Search results for "12"

showing 10 items of 15303 documents

Mark-recapture estimation of mortality and migration rates for sea trout (Salmo trutta) in the northern Baltic sea

2016

Knowledge of current fishing mortality rates is an important prerequisite for formulating management plans for the recovery of threatened stocks. We present a method for estimating migration and fishing mortality rates for anadromous fishes that combines tag return data from commercial and recreational fisheries with expert opinion in a Bayesian framework. By integrating diverse sources of information and allowing for missing data, this approach may be particularly applicable in data-limited situations.Wild populations of anadromous sea trout (Salmo trutta) in the northern Baltic Sea have undergone severe declines, with the loss of many populations. The contribution of fisheries to this dec…

0106 biological sciencesBaltic SeaAquatic ScienceOceanography010603 evolutionary biology01 natural sciencesMark and recaptureRecreational fishingSea trout14. Life underwaterSalmoEcology Evolution Behavior and SystematicsEstimationta112sea troutEcologybiology010604 marine biology & hydrobiologybiology.organism_classificationexpert opinionFisheryOceanographyGeographyBaltic seaExpert opinionrecreational fisheriesta1181mark-recaptureICES Journal of Marine Science
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Fifteen operationally important decisions in the planning of biodiversity offsets

2018

Many development projects, whether they are about construction of factories, mines, roads, railways, new suburbs, shopping malls, or even individual houses, have negative environmental consequences. Biodiversity offsetting is about compensating that damage, typically via habitat restoration, land management, or by establishment of new protected areas. Offsets are the fourth step of the so-called mitigation hierarchy, in which ecological damage is first avoided, minimized second, and third restored locally. Whatever residual damage remains is then offset. Offsetting has been increasingly adopted all around the world, but simultaneously serious concerns are expressed about the validity of the…

0106 biological sciencesBiodiversity offsettingComputer scienceta1172FrameworkCONSERVATIONLand managementBiodiversity010501 environmental sciencesResidualECOLOGY010603 evolutionary biology01 natural sciences12. Responsible consumptionOperational designAdditionalityMANAGEMENTympäristövastuuOffset ratioRestoration ecologyEcology Evolution Behavior and SystematicsMultiplier1172 Environmental sciences0105 earth and related environmental sciencesNature and Landscape ConservationRESTORATIONOUTCOMESSubjective judgmentPERMANENCEEcological compensation15. Life on landEnvironmental economicsPOLICYkompensointibiodiversiteettiCONTEXTympäristövaikutukset13. Climate actionNo net lossADDITIONALITYta1181Time preferenceFlexibility
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New national and regional Annex I Habitat records: from #16 to #20

2020

New data on the distribution of the Annex I Habitats 3120, 3260, 6310, 9180* and 92A0 are reported in this contribution. In detail, 3 new occurrences in Natura 2000 Sites are presented and 5 new cells in the EEA 10 km x 10 km Reference grid are added. The new data refer to Italy and in particular to the Administrative Regions of Liguria, Sardinia, Sicily and Umbria. This issue of the section “Habitat records” includes an Errata corrige referring to the last released issue.

0106 biological sciencesBiodiversityDistribution (economics)Plant ScienceReference grid32603120010603 evolutionary biology01 natural sciences6310SB1-11103120 3260 6310 9180vegetation9180*QK900-9893120 3260 6310 9180; 92A0 92/43/EEC Directive; Biodiversity; Conservation; Italy; VegetationPlant ecology92A0Ecology Evolution Behavior and SystematicsbiodiversityEcologybusiness.industryconservation92A0 92/43/EEC DirectivePlant cultureForestryVegetationGeographyHabitatItaly918092/43/EEC DirectiveSettore BIO/03 - Botanica Ambientale E ApplicataPhysical geographyNatura 2000business010606 plant biology & botany
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Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

2018

International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…

0106 biological sciencesCanopyEarth observationPhoton010504 meteorology & atmospheric sciencesF40 - Écologie végétalehttp://aims.fao.org/aos/agrovoc/c_1920Soil Science01 natural sciencesMeasure (mathematics)http://aims.fao.org/aos/agrovoc/c_7701Multi-angle remote sensingProbability theoryhttp://aims.fao.org/aos/agrovoc/c_718Foliage clumping indexRange (statistics)http://aims.fao.org/aos/agrovoc/c_3081[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyComputers in Earth SciencesLeaf area indexhttp://aims.fao.org/aos/agrovoc/c_4039http://aims.fao.org/aos/agrovoc/c_4116Photon recollision probabilityhttp://aims.fao.org/aos/agrovoc/c_10672http://aims.fao.org/aos/agrovoc/c_32450105 earth and related environmental sciencesMathematicsRemote sensinghttp://aims.fao.org/aos/agrovoc/c_8114GeologyVegetationhttp://aims.fao.org/aos/agrovoc/c_5234http://aims.fao.org/aos/agrovoc/c_7558Leaf area indexhttp://aims.fao.org/aos/agrovoc/c_7273http://aims.fao.org/aos/agrovoc/c_1236http://aims.fao.org/aos/agrovoc/c_1556U30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_4026010606 plant biology & botanyhttp://aims.fao.org/aos/agrovoc/c_6124
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Spatial Variation of Leaf Optical Properties in a Boreal Forest Is Influenced by Species and Light Environment

2017

Leaf Optical Properties (LOPs) convey information relating to temporally dynamic photosynthetic activity and biochemistry. LOPs are also sensitive to variability in anatomically related traits such as Specific Leaf Area (SLA), via the interplay of intra-leaf light scattering and absorption processes. Therefore, variability in such traits, which may demonstrate little plasticity over time, potentially disrupts remote sensing estimates of photosynthesis or biochemistry across space. To help to disentangle the various factors that contribute to the variability of LOPs, we defined baseline variation as variation in LOPs that occurs across space, but not time. Next we hypothesized that there wer…

0106 biological sciencesCanopyPIGMENT010504 meteorology & atmospheric sciencesSpecific leaf areaPlant SciencePhotochemical Reflectance IndexAtmospheric sciences01 natural sciencesleaf optical propertiesPHOTOCHEMICAL REFLECTANCE INDEXCANOPYLEAVESCHLOROPHYLL FLUORESCENCE EMISSIONNITROGEN-CONTENTSCOTS PINEChlorophyll fluorescenceOriginal ResearchCONIFER NEEDLES0105 earth and related environmental sciences4112 Forestryphotosynthesischlorophyll fluorescencebiologyEcologyTaigaScots pine15. Life on landbiology.organism_classificationDECIDUOUS FORESTbaselineBoreal13. Climate actionEnvironmental scienceSpatial variabilityPRI010606 plant biology & botanyFrontiers in Plant Science
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Effect of pulp cell number and assimilate availability on dry matter accumulation rate in a banana fruit (Musa sp. AAA group 'Grande Naine' (Cavendis…

2001

Fruit position on the bunch (inflorescence) is an important part of variability in banana fruit weight at harvest, as fruits at the bottom of the bunch (distal fruits) are approx. 40% smaller than those at the top (proximal fruits). In this study, the respective roles of cell number and cell filling rate in the development of pulp dry weight are estimated. To this end, the source/sink ratio in the plant was altered at different stages of fruit development. Leaf shading (reducing resource availability), bunch bagging (increasing sink activity by increasing fruit temperature), and bunch trimming (decreasing sink size by fruit pruning), applied once cell division had finished, showed that the …

0106 biological sciencesCell numberFruit developmentF62 - Physiologie végétale - Croissance et développementPlant ScienceBiology01 natural sciencesSink (geography)[SDV.BV.BOT] Life Sciences [q-bio]/Vegetal Biology/Botanics03 medical and health sciencesFilling rateCelluleDry weightstomatognathic systemBananeDry matterPulpe de fruitshttp://aims.fao.org/aos/agrovoc/c_3126Croissancehttp://aims.fao.org/aos/agrovoc/c_4993ComputingMilieux_MISCELLANEOUS030304 developmental biology2. Zero hunger0303 health sciencesgeographygeography.geographical_feature_categoryhttp://aims.fao.org/aos/agrovoc/c_1418BANANIERfungifood and beveragesMusaECOPHYSIOLOGIE[SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/BotanicsTempératurehttp://aims.fao.org/aos/agrovoc/c_921Relation source puitsstomatognathic diseaseshttp://aims.fao.org/aos/agrovoc/c_3394http://aims.fao.org/aos/agrovoc/c_7657AgronomyInflorescencehttp://aims.fao.org/aos/agrovoc/c_806http://aims.fao.org/aos/agrovoc/c_34110Shading010606 plant biology & botanyDéveloppement biologique
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Fig virus-free production and survival rate improvement using meristem tip culture techinique associated with the encapsulation technology

2018

Three Mediterranean F. carica genotypes, i.e. cultivars Palazzo, Bifera nera and Catalanisca, initially infected by Fig leaf mottle-associated virus 1 (FLMaV-1), Fig leaf mottle-associated virus 2 (FLMaV-2), Fig mild mottling-associated virus (FMMaV), Fig mosaic virus (FMV), Fig latent virus 1 (FLV-1), Fig Badnavirus 1 (FBV-1) and Fig fleck-associated virus (FFkaV), were subjected to the sanitation technique via Meristem Tip (0.3-0.5 mm in size) Culture (MTC), also associated with the encapsulation technique (MTC-SS), in order to produce virus-free plant material. Encapsulation was tested to overcome the very low survival and regeneration rates, due to the small propagule size. Encouraging …

0106 biological sciencesChemistryfig mosaic disease synthetic seed sanitation RT-PCR.Settore AGR/12 - Patologia Vegetale04 agricultural and veterinary sciencesHorticultureMeristem01 natural sciencesEncapsulation (networking)Cell biologySettore AGR/03 - Arboricoltura Generale E Coltivazioni Arboree040103 agronomy & agriculture0401 agriculture forestry and fisheriesVirus freeSurvival rate010606 plant biology & botany
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Calibrating Expert Assessments Using Hierarchical Gaussian Process Models

2020

Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…

0106 biological sciencesComputer sciencepäätöksentekoRECONCILIATIONInferencecomputer.software_genre01 natural sciencesSTOCK ASSESSMENTenvironmental management010104 statistics & probabilityJUDGMENTSELICITATIONkalakantojen hoito111 Mathematicstilastolliset mallitReliability (statistics)Applied Mathematicsgaussiset prosessitfisheries sciencebias correctionexpert elicitationPROBABILITY62P1260G15symbols62F15Statistics and ProbabilityarviointimenetelmätBayesian probabilityenvironmental management.Bayesian inferenceMachine learningHEURISTICSsymbols.namesakeasiantuntijatMANAGEMENT0101 mathematicsGaussian processGaussian processCATCH LIMITSbusiness.industrybayesilainen menetelmä010604 marine biology & hydrobiologyUnivariateExpert elicitationOPINIONSupra BayesArtificial intelligenceHeuristicsbusinessFISHERIEScomputerBayesian Analysis
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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…

0106 biological sciencesComputer scienceta1172Sample (statistics)monitorointi02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural network0202 electrical engineering electronic engineering information engineeringkonenäköfine-grained classification14. Life underwaterFine-grained classificationInvertebrateta113ta112Contextual image classificationbusiness.industry010604 marine biology & hydrobiologyDeep learningConvolutional Neural NetworksBenchmark databasedeep learningPattern recognitionDeep learningselkärangattomatvedenlaatu6. Clean waterkoneoppiminenBenthic zoneBenthic macroinvertebratesbiomonitoringSignal ProcessingBiomonitoringta1181lajinmääritys020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceWater qualitybusinessbenthic macroinvertebrates
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Degradation in landscape matrix has diverse impacts on diversity in protected areas.

2017

Introduction: A main goal of protected areas is to maintain species diversity and the integrity of biological assemblages. Intensifying land use in the matrix surrounding protected areas creates a challenge for biodiversity conservation. Earlier studies have mainly focused on taxonomic diversity within protected areas. However, functional and especially phylogenetic diversities are less studied phenomena, especially with respect to the impacts of the matrix that surrounds protected areas. Phylogenetic diversity refers to the range of evolutionary lineages, the maintenance of which ensures that future evolutionary potential is safeguarded. Functional diversity refers to the range of ecologic…

0106 biological sciencesConservation geneticsConservation BiologyBiodiversitylcsh:MedicinemaankäyttöForestsAnimal Phylogenetics01 natural scienceslcsh:ScienceSpecies diversityConservation ScienceData ManagementMultidisciplinaryEcologyEcologyEukaryotaBiodiversityrespiratory systemta4112Terrestrial EnvironmentsPhylogeneticsGeographyHabitatVertebratesConservation GeneticsConservation geneticsResearch ArticleComputer and Information SciencesConservation of Natural ResourcesEcological MetricsForest managementAnimal phylogenetics010603 evolutionary biologyEcosystemsBirdssuojelualueetGeneticsAnimalsEcosystemEvolutionary SystematicsEcosystemTaxonomyEvolutionary BiologyLand use010604 marine biology & hydrobiologyEcology and Environmental Scienceslcsh:ROrganismsSpecies diversityland useBiology and Life SciencesSpecies Diversity15. Life on landbiodiversiteettiPhylogenetic diversity13. Climate actionConservation scienceAmniotesta1181lcsh:Qprotected areasZoologyhuman activitiesPLoS ONE
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