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Understanding the effects of forest-to-agriculture conversion on microbial diversity has been a major goal in soil ecological studies. However, linking community assembly to the ruling ecological processes at local and regional scales remains challenging. Here, we evaluated bacterial community assembly patterns and the ecological processes governing niche specialization in a gradient of geography, seasonality, and land-use change, totaling 324 soil samples, 43 habitat characteristics (abiotic factors), and 16 metabolic and co-occurrence patterns (biotic factors), in the Brazilian Atlantic Rainforest, a subtropical biome recognized as one the world's largest and most threatened hotspots of biodiversity. Pairwise beta diversities were lower in pastures than in forest and no-till soils. Pasture communities showed a predominantly neutral model, regarding stochastic processes, with moderate dispersion, leading to biotic homogenization. Most no-till and forest microbial communities followed a niche-based model, with low rates of dispersal and weak homogenizing selection, indicating niche specialization or variable selection. Historical and evolutionary contingencies, as represented by soil type, season, and dispersal limitation were the main drivers of microbial assembly and processes at the local scale, markedly correlated with the occurrence of endemic microbes. Our results indicate that the patterns of assembly and their governing processes are dependent on the niche occupancy of the taxa evaluated (generalists or specialists). They are also more correlated with historical and evolutionary contingencies and the interactions among taxa (i.e., co-occurrence patterns) than the land-use change itself.

Individual based models (IBMs) are up-to-date tools both in research and educational areas. Here we introduce an IBM built on NetLogo platform that simulates a top-down trophic cascade controlled by the pressure exerted by two model predators (web-building spiders and ground runner spiders) on a model pest (the olive fruit fly) within a hypothetical agricultural landscape (the olive crop). EcoPred is an IBM that aims to be an educational tool that can help teachers to explain concepts related to ecology in a modern, enjoyable and comprehensive way. EcoPred reflects the changes on a fly population within a simulated olive crop according to (1) the mortality rate caused by the predation of two spider species and energy loss, (2) the energy gain by feeding on flowers and (3) the reproduction rate in olive trees. The model was tested with 26 students achieving very good results in terms of acceptance and interest on the learning method. EcoPred can be used for educational purposes with 16 year old students and older to explain ecological concepts such as trophic level, species interactions, limiting factor and biological control in an interactive way simultaneously introducing students to biology oriented programming languages.

Simple Summary: Increasing honey bee resilience against the parasitic mite Varroa destructor, while respecting sustainability, may be achieved by enriching natural mite resistance traits in the breeding population. Some of these traits are linked to specific variants in the honey bee genome, which can be pinpointed and characterized with high-throughput molecular lab tests. Breeding by focusing on these genomic variants is thus more efficient and less time-consuming. However, when evaluating the link between a specific varroa resistance trait outcome and its associated variants in the genome, different contributions of the variants may be observed between honey bee races. It is hypothesized that these observations evolve from different linkages between the trait-causing genes and the genomic variants. Therefore, we evaluated the presence of genomic variants associated with a varroa resistance trait in different honey bee samples across the European continent. We observed significant differences in the presence of the genomic variants in the considered honey bee races, which underpin our hypothesis of linkage dissimilarities. This study shows that determining the honey bee race prior to using the genomic variants associated with varroa resistance for selective breeding is of utmost importance. Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Chrysoperla carnea s.l., a vital predator in olive groves, plays a key role in reducing the reliance on pesticides. Despite its efficacy, habitat diversification at the landscape level can compromise its effectiveness as a generalist natural enemy, diverting its attention from olive pests to other resources. To unravel its habitat preferences and maximize biocontrol services, a comprehensive study was conducted, collecting specimens monthly across diverse habitats in a Portuguese olive grove landscape. These habitats included shrublands, "montado," grasslands, eucalyptus and pine forests, vineyards, and olive groves. The findings revealed C. carnea s.l. displayed a widespread presence in all habitats, with peak abundance initially observed in olive groves, coinciding with the presence of its preferred prey, Prays oleae. However, the peak abundance of this species varies among habitats, with the highest numbers initially observed in olive groves, gradually decreasing throughout the summer and reaching the lowest levels in vineyards. Significantly, habitat diversification at the landscape level contributes to an increased abundance of C. carnea s.l. in olive groves. This suggests that diversifying available resources aids in sustaining natural enemy populations in proximity to the targeted crop, thereby enhancing their efficacy in pest control. Consequently, we advocate for stakeholders in olive cultivation to promote landscape-scale habitat diversity by preserving, restoring, or fostering alternative habitats surrounding olive groves. [ABSTRACT FROM AUTHOR]

Simple Summary: Honey bees are very important for nature and food production. However, beekeepers' work is continuously challenged by pests, pathogens, pesticides, and other impacts of the environment on their honey bee colonies, and, therefore, they would greatly benefit from up-to-date insights on the health condition of their bees. To disturb those bee colonies as little as possible, it is preferable that this information be collected in an automated way. In this article, we present the B-GOOD project as a case study to monitor the health of honey bee colonies in an automated, standardized way. The use of a similar approach by researchers in their future studies would allow the combination of different datasets on bee health. More data combinations would facilitate the use of machine learning to better and more accurately determine the thresholds for beekeeper interventions, the underlying mechanisms of honey bee colony health, and the prediction of health and colony losses, among other indicators. Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping. [ABSTRACT FROM AUTHOR]

Honey bees play an important role in agricultural landscapes by providing pollination services. Throughout the season, colonies increase their population and collect resources from the available flowering plants. Besides internal mechanisms, such as the amount of brood or the availability of bees to perform foraging flights, colonies are also influenced by the climate and the surrounding landscape. Therefore, exposure to different environmental contexts leads to distinct development rates. In this study, we show how colonies develop under three different landscape contexts and explore which external variables (mostly climate and resources availability) influence the colonies' development. We installed three apiaries in three different landscapes in the Iberian Peninsula, with temporal and spatial variation in climatic conditions and resource availability. The availability of resources and their use, as well as the development of colonies throughout the season, were thoroughly investigated. These data were used to take the first step into creating an ecologically relevant landscape by calculating the number of available resources in the landscape at different points in time, based on plants' beekeeping interest as well as nectar and production. Furthermore, climatic variables were transformed into the amount of available foraging minutes that bees had to collect resources, and a theoretical threshold of optimal vs. sub-optimal conditions was also explored. Interestingly, the main drivers of colony development (measured by daily weight increase) were not the same in the tested apiaries, evidencing how colonies are indeed intrinsically connected with the surrounding environmental scenario. Therefore, results from field testing are extremely context-dependent and should be interpreted with caution when being extrapolated to other environmental scenarios. [ABSTRACT FROM AUTHOR]

Approaches integrating interdisciplinary perspectives are necessary to address current and future health and environmental challenges. Many policy initiatives have embraced more holistic approaches to tackle these challenges, e.g., the One Health concept, the Farm to Fork (F2F), Biodiversity and Chemical strategies within the European Green Deal and the global Sustainable Development Goals (SDGs). Insect pollinators are an excellent example of the One Health concept and have gained renewed focus through the EU Pollinator Initiative. Insect pollinators are essential for healthy diets by providing pollination services and maintaining biodiversity and healthy ecosystem functions. For this reason, they are part of the Environmental Risk Assessment (ERA) of chemicals, such as plant protection products (PPPs). However, an ERA of PPPs can align with and embrace these more holistic concepts and strategies by evolving towards a systems‐based approach that recognises the diversity and the important role played by insect pollinators (e.g., pollination services for food security), as well as the variety of habitats and contexts they live in with their multiple stressors, and where PPPs may be used. A roadmap has been developed to determine the steps and actions needed to progress ERA methodologies and tools for insect pollinators. This roadmap is based on a review of the latest scientific knowledge, determining key areas for development to advance ERA, and identifying expertise and networks needed to foster progressive dialogue and public acceptance. The roadmap proposes several actions to generate the necessary knowledge to advance methodologies and tools within the current ERA framework, initially for chemical PPPs but extendable to other regulated chemicals. In addition, it outlines the actions needed to build the framework and the collaborative activities required to realise the transition to a systems‐based ERA for insect pollinators by 2030. [ABSTRACT FROM AUTHOR]

Honey bees are key insect pollinators, providing important economic and ecological value for human beings and ecosystems. This has triggered the development of several monitoring methods for assessing the temporal development of colony size, food storage, brood and pathogens. Nonetheless, most of these methods are based on visual assessments that are observer-dependent and prone to bias. Furthermore, the impact on colony development (invasiveness), as well as accuracy, were rarely considered when implementing new methods. In this study, we present and test a novel accurate and observer-independent method for honey bee colony assessment, capable of being fully standardized. Honey bee colony size is quantified by assessing the weight of adult bees, while brood and provision are assessed by taking photos and conducting image analysis of the combs with the image analysis software Deepbee®. The invasiveness and accuracy of the method were investigated using field data from two experimental apiaries in Portugal, comparing results from test and control colonies. At the end of each field experiment, most of the tested colonies had the same colony size, brood levels and honey production as the control colonies. Nonetheless, continuous weight data indicated some disturbance in tested colonies in the first year of monitoring. The overall accuracy of the image analysis software was improved by training, indicating that it is possible to adapt the software to local conditions. We conclude that the use of this fully quantitative method offers a more accurate alternative to classic visual colony assessments, with negligible impact on colony development. [ABSTRACT FROM AUTHOR]

Changes in microbial biomass carbon (MBC) and microbial respiration in soils under five different land‐use systems were evaluated at a regional scale in Santa Catarina State, Southern Brazil, to assess the effects of land‐use change and geographical distribution on the microbial and environmental patterns related to soil carbon (C) dynamics. Results showed that, in the West mesoregion, changes in MBC were correlated to the sampling season in forest and pasture systems. In the Plateau mesoregion, however, a land‐use effect was observed, with MBC decreasing in no‐till and crop‐livestock integration systems. Forest and grassland sites presented the highest values of MBC and microbial activity, while grassland sites showed lower values of the metabolic quotient (qCO2) and higher values of the microbial quotient. The qCO2 was also lower in winter for all land‐use systems. The highest total and particulate organic carbon values were found in forest sites. Chemical–physical characteristics were also observed to be significantly correlated with microbiological variables related to soil microbial C dynamics. In conclusion, land‐use intensity, season, and location were found to be the main drivers of changes in microbial C dynamics. Core Ideas: Land‐use change has affected soil microbial C dynamics.Grassland soils have presented lower metabolic quotient and higher microbial quotient values.Forest and grassland soils have presented the highest values of microbial biomass carbon and microbial activity.Forest sites have shown the highest total and particulate organic carbon values.Land‐use intensity, season, and geographic location were the main drivers of microbial C dynamics. [ABSTRACT FROM AUTHOR]

Simple Summary: Male and female red deer typically live separately in single-sex groups throughout the year, except during the mating season when they come together in mixed groups to mate. This phenomenon is known as sexual segregation. Some experts believe that this segregation occurs because males and females have different nutritional requirements due to their distinct body sizes. Our study delves into the diets of both sexes in a Mediterranean mountainous environment and provides evidence that diet may be a contributing factor to sexual segregation. Our findings indicate that males consume more arboreal species, while both sexes primarily consume shrub species. Additionally, our research highlights the importance of evaluating other factors that may impact sexual segregation in ungulates across various species and populations. Sexual segregation is a common phenomenon among animals, particularly dimorphic ones. Although widely addressed, the reasons and consequences of sexual segregation are still an important topic in need of better understanding. In this study, we mainly evaluate the diet composition and feeding behaviour of animals, which are related to the use of different habitats by the sexes, a special case of sexual segregation also termed habitat segregation. Sexually size dimorphic males and females often have different energetic and nutritional needs and, thus, different diets. We collected fresh faecal samples from wild Iberian red deer (Cervus elaphus L.) in Portugal. Samples were analysed in terms of diet composition and quality. As expected, both sexes differed in their diet composition, with males eating more arboreous species than females, but this difference was affected by sampling periods. Diet composition of both sexes had the biggest differences (and the lowest overlap) in spring, which corresponds to the end of gestation and beginning of birth. These differences might be a consequence of the sexual body size dimorphism characteristic of this species, as well as of different needs due to different reproductive costs. No differences regarding the quality of the excreted diet were observed. Our results may help to understand some patterns of sexual segregation observed in this red deer population. However, besides foraging ecology, other factors may also be contributing to sexual segregation in this Mediterranean population of red deer, and further studies focusing on sexual differences regarding feeding behaviour and digestibility are needed. [ABSTRACT FROM AUTHOR]

Enhanced drought, more frequent rainfall events and increased inter-annual variability of precipitation are the main trends of climate expected for the Mediterranean. Drought is one of the most important stressors for plants and significantly impacts plant communities causing changes in plant composition and species dominance. Through an experiment under controlled conditions, we assessed the response of Mediterranean species from different functional groups (annual grass, annual forb, annual legume, and perennial shrub) to moderate and severe water deficit. Changes in plant traits (leaf dry matter), biomass and physiology (water status, photosynthesis, pigments, and carbohydrate) were evaluated. The studied species differed in their response to water deficit. Ornithopus compressus, the legume, showed the strongest response, particularly under severe conditions, decreasing leaf relative water content (RWC), pigments and carbohydrates. The grass, Agrostis pourreti and the forb, Tolpis barbata, maintained RWC, indicating a higher ability to cope with water deficit. Finally, the shrub, Cistus salviifolius, had the lowest response to stress, showing a higher ability to cope with water deficit. Despite different responses, plant biomass was negatively affected by severe water deficit in all species. These data provide background for predicting plant diversity and species composition of Mediterranean grasslands and Montado under climate change conditions. [ABSTRACT FROM AUTHOR]

Benthic nematodes are recognized as suitable organisms to provide valuable information on the potential ecological effects of natural and anthropogenic disturbances in aquatic ecosystems. The biomass and morphometric attributes of nematodes (body length, width, and length/width) collected in the Mira estuary (SW Portugal) were analysed before the collapse and during the natural recovery process of the Zostera noltii bed. In addition, their relationship with community characteristics and environmental variables was studied. Moreover, biomass and morphometric attributes were investigated for their potential use as a complementary tool to the classical descriptor 'density' (from which several other descriptors are derived) when studying nematodes as biological indicators. Nematode biomass and morphometric attributes proved to be valuable as correlate with the environmental changes associated with the Z. noltii collapse. High values of nematode biomass, length, width, and length/width ratio were observed during the early recovery process of Z. noltii, contrasting with nematode densities, which showed consistently higher values before the collapse. These findings suggest that biomass and morphometric attributes indicate a functional adaptation of nematode communities to the new environmental conditions in the early recovery process of Z. noltii. Therefore, these traits may be used to provide complementary information to standing stocks of nematode assemblages so as to assess ecological changes over spatial and temporal scales in marine ecosystems, particularly within seagrass bed habitats., Author(s): Patrick Materatski [sup.1] , Rui Ribeiro [sup.2] , Matilde Moreira-Santos [sup.2] , José Paulo Sousa [sup.2] , Helena Adão [sup.3] Author Affiliations: (1) ICAAM-Instituto de Ciências Agrárias e Ambientais [...]

Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)