Search results for " network"

Species’ ecological functionality alters the outcome of fish stocking success predicted by a food-web model

2018

Fish stocking is used worldwide in conservation and management, but its effects on food-web dynamics and ecosystem stability are poorly known. To better understand these effects and predict the outcomes of stocking, we used an empirically validated network model of a well-studied lake ecosystem. We simulate two stocking scenarios with two native fish species valuable for fishing. In the first scenario, we stock planktivorous fish (whitefish) larvae in the ecosystem. This leads to a 1% increase in adult whitefish biomasses and decreases the biomasses of the top predator (perch). In the second scenario, we also stock perch larvae in the ecosystem. This decreases the planktivorous whitefish an…

Hierarchical networks of food exchange in the black garden ant Lasius niger

2020

In most eusocial insects, the division of labour results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterise the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e. efficiency, resilience, centralisation and modularity) and (ii) individual values (i.e. …

Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs…

2020

Abstract Image processing and artificial intelligence (AI) techniques have been applied to analyze, evaluate and classify mulberry fruit according to their ripeness (unripe, ripe, and overripe). A total of 577 mulberries were graded by an expert and the images were captured by an imaging system. Then, the geometrical properties, color, and texture characteristics of each segmented mulberry was extracted using two feature reduction methods: Correlation-based Feature Selection subset (CFS) and Consistency subset (CONS). Artificial Neural Networks (ANN) and Support Vector Machine (SVM) were applied to classify mulberry fruit. ANN classification with the CFS subset feature extraction method res…

Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation

2019

Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classificat…

Systematic targeting of management actions as a tool to enhance conservation of traditional rural biotopes

2017

Traditional rural biotopes (TRBs), which are biologically and culturally valuable habitats maintained by low-intensity grazing and mowing, are a core element of biodiversity in Europe. During the last decades, TRBs have faced severe habitat loss and fragmentation due to agricultural modernization. Despite their well-known critical state, their conservation remains inadequate, thus raising a need to advance TRB conservation via spatial land-use planning. In this study we analyze a national GIS database on TRBs in order to examine how the current TRB network can be complemented in terms of conservation value based on known ecological characteristics. Given different target scenarios for the a…

Surgical implantation of electronic tags does not induce medium-term effect: insights from growth and stress physiological profile in two marine fish…

2020

Abstract Background Telemetry applied to aquatic organisms has recently developed greatly. Physiological sensors have been increasingly used as tools for fish welfare monitoring. However, for the technology to be used as a reliable welfare indicator, it is important that the tagging procedure does not disrupt fish physiology, behaviour and performance. In this communication, we share our medium-term data on stress physiological profile and growth performance after surgical tag implantation in two important marine fish species for European aquaculture, the sea bream (Sparus aurata) and the European sea bass (Dicentrarchus labrax). Results Blood samples after surgical tag implantation (46 day…

Benchmark database for fine-grained image classification of benthic macroinvertebrates

2018

Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…

A multidisciplinary analytical framework to delineate spawning areas and quantify larval dispersal in coastal fish

2019

International audience; Assessing larval dispersal is essential to understand the structure and dynamics of marine populations. However, knowledge about early-life dispersal is sparse, and so is our understanding of the spawning process, perhaps the most obscure component of biphasic life cycles. Indeed, the poorly known species-specific spawning modality and early-life traits, along with the high spatio-temporal variability of the oceanic circulation experienced during larval drift, hamper our ability to properly appraise the realized connectivity of coastal fishes. Here, we propose an analytical framework which combines Lagrangian modeling, network theory, otolith analyses and biogeograph…

Structure and vulnerability of the multi‐interaction network in macrophyte‐dominated lakes

2019

The network approach is crucial to understand how ecosystems are structured and how they will respond to the disturbances (e.g. the current global change). We have recreated the multi‐interaction network of a shallow freshwater lake dominated by submerged macrophytes (Charophytes), a known system very vulnerable to environmental changes, considering both trophic and non‐trophic relationships among its elements. To minimize the environmental variability, we established it in an experimental mesocosm, including three habitats: the pelagic, the habitat around the meadow and the periphytic community living on macrophytes. We aimed to study the structure of this network and the roles of its elem…

2020

Abstract Facing the loss of biodiversity caused by landscape fragmentation, implementation of ecological networks to connect habitats is an important biodiversity conservation issue. It is necessary to develop easily reproducible methods to identify and prioritize actions to maintain or restore ecological corridors. To date, several competing methods are used with recurrent debate on which is best and if expert-based approaches can replace data-driven models. We compared three methods: knowledge-driven (expert based), data-driven (based on species distribution model), and a mixed approach. We quantified their differences in habitat and corridor mapping, and prioritizations of landscape elem…