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96 results for “dispersion modelling”
Biophysical larval dispersal models of observed bonefish (Albula vulpes) spawning events in Abaco, The Bahamas: An assessment of population connectivity and ocean dynamics
<p>Biophysical models are a powerful tool for assessing population connectivity of marine organisms that broadcast spawn. <em>Albula</em> <em>vulpes</em> is a species of bonefish that is an economically and culturally important sportfish found throughout the Caribbean and that exhibits genetic connectivity among geographically distant populations. We created ontogenetically relevant biophysical models for bonefish larval dispersal based upon multiple observed spawning events in Abaco, The Bahamas in 2013, 2018, and 2019. Biological parameterizations were informed through active acoustic telemetry, CTD casts, captive larval rearing, and field collections of related albulids and anguillids. Ocean conditions were derived from the Regional Navy Coastal Ocean Model American Seas dataset. Each spawning event was simulated 100 times using the program Ichthyop. Ten thousand particles were released at observed and putative spawning locations and were allowed to disperse for the full 71-day pelagic larval duration for <em>A</em>. <em>vulpes</em>. Settlement densities in defined settlement zones were assessed along with interactions with oceanographic features. The prevailing Northern dispersal paradigm exhibited strong connectivity with Grand Bahama, the Berry Islands, Andros, and self-recruitment to lower and upper Abaco. Ephemeral gyres and flow direction within Northwest and Northeast Providence Channels were shown to have important roles in larval retention to the Bahamian Archipelago. Larval development environments for larvae settling upon different islands showed few differences and dispersal was closely associated with the thermocline. Settlement patterns informed the suggestion for expansion of conservation parks in Grand Bahama, Abaco, and Andros, and the creation of a park in Eleuthera and the Berry Islands to protect fisheries. Further observation of spawning events and the creation of biophysical models will help to maximize protection for bonefish spawning locations and nursery habitat, and may help to predict year-class strength for bonefish stocks throughout the Greater Caribbean.</p>
Datasets for "Time-evolving effective dispersion (TED) model for1 transport in porous media"
<p>Temporal evolution of <span class="math-tex">\(D^{\mathrm{eff}}_{\mathrm L}(t)\)</span> simulated by particle tracking. Ensemble of 100 realisations. var: <span class="math-tex">\(\sigma^2_f\)</span>.</p>
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
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Extinction and ecosystem function debt across dispersal rate and behavior in a heterogeneous metacommunity model
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Biophysical larval dispersal models of observed bonefish (Albula vulpes) spawning events in Abaco, The Bahamas: An assessment of population connectivity and ocean dynamics
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Data to support publication figures and animation scripts at GitHub: Modeling weather-driven long-distance dispersal of spruce budworm moths (Choristoneura fumiferana)
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Stan code from: Simulation modeling reveals the evolutionary role of landscape shape and species dispersal on genetic variation within a metapopulation
Different shapes of landscape boundaries can affect the habitat networks within them and consequently the spatial genetic-patterns of a metapopulation. In this study, we used a mechanistic framework to evaluate the effects of landscape shape, through watershed elongation, on genetic divergence among populations at the metapopulation scale. Empirical genetic data from four, sympatric stream-macroinvertebrates having aerial adults were collected from streams in Japan to determine the roles of species-specific dispersal strategies on metapopulation genetics. Simulation results indicated that watershed elongation allows the formation of river networks with fewer branches and larger topographic constraints. This results in decreased interpopulation connectivity but a lower level of spatial isolation of distal populations (e.g., those found in headwaters) occurring in the landscapes examined. Distal populations had higher genetic divergence when their downstream-biased dispersal (relative to upstream- and/or overland-biased dispersal) was high. This underscores the importance of distal populations influencing genetic divergence at the metapopulation scale for species having downstream-biased dispersal. In turn, lower genetic divergence was observed under watershed elongation when the genetic isolation of distal populations was decreased in such species. This strong association between landscape shape and evolutionary processes highlights the importance of natural, spatial architecture in assessing the effectiveness of conservation and management strategies.
Model output data for "Negative density-dependent dispersal emerges from the joint evolution of density- and body condition-dependent dispersal strategies"
<p>Empirical studies have documented both positive and negative density-dependent dispersal, yet most theoretical models predict positive density dependence as a mechanism to avoid competition. Several hypotheses have been proposed to explain the occurrence of negative density-dependent dispersal, but few of these have been formally modeled. Here, we developed an individual based model of the evolution of density-dependent dispersal. This model is novel in that it considers the effects of density on dispersal directly, and indirectly through effects on individual condition. Body condition is determined mechanistically, by having juveniles compete for resources in their natal patch. We found that the evolved dispersal strategy was a steep, increasing function of both density and condition. Interestingly, although populations evolved a positive density-dependent dispersal strategy, the simulated metapopulations exhibited negative density-dependent dispersal. This occurred because of the negative relationship between density and body condition: high density sites produced low condition individuals that lacked the resources required for dispersal. Our model therefore generates the novel hypothesis that observed negative density-dependent dispersal can occur when high density limits the ability of organisms to disperse. We suggest that future studies consider how phenotype is linked to the environment when investigating the evolution of dispersal.</p>
Modelling mycorrhizal fungi dispersal by the mycophagous swamp wallaby (Wallabia bicolor)
<p>Despite the importance of mammal-fungal interactions, tools to estimate the mammal-assisted dispersal distances of fungi are lacking. Many mammals actively consume fungal fruiting bodies, the spores of which remain viable after passage through their digestive tract. Many of these fungi form symbiotic relationships with trees and provide an array of other key ecosystem functions. We present a flexible, general model to predict the distance a mycophagous mammal would disperse fungal spores. We modelled the probability of spore dispersal by combining animal movement data from GPS-telemetry with data on spore gut-retention time. We test this model using an exemplar generalist mycophagist, the swamp wallaby (<i>Wallabia bicolor</i>). We show that swamp wallabies disperse fungal spores hundreds of metres—and occasionally up to 1265 m—from the point of consumption, distances that are ecologically significant for many mycorrhizal fungi. In addition to highlighting the ecological importance of swamp wallabies as dispersers of mycorrhizal fungi in eastern Australia, our simple modelling approach provides a novel and effective way of empirically describing spore dispersal by a mycophagous animal. This approach is applicable to the study of other animal-fungi interactions in other ecosystems.</p>
Data and R Code for publication: Should dispersers be fast learners? Modelling the role of cognition in dispersal
<p><span><span><span><span><span><span><span><span><span><span><span>Both cognitive abilities and dispersal tendencies can vary strongly between individuals. Since cognitive abilities may help dealing with unknown circumstances it is conceivable that </span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span>dispersers may rely more heavily on learning abilities than residents. However, cognitive abilities are costly and leaving a familiar place might result in losing the advantage of having learned to deal with local conditions. Thus, individuals which invested in learning to cope with local conditions may be more reluctant to leave their natal place. In order to disentangle the complex relationship between dispersal and learning abilities we implemented individual-based simulations. By allowing for developmental plasticity, individuals could either develop a "resident" or "dispersal" cognitive phenotype.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>In line with our expectations, the correlation between learning abilities and dispersal could take any direction, depending how much time individuals had to recoup their investment in cognition. Both, longevity and the timing of dispersal within lifecycles determine the time individuals have to recoup that investment and thus crucially influence this correlation. We therefore suggest that species' life-history will strongly impact the expected cognitive abilities of dispersers, relative to their resident conspecifics, and that cognitive abilities might be an integral part of dispersal syndromes.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Modelling the dispersal of the two main hosts of the raccoon rabies variant in heterogeneous environments with landscape genetics
Predicting the geographic spread of wildlife epidemics requires knowledge about the movement patterns of disease hosts or vectors. The field of landscape genetics provides valuable approaches to study dispersal indirectly, which in turn may be used to understand patterns of disease spread. Here, we applied landscape genetic analyses and spatially explicit models to identify the potential path of raccoon rabies spread in a mesocarnivore community. We used relatedness estimates derived from microsatellite genotypes of raccoons and striped skunks to investigate their dispersal patterns in a heterogeneous landscape composed predominantly of agricultural, forested and residential areas. Samples were collected in an area covering 22 000 km2 in southern Québec, where the raccoon rabies variant (RRV) was first detected in 2006. Multiple regressions on distance matrices revealed that genetic distance among male raccoons was strictly a function of geographic distance, while dispersal in female raccoons was significantly reduced by the presence of agricultural fields. In skunks, our results suggested that dispersal is increased in edge habitats between fields and forest fragments in both males and females. Resistance modelling allowed us to identify likely dispersal corridors used by these two rabies hosts, which may prove especially helpful for surveillance and control (e.g. oral vaccination) activities.
Data from: Seeds in motion: genetic assignment and hydrodynamic models demonstrate concordant patterns of seagrass dispersal
Movement is fundamental to the ecology and evolutionary dynamics within species. Understanding movement through seed dispersal in the marine environment can be difficult due to the high spatial and temporal variability of ocean currents. We employed a mutually enriching approach of population genetic assignment procedures and dispersal predictions from a hydrodynamic model to overcome this difficulty and quantify the movement of dispersing floating fruit of the temperate seagrass Posidonia australis Hook.f. across coastal waters in southwestern Australia. Dispersing fruit cohorts were collected from the water surface over two consecutive years and seeds were genotyped using microsatellite DNA markers. Likelihood-based genetic assignment tests were used to infer the meadow of origin for seed cohorts and individuals. A three-dimensional hydrodynamic model was coupled with a particle transport model to simulate the movement of fruit at the water surface. Floating fruit cohorts were mainly assigned genetically to the nearest meadow, but significant genetic differentiation between cohort and most-likely meadow of origin suggested a mixed origin. This was confirmed by genetic assignment of individual seeds from the same cohort to multiple meadows. The hydrodynamic model predicted 60% of fruit dispersed within 20 km, but that fruit were physically capable of dispersing beyond the study region. Concordance between these two independent measures of dispersal provide insight into the role of physical transport for long distance dispersal (LDD) of fruit and the consequences for spatial genetic structuring of seagrass meadows.
Data from: Discrete choice modelling of natal dispersal: "choosing" where to breed from a finite set of available areas
1. Classic natal dispersal studies focus mainly on distance travelled. Although distances capture some of the main selective pressures related to dispersal, this approach cannot easily incorporate the properties of the actual destination vs. the available alternatives. Recently, movement ecology studies have addressed questions on movement decisions in relation to availability of resources and/or availability of suitable habitats through the use of discrete choice models (DCMs), a widely used type of models within econometrics, which explains individual choices as a function of the properties of a finite number of alternatives. 2. In this contribution, we show how the dispersal discrete choice model (DDCM) can be used for analysing natal dispersal data in patchy environments given that the natal and the breeding area of the disperser are observed. We test this method using a case study on Great Tits (Parus major) in an archipelago of small woodlots. 3. Our results show that DDCMs are able to capture the results of classic distance-based approaches and simultaneously allow testing hypotheses on how departure and settlement are affected by variables that characterize the disperser, the natal patch and the breeding area, as well as their interactions. 4. DDCMs can be applied to any other species and system that uses some form of discrete breeding location or a certain degree of discretization can be applied.
Data from: Understanding age-specific dispersal in fishes through hydrodynamic modelling, genetic simulations and microsatellite DNA analysis
Many marine species have vastly different capacities for dispersal during larval, juvenile and adult life stages, and this has the potential to complicate the identification of population boundaries and the implementation of effective management strategies such as marine protected areas. Genetic studies of population structure and dispersal rarely disentangle these differences and usually provide only lifetime-averaged information that can be considered by managers. We address this limitation by combining age-specific autocorrelation analysis of microsatellite genotypes, hydrodynamic modelling and genetic simulations to reveal changes in the extent of dispersal during the lifetime of a marine fish. We focus on an exploited coral reef species, Lethrinus nebulosus, which has a circum-tropical distribution and is a key component of a multispecies fishery in northwestern Australia. Conventional population genetic analyses revealed extensive gene flow in this species over vast distances (up to 1500 km). Yet, when realistic adult dispersal behaviours were modelled, they could not account for these observations, implying adult dispersal does not dominate gene flow. Instead, hydrodynamic modelling showed that larval L. nebulosus are likely to be transported hundreds of kilometres, easily accounting for the observed gene flow. Despite the vast scale of larval transport, juvenile L. nebulosus exhibited fine-scale genetic autocorrelation, which declined with age. This implies both larval cohesion and extremely limited juvenile dispersal prior to maturity. The multidisciplinary approach adopted in this study provides a uniquely comprehensive insight into spatial processes in this marine fish.
Data from: Modelling unbiased dispersal kernels over continuous space by accounting for spatial heterogeneity in marking and observation efforts
1. Although a key demographic trait determining the spatial dynamics of wild populations, dispersal is notoriously difficult to estimate in the field. Indeed, dispersal distances obtained from the monitoring of marked individuals typically lead to biased estimations of dispersal kernels as a consequence of i) restricted spatial scale of the study areas compared to species potential dispersal and ii) heterogeneity in marking and observation efforts and therfore in detection probability across space. 2. Here we propose a novel method to circumvent these issues that does not require data on observation effort per se, to correct for the variability in detection of marked individuals across space. Observed dispersal events were weighted by the distribution of departure points and an eroded spatial window approach was applied so as to deal with border effect. We conducted a set of simulations which indicated that our method was successful in correcting the effect of spatially heterogeneous detectability and produce unbiased dispersal kernels. 3. We applied this method to a real dataset on Montagu's harrier (>5000 chicks tagged), providing ca. 6000 resightings collected in entire France by a network of 1200 volunteers within a citizen-science program. The median dispersal distance observed was 32 km (range: 0.1-627 km). Once corrected for spatial heterogeneity in marking and observation efforts and border effect, the modelled dispersal kernel indicated a median dispersal distance of 78-123 km depending on the spatial scale considered (constrained within French borders or not, respectively). 4. Synthesis and applications: The current rise of citizen-science programs is likely to stretch our estimate of the ecologically-relevant spatial scale at which dispersal takes place for many taxa. Our method is particularly suited for such large scale data that typically suffer from high spatial heterogeneity in marking and observation efforts and offers the possibility to derive unbiased dispersal kernels, a key component for modelling population dynamics and species distribution in a context of environmental change. Currently, our method assumes homogeneity in both habitat and dispersal behaviour across individuals. We discuss however how to relax these hypotheses to further investigate the effect of e.g. local conspecific density or habitat quality on dispersal propensity.
Data from: Model-based analysis supports interglacial refugia over long-dispersal events in the diversification of two South American cactus species
Pilosocereus machrisii and P. aurisetus are cactus species within the P. aurisetus complex, a group of eight cacti that are restricted to rocky habitats within the Neotropical savannas of eastern South America. Previous studies have suggested that diversification within this complex was driven by distributional fragmentation, isolation leading to allopatric differentiation, and secondary contact among divergent lineages. These events have been associated with Quaternary climatic cycles, leading to the hypothesis that the xerophytic vegetation patches which presently harbor these populations operate as refugia during the current interglacial. However, owing to limitations of the standard phylogeographic approaches used in these studies, this hypothesis was not explicitly tested. Here we use Approximate Bayesian Computation to refine the previous inferences and test the role of different events in the diversification of two species within P. aurisetus group. We used molecular data from chloroplast DNA and simple sequence repeats loci of P. machrisii and P. aurisetus, the two species with broadest distribution in the complex, in order to test if the diversification in each species was driven mostly by vicariance or by long-dispersal events. We found that both species were affected primarily by vicariance, with a refuge model as the most likely scenario for P. aurisetus and a soft vicariance scenario most probable for P. machrisii. These results emphasize the importance of distributional fragmentation in these species, and add support to the hypothesis of long-term isolation in interglacial refugia previously proposed for the P. aurisetus species complex diversification.
Dataset for AMT paper "Ammonia emissions from a grazed field estimated by miniDOAS measurements and inverse dispersion modelling"
<p>Single excel file containing 30 minute averaged measurements and model outputs. Includes miniDOAS concentration measurements, sonic anemometer (Gill WindMaster) wind & turbulence, environmental measurements (relative humidity, rainfall, temperature, net radiation flux), deposition velocity resistance components (measured Ra and Rb and modelled Rc), and bLS-R model outputs (dispersion coefficients, also known as C/E ratios). These data provide the model inputs required to run the bLS-R dispersion model, (alternatively the WindTrax dispersion model can be used). The emissions from the field during both measuring periods can be determined from the measured horizontal concentration gradient and the simulated dispersion coefficients (Emissions = (Cdownwind-Cupwind)/Dispersion coefficient).</p>
Salmon louse infestation levels on sea trout can be predicted from a hydrodynamic lice dispersal model
<p>The abundance of the parasitic salmon louse has increased with the growth in aquaculture of salmonids in open net pens. This represents a threat to wild salmonid populations as well as a key limiting factor for salmon farming. The Norwegian 'traffic light' management system for salmon farming aims to increase aquaculture production while securing sustainable wild salmonid populations. However, this system is at present solely focusing on mortality in wild Atlantic salmon, while responses of sea trout with different ecological characteristics are not included.</p> <p>We analyze lice counts on sea trout from surveillance data and use Bayesian statistical models to relate the observed lice infestations to the environmental lice infestation pressure, salinity, and current speed. These models can be used in risk assessment to predict when and where lice numbers surpass threshold levels for expected serious health effects in wild sea trout.</p> <p>We find that in production areas with the highest density of salmon farms (West coast), more than 50 % of the sea trout experienced lice infestations above levels of expected serious health effects.</p> <p>We also observed high lice infestations on sea trout in areas with salinities below louse tolerance levels, indicating that the fish had been infested elsewhere but were returning to low-saline waters to avoid lice or delouse. This behavioural response may over time disrupt anadromy in sea trout.</p> <p>The observed infestations on sea trout can be explained by the hydrodynamic lice dispersal model, which provides continuous estimates of lice exposure along the whole Norwegian coast. These estimates, which are used in Atlantic salmon research and management, can also be used for sea trout.</p> <p>Synthesis and policy implications: Wild sea trout, spending its entire feeding migration in fjords and coastal areas, is at higher risk than Atlantic salmon to lice infestations from aquaculture. The observed high levels of lice infestation on sea trout question the environmental sustainability of the current aquaculture industry in areas with intensive farming. We discuss the complex responses of sea trout to salmon lice and how the 'traffic light' management system may include data on this species.</p>
Supplementary material of "VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling"
<p>This dataset includes the Supplementary material of the paper: </p> <p>Dioguardi F, Massaro S, Chiodini G, Costa A, Folch A, Macedonio G, Sandri L, Selva J, Tamburello G. VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling. Ann. Geophys. [Internet]. 2022Apr.3 [cited 2022Apr.7];65(1). Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/8796</p>
Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion
<p>Online resource 1 - Test-data response for GIM model.</p> <p>Online resource 2 - Test-data response for RGI model.</p>
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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