency of crowd evacuation.

The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this frame-work, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles, and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of history-dependent community assembly.

We present a multi-species trace gas sensor based on a broadband mid-infrared supercontinuum source and a compact home-built Fourier Transform Spectrometer with a balanced detection scheme. The gas sensor provides a spectral resolution of 1 GHz in the wavelength range of 2.4-4.2 µm. Using a global fitting routine, we are able to retrieve the concentrations of different species in complex gas mixtures, achieving detection sensitivities in the order of 100 ppbv.Hz-1/2 (4s measurement time). We used the sensor to measure volatiles from fruit (apples, pears) under storage conditions, demonstrating its potential for monitoring fruit in commercial storage facilities.

The greenhouse gas (GHG) emissions from cities account for more than 70% of the global emissions. Over the past decades, GHG-dedicated space-based instruments, such as Japan’s Greenhouse gases Observing SATellite (GOSAT) (2009-), GOSAT-2 (2018-), NASA’s Orbiting Carbon Observatory-2 (OCO-2) (2014-), and OCO-3 (2019-), have collected the increased amount of the GHG data on the global scale, especially over urban areas. Such data have provided new opportunities to explore ways to study urban emissions, and they will also play a key role in monitoring the progress of subnational climate mitigation efforts towards the Paris Climate Agreement goal.Here we present the first high-resolution multi-species (CO2 and NO2) observations from Japanese passenger aircrafts, which should further enhance our ability to quantify GHG emissions in combination with data collected from existing ground-based stations and satellites. Our multi-species observations should also provide direct technical and scientific implications to the planned future space missions, such as Japan’s Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW) and ESA’s CO2 Monitoring Mission (CO2M), which also plan to measure CO2 and NO2 with a special focus on monitoring GHG emissions.We designed and developed a carry-on luggage sized imaging spectrometer to collect high-resolution (a few handed m to a few thousand m) CO2 and NO2 concentration data during domestic passenger flights. We conducted our first observation during the flight between Tokyo and Fukuoka in October 2020. The two-hour flight allowed us to collect sounding data ranging from 130°E to 140°E in longitude and 33.5°N to 36°N in latitude. The data were being collected every 0.5 sec in nominal and were created up to 5M soundings during the single flight. The obtained data depicted spatial patterns of CO2and NO2 concentrations over the cities and industrial areas, with some notable differences from ones seen from existing satellite observations. We compared our data to other data, such as emission inventories, and satellite observations of CO2, NO2, and nighttime lights, in order to further characterize the observed spatial gradient and patterns.In our presentation, we will also discuss the unique utility of our new aircraft observation and its potential contribution to GHG emission monitoring and the upcoming Global Stocktakes (GST) with an expanded observation coverage and frequency.

Introduction: Currently, patients suspected of endophthalmitis are referred to a tertiary centre for a vitreous biopsy and bacterial culture, thereby causing a treatment delay for the intravitreal antibiotics injection. We developed a new diagnostic tool, multi-mono-PCR (mm-PCR), not requiring viable bacteria, allowing antibiotic injection without delay. Performance of mm-PCR was tested on biopsies from patients with suspected postoperative endophthalmitis with known bacterial culture results. Methods: Most frequently occurring pathogens in endophthalmitis were determined using published data and treatment logs of endophthalmitis patient of the Rotterdam Eye Hospital. Vitreous biopsies from patients with suspected endophthalmitis were aliquoted in two parts. One part was sent out for bacterial culture and another was stored at −80°C for mm-PCR analysis and, as a backup, also by panbacterial PCR. Twelve vitreous samples from patients not suspected of having endophthalmitis were added as control samples. Results: Concordancy between bacterial culture and mm-PCR was 89% (24 of 27). All twelve control samples were negative. In three nonconcordant samples, the PCR results were most likely the correct ones. Conclusion: mm-PCR results are highly concordant with bacterial culture. mm-PCR with panbacterial PCR as backup could be considered a diagnostic tool in patients with endophthalmitis, which would allow us to reverse the order of diagnosis and treatment while maintaining diagnostic surveillance, thereby preventing treatment delay.

A wide knowledge base regarding the ecological preferences of benthic macroinvertebrates is synthesized in public databases. This knowledge can assist in disentangling the influence of mult...

In this paper, we analyze a bio-economic model of exploitation of renewable commercial resources. To take into account the typically continuous-time modeling of biological species and, instead, of the specialized harvesting activities, which by its nature cannot change continuously, the resulting dynamic system is of the hybrid type, i.e. continuous for biological variables and discrete for the economic ones. Through a discretization of the continuous variables, the problem is then reformulated by means of a three-dimensional map. Of this map, we study the dynamic properties to understand how economic parameters influence the long-run availability of resources.

Graph Convolutional Networks have recently received a lot of attention for their capability of representation learning on non-Euclidian feature spaces. Graph convolutional networks aggregate the neighbouring node features and attribute to learn graph representations. Like traditional deep learning models, the representation power of graph convolutional networks also increases with the increasing number of layers. However, it also increases the difficulty associated with training such models. Deep graph convolutional networks suffer from issues like vanishing gradient or over-fitting. In this paper, we explored skip connections in graph convolutional networks and proposed a deep residual graph convolutional neural network for predicting node properties in a protein-protein interaction network. The proposed model is an improvement over traditional deep learning models and present state-of-the-art graph learning algorithms. The implementation of the algorithm, as well as the saved model, is available online for reproducibility at https://github.com/rangan2510/R-GCN.

Biofilms are suggested to be a source of contamination in the food producing environment leading to food spoilage or the transmission of food-borne pathogens. However, to date, research has mainly focused on the presence of (biofilm-forming) bacteria within food processing environments, without analysing the associated biofilm matrix components. The aim of this study was to identify biofilm hotspots in a meat processing environment by analysing the presence of microorganisms (by cultivation and targeted quantitative real-time PCR based on 16S rRNA) and the major matrix components carbohydrates, extracellular DNA and proteins. Sampling included 47 distinct food contact surfaces and 61 distinct non-food contact surfaces from eleven rooms within an Austrian meat processing plant, either during operation or after cleaning and disinfection. Additionally, we isolated and characterized bacteria found in biofilms. The biofilm forming capacity of eleven isolates, was tested, using a static biofilm model. Additionally, two different multi-species settings were tested combining three strains, each. Biofilms were grown on stainless-steel slides for seven days at 10 °C, to mimic conditions found in the food producing environment. Overall, we identified ten biofilm positive sites, among them seven of which were sampled during operation and three after cleaning and disinfection. Five biofilms were detected on food contact surfaces (cutters and associated equipment and a screw conveyor) and five on non-food contact surfaces (drains and water hoses) resulting in 9.3 % of the sites being classified as biofilm positive. From these sites we cultivated bacteria of 29 different genera. The most prevalent bacteria belonged to the genera Brochothrix, Pseudomonas and Psychrobacter. From each biofilm we isolated bacteria from four to 12 different genera, indicating the presence of multi-species biofilms. Culturing of eleven isolates of different species (all detected in the mentioned biofilms, representing typical residential and spoilage bacteria in the meat processing environment) showed that there are differences of individual strains to produce matrix components and biomass on stainless steel slides. Brochothrix, Carnobacterium and Kocuria produced only detectable amounts of carbohydrates but neither eDNA nor proteins. The Acinetobacter and the Flavobacterium isolates were able to produce two of the measured components and six strains were capable of producing all types of analysed matrix components, among them a Pseudomonas fragi isolate. The minimal mean bacterial load detected was 5.4 log CFU/cm2 formed by the Psychrobacter strain. Different isolates showed differences in matrix formation ability, possible contributing in different amounts to the matrix production in multi-species biofilms, indicating that multi-species biofilms are a key survival mechanism for microorganisms within the food processing environment. Currently, we are testing two different multi-species biofilms in our model. Hereby we cultivate three species detected in the cutter-associated biofilms and other three species detected in the water hose-associated biofilms together to mimic these biofilms. This work ultimately showed the presence of multi-species biofilms within the meat processing environment, thereby identifying various sources of potential contamination. Data on the presence, formation and composition of biofilms (i.e. chemical and microbiological) will help to prevent and reduce biofilm formation within food processing environments.

We demonstrated a multipass-assisted dual-comb gas sensor for the simultaneous and sensitive detection of C2H2 and NH3 near 1.5 μm using a single free-running fiber laser. Two pulse trains generated from the shared cavity in the passively mode-locked fiber laser ensure the mutual coherence and common-mode noise rejection. One of the comb pulse trains passed through an open-path multipass cell with an effective path length of 4 m. A synchronized acquisition technique was adopted for more efficient interferogram acquisition compared with the conventional continuous acquisition method. At an acquisition time of 1.5 s, we obtained a signal-to-noise ratio of more than 600 by 1500 averages of the acquired spectrum of 0.1% C2H2. Pressure broadening of C2H2 and NH3 in the frequency range of 6503–6530 cm−1 between 0.1 and 1 bar were captured by the dual-comb sensor. Finally, the free-running fiber laser-based dual-comb sensor successfully analyzed the C2H2/NH3 mixtures, enabling real-time gas sensing without using complex optical and electronic feedback systems.

We present a transportable, multi-species, trace gas sensor using a high repetition rate mid-infrared supercontinuum source in combination with a lock-in amplifier, achieving tens of ppbv·Hz-1/2 detection sensitivity for multiple gas species.

Recent technological and methodological advances have revolutionized wildlife monitoring. Although most biodiversity monitoring initiatives are geared towards focal species of conservation concern, researchers are increasingly studying entire communities, specifically the spatiotemporal drivers of community size and structure and interactions among species. This has resulted in the emergence of multi-species occupancy models (MSOMs) as a promising and efficient approach for the study of community ecology. Given the potential of MSOMs for conservation and management action, it is critical to know whether study design and model assumptions are consistent with inference objectives. This is especially true for studies that are designed for a focal species but can give insights about a community. Here, we review the recent literature on MSOMs, identify areas of improvement in the multi-species study workflow, and provide a reference model for best practices for focal species and community monitoring study design. We reviewed 92 studies published between 2009 and early 2018, spanning 27 countries and a variety of taxa. There is a consistent under-reporting of details that are central to determining the adequacy of designs for generating data that can be used to make inferences about community-level patterns of occupancy, including the spatial and temporal extent, types of detectors used, covariates considered, and choice of field methods and statistical tools. This reporting bias could consequently result in skewed estimates, affecting conservation actions and management plans. On the other hand, comprehensive reporting is likely to help researchers working on MSOMs assess the robustness of inferences, in addition to making strides in terms of reproducibility and reusability of data. We use our literature review to inform a roadmap with best practices for MSOM studies, from simulations to design considerations and reporting, for the collection of new data as well as those involving existing datasets.

We present a multi-species trace gas sensor based on broadband mid-infrared absorption spectroscopy as well as its application to measure fruit-produced volatiles under different atmospheric conditions, demonstrating its potential for monitoring fruit storage rooms.

Organic farming is more environmentally friendly than conventional agriculture, promoting greater levels of habitat heterogeneity. Field borders could be more suitable for biodiversity in agricultural anthromes. Small mammals are crucial in these anthromes due to their contribution to food webs and seed consumption. We used hierarchical multi-season occupancy models to assess the effect of organic versus conventional farming on multiple small mammal species in agricultural anthromes of central Argentina. We modelled detectability and increased precision of estimates, overcoming deficiencies of previous studies. Small mammals were seasonally surveyed in 70 field borders (conventional) and 63 (organic) during two years. We were able to include less frequent specialist species, detecting a positive relationship with organic management possibly because of higher habitat quality of borders. Vegetation volume was the most important explanatory variable in both managements. Species' richness was greater under organic management mainly in spring when the habitat quality differences with conventional management were the greatest. Spring is key for the rodent assemblage because of the beginning of reproductive period, when resource demand is important. We suggest that maintaining high quality border habitats, as those supported by organic management, could allow farmers to obtain economic profit while also contributing to biodiversity conservation. Considering the positive role that native rodents may have in some agricultural anthromes, the maintenance of high population numbers may be important for biodiversity conservation. The approach used in this study shows the importance of modelling imperfect detection, reducing bias in parameter estimates, and it should be implemented in similar studies. Fil: Gomez, Maria Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina Fil: Goijman, Andrea Paula. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina Fil: Coda, José Antoni. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Serafini, Vanesa Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina Fil: Priotto, Jose Waldemar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina

Assessing the stock status of mixed and/or multi-species fishery resources is challenging. This is especially true in highly diverse systems, where landed catches are small, but comprise many species. In these circumstances, whole-of-ecosystem management requires consideration of the impact of harvesting on a plethora of species. However, this is logistically infeasible and cost prohibitive. To overcome this issue, selected ‘indicator’ species are used to assess the risk to sustainability of all ‘like’ species susceptible to capture within a fishery resource. Indicator species are determined via information on their (1) inherent vulnerability, i.e. biological attributes; (2) risk to sustainability, i.e. stock status; and (3) management importance, i.e. commercial prominence, social and/or cultural amenity value of the resource. These attributes are used to determine an overall score for each species which is used to identify ‘indicator’ species. The risk status (i.e. current risk) of the indicator species then determines the risk-level for the biological sustainability of the entire fishery resource and thus the level of priority for management, monitoring, assessment and compliance. A range of fishery management regimes are amenable to the indicator species approach, including both effort limited fisheries (e.g. individually transferable effort systems) and output controlled fisheries (e.g. species-specific catch quotas). The indicator species approach has been used and refined for fisheries resources in Western Australia over two decades. This process is now widely understood and accepted by stakeholders, as it focuses fishery dependent- and/or independent-monitoring, biological sampling, stock assessment and compliance priorities, thereby optimising the use of available jurisdictional resources.

Informing fishery management decisions using coupled socio-ecological systems (CSES) models requires model construction that captures the systems interactions with high precision. Ecological uncertainty in fishery models is easily reduced using existing scientific literature, but social drivers are often poorly defined or understood. The lack of knowledge about fishermen behavior results in inaccurate models of questionable utility for fishery managers. We designed and constructed a high fidelity agent based model (ABM) using the socio-ecological framework that reduces social system uncertainty by capturing complex behaviors using data-driven bounded rationality and feedback. The resulting generalized ABM of CSES dynamics was instantiated to Pacific salmon fisheries at Kenai river in Upper Cook Inlet, Alaska. The data-driven model construction fuses multiple data-sets for classification of social and ecological fishery regimes into stochastic distributions; the agent behaviors were generalized by evolving parametrized equations using data-driven machine learning; multiple non-trivial metrics on multiple scales verified model's accuracy and predictive capacity. The verified model of CSES dynamics at the Kenai river revealed recent instability in the dipnet fishery coupled dynamics, historic instability in the drift gillnet fishery coupled dynamics due to a compensatory and aggressive fishing strategy, and in the future the model will be used for scenario-based studies to understand the outcomes of alternative management strategies.

Increasing evidence within the literature has identified the presence of biofilms in chronic wounds and proposed that they contribute to delayed wound healing. This research aimed to investigate the presence of biofilm in diabetic foot ulcers (DFUs) using microscopy and molecular approaches and define if these are predominantly mono- or multi-species. Secondary objectives were to correlate wound observations against microscopy results in ascertaining if clinical cues are useful in detecting wound biofilm. DFU tissue specimens were obtained from 65 subjects. Scanning electron microscopy (SEM) and peptide nucleic acid fluorescent in situ hybridisation (PNA-FISH) techniques with confocal laser scanning microscopy (CLSM) were used to visualise biofilm structures. Next-generation DNA sequencing was performed to explore the microbial diversity. Clinical cues that included the presence of slough, excessive exudate, a gel material on the wound bed that reforms quickly following debridement, poor granulation and pyocyanin were correlated to microscopy results. Of the 65 DFU specimens evaluated by microscopy, all were characterised as containing biofilm (100%, P < 0·001). The presence of both mono-species and multi-species biofilms within the same tissue sections were detected, even when DNA sequencing analysis of DFU specimens revealed diverse polymicrobial communities. No clinical correlations were identified to aid clinicians in identifying wound biofilm. Microscopy visualisation, when combined with molecular approaches, confirms biofilms are ubiquitous in DFUs and form either mono- or multi-species biofilms. Clinical cues to aid clinicians in detecting wound biofilm are not accurate for use in DFUs. A paradigm shift of managing DFUs needs to consider anti-biofilm strategies.

The use of antibacterial drugs for the treatment of acute respiratory pathology promotes the development of dysbiosis in some patients, negatively affects the state of the intestine. The use of the probiotic complex Probiz, which contains Saccharomyces boulardii, lacto- and bifidobacteria, from the first days of therapy with antibacterial drugs, significantly reduces the manifestations of antibiotic-associated diarrhea in children and positively effects on the intestinal microbiota.

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

We present an UAV compatible spectrometer designed for sampling air pollutants in remote locations. Relying on a custom-made Multi-Pass Cell and a 3-5 µm broadband supercontinuum light source, it takes advantage of an uncooled MWIR camera to record 2D cross-dispersed molecular absorption spectra.

Price and market structures in fisheries change rapidly, now 40% of seafood is traded internationally and are associated with overharvesting of marine species. We have developed a bio-economic fishery model to address the pressing need of managing the interplay of different markets. We first regard local, multi-level and global markets individually and then analyze the effect of transitioning between markets on the exploitation of species and the stability of income. We find that in gradually globalizing markets, transition management needs to account for non-linear price changes since earlier policies may not be suitable after globalization. We hypothesize that short-term policies to ban harvest in the interest of species recovery benefit a local market in which incentives prevent overharvesting. In global markets we expect that sustained initiatives are needed to prevent overharvesting. Individual fisheries using contextualized models representing local ecological and trade structures may benefit from assessing the price dynamics presented in this analysis.

In the article by Lim et al. published in Journal of Microbiology 2021; 59, 417–425, did not include acknowledgments or conflict of interest.

Based on an analysis of China's marine fishery management policies since the promulgation of the Fisheries Law in 1986, this paper finds that before 2011, China's marine fishery policy mainly focused on the input control of fishing gear, fishing vessels and fishermen. Since 2011 China's marine fishery policy has been adjusted to output control in recent ten years. The management of marine fishery resources in China has gradually changed from input control management to input and output control management. The past decade was a key period in the adjustment of marine fishery policies. The characteristics of China's marine fishery policy in recent ten years include not only increasing output control on the basis of strict input control, but also paying attention to fishermen's livelihood, paying attention to the upgrading of fishing equipment, coordinating policy objectives and coastal ecological protection. In the future, China's marine fisheries management will face challenges in policy-making, such as multi species fisheries, long coastline, numerous fishing ports, large proportion of small fishing vessels, and scattered landing sites of catches. Ultimately, China's marine fishery policy aims to realize the sustainable development of the marine fishery industry under the dual goals of focusing on the livelihood of fishermen and repairing coastal and offshore fishery resources.

Breeding facilities based at zoological institutions are now considered a key component of integrated species-conservation efforts. Many zoos and aquariums now operate such facilities under the One Plan Approach, which integrates in situ and ex situ efforts with disease management, research and education elements. Perth Zoo, Australia, has been using such an approach since the late 1980s and has demonstrated success by producing large numbers (n = 3841) of animals from 11 species for release to the wild as part of coordinated species-recovery programmes, operated with key government and non-governmental partners. Managing a multi-species breeding facility has been made possible by having dedicated staff caring for the animals, establishing a science-based approach to all aspects of husbandry, and regularly publishing key results and lessons learned from those efforts. The longer-term success of the programme has been dependent on the continuous support of the board and executive of Perth Zoo, and the embedding of a conservation ethos into strategic documents, education programmes and media communications with the wider public. Funding a long-term programme has not been without its difficulties, and a flexible and adaptive approach to seeking and securing funding has been necessary.

The heterogeneous mixture of participants, fishing devices, licence conditions and regulations associated with South Australia’s Marine Scalefish Fishery (MSF), makes the task of managing it extremely challenging. This is further compounded by the highly dynamic nature of the commercial fishers who can switch their target effort between species at will. The complex nature of this fishery means that there has always been considerable capacity for it to expand through the realisation of latent effort. To counter this expansion, a licence amalgamation scheme was implemented in 1994 with the principal aim of reducing the number of participants (and therefore fishing effort) in the commercial sector. This perpetual scheme requires prospective fishers to purchase at least two existing licences before they can enter the fishery. Since its implementation, this unique management strategy has reduced the MSF’s fishing capacity by 57%, which has translated to a 52% reduction in fishing effort. Licences that were sold as part of the licence amalgamation scheme or surrendered through additional buy-back initiatives generally displayed a decline in fishing effort in their final years. Although the licence amalgamation scheme is still active, it has lost momentum. Under the current regulations the fishery can theoretically be reduced a further 22% to become fully amalgamated, but is unlikely to achieve this target as fishers are retaining their assets (licences) due to uncertainty surrounding the future of the fishery and local economy. As a long-term fisheries management initiative the licence amalgamation scheme has been successful and widely applauded by the relevant stakeholders. There is scope, however, to augment the criteria of the scheme to encourage the amalgamation of the remaining licences and maximise the benefit of this self-funded, effort reduction strategy.

The current fisheries management goals set by the European Commission states that fish stocks should be harvested to deliver maximum sustainable yields (MSY) and simultaneously, management should take ecosystem considerations into account. This creates unsolved trade-offs for the management of the stocks. We suggest a definition of a multi-species-MSY (MS-MSY) where no alternative fishing mortality (F) can increase yield (long term) for any ecologically interacting stock, given that the other stocks are fished at constant efforts (Fs). Such a MS-MSY can be solved through the game theoretic concept of a Nash equilibrium and here we explore two solutions to this conflict in the Baltic Sea. We maximize the sustainable yield of each stock under two constraints: first, we harvest the other stocks at a fixed F (FNE); second, we keep the spawning stock biomasses of the other stocks fixed [biomass Nash equilibrium (BNE)]. As a case study, we have developed a multi-species interaction stochastic operative model (MSI-SOM), which contains a SOM for each of the three dominant species of the Baltic Sea, the predator cod (Gadus morhua), and its prey herring (Clupea harengus), and sprat (Sprattus sprattus). For our Baltic Sea case, MS-MSYs exist under both the FNE and the BNE, but there is no guarantee that point solutions exists. We found that the prey species’ spawning stock biomasses are additive in the cod growth function, which allowed for a point solution in BNE. In the FNE, the herring MSY was found to be relatively insensitive to the other species’ fishing mortalities (F), which facilitated a point solution. The MSY targets of the BNE and the FNE differ slightly where the BNE gives higher predator yields and lower prey yields. CC BY 4.0

One of the most important goals in current fisheries management is to maintain or restore stocks above levels that can produce the maximum sustainable yield (MSY). However, it may not be feasible to achieve MSY simultaneously for multiple species because of trade-offs that result from interactions between species, mixed fisheries and the multiple objectives of stakeholders. The premise in this study is that MSY is a concept that needs adaptation, not wholesale replacement. The approach chosen to identify trade-offs and stakeholder preferences involved a process of consulting and discussing options with stakeholders as well as scenario modelling with bio-economic and multi-species models. It is difficult to intuitively anticipate the consequences of complex trade-offs and it is also complicated to address them from a political point of view. However, scenario modelling showed that the current approach of treating each stock separately and ignoring trade-offs may result in unacceptable ecosystem, economic or social effects in North Sea fisheries. Setting FMSY as a management target without any flexibility for compromises may lead to disappointment for some of the stakeholders. To treat FMSY no longer as a point estimate but rather as a “Pretty Good Yield” within sustainable ranges was seen as a promising way forward to avoid unacceptable outcomes when trying to fish all stocks simultaneously at FMSY. This study gives insights on how inclusive governance can help to reach consensus in difficult political processes, and how science can be used to make informed decisions inside a multi-dimensional trade-off space.

Optimal management of herring, mackerel, and blue whiting in the North East Atlantic is analyzed. The main motivation is to quantify the potential gain from implementing multispecies management compared to traditional single-species management. The objective is to maximize discounted net revenue; in other words a sole-owner perspective. The results are derived from an empirically based surplus growth type of model with three species. The biological interaction in the model is mainly competition for food. One result is that discounted net revenue could have been around 25% higher if the stocks had been optimally managed from a multi-species perspective.

Technology has an important part to play in wildlife and ecosystem conservation, and can vastly reduce time and effort spent in the associated tasks. Deep learning methods for computer vision in particular show good performance on a variety of tasks; animal detection and classification using deep learning networks are widely used to assist ecological studies. A related challenge is tracking animal movement over multiple cameras. For effective animal movement tracking, it is necessary to distinguish between individuals of the same species to correctly identify an individual moving between two cameras. Such problems could potentially be solved through animal re-identification methods. In this paper, the applicability of existing animal re-identification techniques for fully automated individual animal tracking in a cross-camera setup is explored. Recent developments in animal re-identification in the context of open-set recognition of individuals, and the extension of these systems to multiple species is examined. Some of the best performing human re-identification and object tracking systems are also reviewed in view of extending ideas within them to individual animal tracking. The survey concludes by presenting common trends in re-identification methods, lists a few challenges in the domain and recommends possible solutions.

International audience; We report on the first steps of maturation towards space of a nested cavity optical parametric oscillator and amplifiers, based on periodically poled nonlinear materials, emitting in the 2μm range for multi species differential absorption lidar (DIAL) .

Social network analysis is an invaluable tool to understand the patterns, evolution, and consequences of sociality. Comparative studies over a range of social systems across multiple taxonomic groups are particularly valuable. Such studies however require quantitative social association or interaction data across multiple species which is not easily available. We introduce the Animal Social Network Repository (ASNR) as the first multi-taxonomic repository that collates 790 social networks from more than 45 species, including those of mammals, reptiles, fish, birds, and insects. The repository was created by consolidating social network datasets from the literature on wild and captive animals into a consistent and easy-to-use network data format. The repository is archived at https://bansallab.github.io/asnr/. ASNR has tremendous research potential, including testing hypotheses in the fields of animal ecology, social behavior, epidemiology and evolutionary biology., Design Type(s)species comparison design • network analysis objective • data integration objectiveMeasurement Type(s)social interaction measurementTechnology Type(s)digital curationFactor Type(s)Taxon • experimental condition • geographic locationSample Characteristic(s)Gasterosteus aculeatus • Poecilia reticulata • Hirundo rustica • Branta leucopsis • Gallus gallus • Haemorhous mexicanus • Zonotrichia atricapilla • Acanthiza • Philetairus socius • Aves • Camponotus fellah • Camponotus pennsylvanicus • Bolitotherus cornutus • Elephas maximus • Papio cynocephalus • Desmodus rotundus • Myotis sodalis • Bison bison • Bos taurus • Tursiops truncatus • Mirounga angustirostris • Crocuta crocuta • Macropus giganteus • Trichosurus cunninghami • Ateles geoffroyi • Macaca fuscata • Macaca mulatta • Macaca radiata • Macaca tonkeana • Pan paniscus • Pan troglodytes • Papio papio • Saguinus fuscicollis • Saguinus mystax • Trachypithecus johnii • Alouatta guariba • Brachyteles arachnoides • Sapajus apella • Cercopithecus campbelli • Colobus guereza • Erythrocebus patas • Macaca arctoides • Macaca assamensis • Procyon lotor • Ovis canadensis • Ateles hybridus • Microtus agrestis • Equus • Gopherus agassizii • Tiliqua rugosa Machine-accessible metadata file describing the reported data (ISA-Tab format)

Light activated disinfection (LAD) is a strategy for optimizing root canal disinfection by using a highly-selective, targeted killing of bacteria using a combination of photosensitizers and light. Over the past decade, numerous in vitro and clinical studies have been performed to demonstrate the effectiveness of this mode of root canal disinfection. While most studies offer an important understanding of the effectiveness of LAD on monospecies biofilms, few have offered credence to the fact that infections of the root canal system are mediated by polymicrobial biofilms. Hence, it is imperative to understand the effect of LAD on polymicrobial biofilms both in terms of microbial killing and the changes in the biofilm architecture. The aim of this review was to systematically review the literature to evaluate the effect of LAD on dual and multispecies biofilms and demonstrate the antibiofilm effect of LAD. Two databases (PubMed and Scopus) were searched to identify eligible studies using a combination of key words. These studies were reviewed to draw conclusions on the effect of LAD on dual and multi species biofilm and the antibiofilm effect of LAD. It was found that LAD alone may be unable to eradicate dual and multispecies biofilms, but it may enhance the effect of conventional canal debridement strategies. Novel formulations of photosensitizers with nanoparticles showed the potential to inhibit biofilm formation and/or disrupt the biofilm architecture.