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documentation:reports:june_28th_2006

June 28th 2006 Capsis annual meeting

F. de Coligny - 16.8.2006 / 22.8.2006

Participants:

Daniel Auclair (INRA AMAP), François de Coligny (INRA AMAP), Antoine Colin (IFN), Guillaume Cornu (Cirad), Tanguy Daufresne (INRA CEFS), Pierre Dubus (Cirad), François Goreaud (Cemagref LISC), Sylvie Gourlet-Fleury (Cirad), Sébastien Griffon (INRA AMAP), Guo Hong (CAF), Hong LingXia (CAF), Marc Jarry (UMR ECOBIOP), Jacques Labonne (UMR ECOBIOP), Véronique Letort (ECP), Corentin Lhuillier (Cemagref LISC), Anne Merot (UMR SYSTEM), Frédéric Mothe (INRA LERFoB), Marie-Ange Ngo-Bieng (Cemagref LISC), Sylvie Oddou (INRA URFM), Olivier Pain (Afocel), Nicolas Picard (Cirad), Laurent Saint-André (Cirad), Patrick Vallet (INRA), Oana Vigy (INRA URFM)

1. Capsis progress, current projects, foreign partnerships (Francois de Coligny, INRA AMAP, Montpellier)
2. Ecological factors shaping the genetic quality of seeds and seedlings in forest trees: a simulation study coupled with sensitivity analyses (Sylvie Oddou, INRA URFM, Avignon)
3. Ongoing computing activities for the use of national forest inventory data and models within Capsis for predictive assessments of forest resources and timber harvests at the regional level (Antoine Colin, IFN, Nogent sur Vernisson)
4. Integrated Stand Growth Model (ISGM) (Hong LingXia, Chinese Academy of Forestry, Beijing)
5. Dynamic connection between Eucalypt-Dendro and ArcGIS for the development of a forest management tool: where do we stand now ? (Laurent Saint-André, Cirad, Montpellier)
6. Coupling deer and forest models in Capsis: why and how ? (Tanguy Daufresne, INRA CEFS, Toulouse)
7. Simulating mixed virtual stands with the "spatial" library: application to Samsara module (Francois Goreaud, Cemagref LISC, Clermont Ferrand)
8. A logging module for oak connected to the Fagacees model (Frédéric Mothe, INRA LERFoB, Nancy)
9. Interactions between gene flow and adaptive divergence in populations of guppies (Poecilia reticulata): an individual based modelling approach (Jacques Labonne, INRA ECOBIOP, Saint Pée sur Nivelle)

1. Capsis progress, current projects, foreign partnerships (Francois de Coligny, INRA AMAP, Montpellier) (pdf)

Reminder of the Capsis project objectives : to build a software platform to integrate many growth and yield or dyamics models for forestry modellers, forestry managers and education. In Capsis, it is possible to choose a model, choose an initial situation and then build scenarios with various iterventions (thinning...). The results can be checked in integrated control tools (viewers, curves, histograms, tables...) and all the simulated data can be easily exported to other software for further analysis.

The Capsis software architecture was built to be stable arround a strong kernel and evolutive thanks to its extension framework. The developpers and modellers are part of the Capsis codevelopment community inside which they share all the source codes, to comply with the Capsis charter. The charter explains the few rules needed to work efficiently together and relies on a free licence (LGPL licence) for all the shared code. The models themselves are the property of their authors and their code is also shared with people in the codevelopment community, they may be distributed outside the community under a licence, free or not, when the authors decide.

The main points in Capsis : models can have very different data descriptions, allowing stand level models as well as diameter class models or even individual based spatialized models or mixt models. It is possible to integrate models for plantations as well as for heterogeneous forests. It was even possible to integrate fish dynamics models as an experience for thematics enlargement. Simulations can be run in interactive or script modes (for long simulations), the user interface is bilingual french/english, A grouping system is proposed for models handling individuals and it is possible to connect with other simulators in various technical ways when needed. Capsis has now about 400 extensions integrated.

There were several training sessions in 2006, one major with 11 trainees in february and 2 others, for people of the National Forest Inventory and for people of the Chinese Academy of Forestry.

The most active projects this past year have been :
- the ArcGIS - Capsis-Eucalypt connection by Véronique Cucchi and Laurent Saint-André,
- the Cytisus model studying a Scotch Broom / Grass / Sheep ecosystem by Estelle Chambon-Dubreuil,
- the joining of the French National Inventory with Antoine Colin, Marie-Dominique Van Damme and Jean-Luc Cousin,
- the mixing of the Fagacées and Sylvestris models to build a model for heterogeneous situations of Oak and Pine by Grégory Decélière and Thomas Perot,
- the Dynaclim model for mixing ecophysiology and dendrometry level models on the basis of the Ventoux model, by Hendrik Davi,
- the Transpoprege model dedicated to transitionnal populations genetic study over one generation by Sylvie Oddou,
- the integration of a Wood Quality Workshop (WQW) in Capsis, started in last november in New-Zealand with Dave Pont and Andrew Gordon (ENSIS) for Radiata pine and continued with Frédéric Mothe for the Fagacées model (Oak) and Céline Meredieu and Thierry Labbé for the PP3 model (Maritime Pine),
- the integration of ISGM, the Integrated Stand Growth Model (Tang ShouZheng) by Hong LingXia of the Chinese Academy of Forestry.

Recent communications, interventions in networks and recent papers related to work in Capsis were mentionned. A list of the models integrated or under integration in Capsis was given, by categories of models : Individual based models (IBM) spatialized or not, Diameter class models, spatialized or not, Stand level or Agroforestry models, Fish dynamics models.

Perspectives: a common 2D / 3D representation system in Capsis at the stand level with Lollypops, do better what we already do, accept new projects, try to become more international, try to have a second developper for the Capsis project to help handle all the partnerships and do needed background work to make it possible to grow more and better.

2. Ecological factors shaping the genetic quality of seeds and seedlings in forest trees: a simulation study coupled with sensitivity analyses (Sylvie Oddou, INRA URFM, Avignon) (ppt)

This study deals with the reproduction cycle of trees. The evolution in space matters a lot. Here, interest in demographic and genetic composition: study the processes that change the demography and genetic compositions. Experimental calibration of input factors. First project for the "Bureau de la Ressource Génétique" (BRG), focusing on regeneration for 6 species: from seed to sappling demography and genetic evolution in natural regeneration. Creation of a module in Capsis named Transoprege for example to spread adults at the beginning of the simulation and simulate regeneration.

Inputs: Density, spatial distribution, phenotypic diversity,  genetic diversity and structure,
Outputs: genetic quality, diversity, spatial structure...

Question: how processes affect sapplings genetic quality, how the way each process is modelled affects the result ?  To answer, run sensitivity analyses with the Morris method to screen the factors that mostly affect the variance of output variables. It is an economic method in simulation and computation (Method presentation).

Transpoprege is interested in the dispersal functions and wether they are light or fat tailed.
The script mode is running correctly, some troubles are under inspections, related to memory management problems or fine bugs in the implementation.

Discussion: the sensitivity analyses do not need a special extension but they need the script mode. The analysis of the spatial and genetic structure is done outside Capsis in an existing C program. A connection with the R software could be interesting. Jacques Labonne and Sylvie Oddou have needs that Guillaume Cornu and Sylvie Gourlet-Fleury already had in their Selva module, possible synergy. The studied factors are supposed to be not linked. The studied parameters are not stochastic but the runs include stochasticity.

3. Ongoing computing activities for the use of national forest inventory data and models within Capsis for predictive assessments of forest resources and timber harvests at the regional level (Antoine Colin, IFN, Nogent sur Vernisson) (ppt)

Projection of potential forest resources and wood removals at the regional level. The National Forest Inventory method changed two ears ago.

Context: modernization of NFI tools. Models: Age classes (regular even-aged stands) and Diameter classes (all stands structures). Develop a new functionnal and user friendly tool to discuss with local forestry managers. Improve project management and traceability. Integrate the NFI into the growth modellers community. Ease the use of the NFI data: 270 000 inventory plots, 3 million trees.

Objectives: Forecast short (5 years) and mid-term (30-50 years) potential timber harvest. Scale: department, regional or national levels. Decision making tool to enhance timber harvest, keep adequacy between forest resource and industry, follow up for national policy and afforestation programs.

A Study: a 3 steps process:
- analyse the current forest resource,
- define appropriate management practices,
- calculate the potential forest resource and wood removals in the future.

Important: define forest management scenarios with several methods.
NFI would like to have various hypotheses on growth, on CO2, on rainfalls, etc and be able to use them in the simulator.

Building sets of Forest Management Units ("Domaines d'étude"): compromise between homogeneity, detail, statistic accuracy. Purpose: describe the regional forest resource for forestry management purpose.

Assessment of forest resource (from raw NFI data):
Variables: growing stock, net increment, forest area, number of stems, basal area...
Criteria: region, ownership, stand structure, tree species, age classes, dbh classes (small, medium, large), slope, accessibility classes, section (timber, industrial, fuel wood), others (to be defined by local manager)...
Preparation of input data for growth models: smooth the raw data:
- to prevent improbable data,
- to obtain one age - one data.
Definition of forest management practices:
- business as usual,
- intensified management practices,
- others (discussed with the managers)
Models:
- iterative model for age class distribution, with area, volume, yield for each class for even aged stands: simple and robust aproach.
- iterative model for diameter class distribution for every kind of stand structure: assess forest resource, calculate potential wood removals, growth and thinning.
Edition of automatic pdf reports + additionnal calculations: economic balance, fuel wood resource, carbon balance, others.

Discussion: NFI will first use its own models but is interested in the models of the community. To have the same management practice for all the Forest Management Units is realistic: generally management for one species with the same rules. It is possible to use the site index as a decision tool. The interactive (gui) approach will be used to search best management practices, then use of the batch mode for large simulations. Within a project, availability of NFI data can be discussed.

4. Integrated Stand Growth Model (ISGM) (Hong LingXia, Chinese Academy of Forestry, Beijing) (ppt1, ppt2)

The Integrated Stand Growth Model was created by Tang ShouZheng in 1994. It is a group of correlated equations including (1) basal area growth model, (2) density index definition, (3) basal area equation, (4) self-thinning model, (5) dominant tree growth model (either Schumacher or Richards model), (6) average tree growth model, (7) form height model, (8) stand volume model.

The statistical algorithm of nonlinear error-in-variable simultaneous equations is used to estimate the parameters of the correlated equations to ensure that the parameter estimation is unbiased and the equations are compatible.

ISGM was previously integrated into CAF's ForStat software (in chinese) in two parts: (1) from measurements, calculate the parameters and (2) simulate the normal stand growth, thinning growth and density control graph. This second part was integrated into Capsis (in english).

Measurements data: several plots for each site type with different ages and densities and some maximum density plots. For each plot, serial measurement for different ages. If one plot was thinned, before and after thinning are considered as two plots.

In Capsis: normal growth simulation from plantation or from current situation. The thinning procedure is integrated. The density control graph (originaly from Japan) can be opened when needed afterwards.

Outputs:
- Stand growth table,
- Dbh growth curve,
- Density index curve,
- Number of trees curve,
- Total basal area growth curve,
- Tree height growth curve,
- Volume growth curve,
- Volume growth rate (continuous and yearly),
- Density control graph.

Discussion: Many references are in chinese but also some in english. Capsis is interesting because the software can be run in english. Tendancy is to focus on individual level with correlation with stand level.

5. Dynamic connection between Eucalypt-Dendro and ArcGIS for the development of a forest management tool: where do we stand now ? (Laurent Saint-André, Cirad, Montpellier) (pdf)

Context: a 42000 ha plantation of Eucalyptus in Congo (Pointe Noire), with about 150 clones in more than 1000 stands. The owner (EFC) wants a dynamic tool for management support and research (models validation).

Eucalypt is a single tree distance independent model based on allometrical relationships. It is a chain of models:
(1) growth module: inventory (t) -> site index -> dominant height growth -> basal area growth -> individual tree basal area growth -> individual tree height -> inventory (t+1). Sum of the individual heights = stand height, same for basal area. No mortality, no climate, no fertilisation yet.
(2) wood properties: volumes, ring patterns, biomass of the trees, by compartments or by ring.
(3) biogeochemical module: nutrients in rings...

The decision making tool is under construction arround the ArcGIS geographical information system, the Access database and Capsis-Eucalypt. The GIS is used (not only) as a Graphical User Interface, Capsis is run in background in script mode, launched from the GIS with a file communication. The simulation results are writen by Capsis in the database.

Why ArcGIS: it is a standard, it was the one used in Congo.

Database: three parts, was recreated for the tool and the plantation people are happy of this.
- Kernel DB: stand characteristics, name, clone, density, management practices...
- Real DB: observations, trees measuremants, environment.
- Simulated DB: results of the simulations under Capsis.

How to?
- From the GIS, the user selects stands and decides to simulate to a target date with management.
- Capsis is launched from the GIS user interface, retrieves the user selection in a file.
- It checks if data is available in the database, then generates for each stand one inventory file.
- Simulation is run with one Capsis project per stand, results are stored in the simulated DB.
- Capsis writes a finishing report.
- The results can be seen under the GIS.

Other functionnalities: queries to visualise environment information (ex: fires in the last 10 years), resulting in DB management and forms creation.

Conclusion: no important technical problems but a lot of work under Capsis. Positive interactions with forestry managers, happy with the new DB, will use it.

Future: finalize management practices procedure, make new GIS+DB applications (new road = how many m3 ?...). The growth model runs only two clones, the 150 clones must be grouped, 7 groups must be done. Growth model  validation and calibration has begun with good results. Need for feedback from biogeochemical models and exchanges / interactions between stands.

DEMO+CHAT: connection GIS - Capsis Eucalypt-Dendro (L. Saint-André)

User will be able to see the real data and the simulated data with layers in the GIS, all simulated data have a simulation number. If same simulation is run again on same stands, results will be replaced. If simulation parameters change, results will be added.

The owner works by zones (policies, ex: harvest a zone). Overall silviculture for zones, not stands.

The geodatabase is complex but the technical link was quite easy to do. All the ArcINFO users are potential users of the system, able to produce the DB. The system could be reused in Africa by Cirad. Cirad has other plots in the same area and the same framework could be reusable.

Local managers do not use Capsis but they use GISs, maybe this way Capsis could be accepted in an easier way ? New Caledonia users are interested. The shape of the DB could be reused: it was designed from two DBs: INRA and Natural Forests teams in Cirad. A good basis for a generic forest DB.

Transfer: training courses for users about models, how they are fed, in one week, they are aware of what is a model. Objective: one target person in the owner's team will exchange with the modeller: an end-user in the Capsis charter  will be an interface to the modeller.

6. Coupling deer and forest models in Capsis: why and how ? (Tanguy Daufresne, INRA CEFS, Toulouse) (ppt)

The Toulouse INRA laboratory is interested in the behaviour and ecology of widlife. Deer closely interact with the ecosystem and forest populations, deer density is low (hunting). Recently, in some places, populations raised again due to many factors. How to manage deer populations in forests?

In France, Roe deer (20-30kg, generalist, selective browser, territorial) and Red deer (80-300kg (Cévennes), generalist, selective browser/grazer (graminates), social). Overall populations have dramatically increased over the past three decades due to local density increase and recolonisation.

Deer effect on forest dynamics (Rooney et al., 2003):
- direct effect: selective browsing, understorey and tree regeneration: diversity and density,
- indirect effect: mediation of plant-herbivore interaction or plant-plant interaction after nutrient recycling.

Forest effect on deer dynamics: habitat quality:
- transfer of soil fertility to foliage quality,
- understorey density,
- hedge effect.

Illustration: impact of Black tailed deer on forest understorey in Western British Columbia. Islands: colonized by deer 15, 20 years ago and without deer: interesting comparison. Decrease is measurable for species richness and biomass density.

Feedback effect of forest structure on deer population dynamics.
- Reduction of understorey biomass due to change in fire regime entailed decline of deer in Oregon,
- soil fertility influences foliage quality hence body size in roe deer.

Impact of Red and Roe deer on forest successions in Europe. Gap model with a negative deer effect on recruitment (seedling -> small sappling (with deer - effect) -> large sappling). Predictions are model and site specific.

Caveats:
- models do not detail enough the early stages of the life cycle of trees,
- indirect effects of deer on trees are ignored,
- feedback of forest structure on deer population dynamics are ignored.

Perspectives:
- theoritical "toy models": mediation tree-understorey with deer population + understorey + one species of canopy tree ; stoichiometric model of N and P: soil nutrients + deer population + understorey,
- introducing "deer effect" including indirect effect in forest models,
- creating a deer population in Capsis to be coupled with forest models in Capsis.

Discussion: Need to consider life cycle, vertical structure of stands and multispecific stands? Trials to couple animals and forests stands already done few years ago, see Benoit Courbaud (Cemagref). To couple forest and animal models, need a seedling and sappling regeneration phase. Considering seedlings and sapplings, measurements can be done in many sites (ONF). Challenges: 1. seedling and sapplings and 2. scale up to Landscape = good forest management scale? See AMAP Landscape platform under development. Entomologists of INRA URFM in Avignon couple insects with forests (Jean-Noel Candeau). Seedlings and sapplings already exist in some Capsis models (Mountain, Samsara, Selva...).

7. Simulating mixed virtual stands with the "spatial" library: application to Samsara module (Francois Goreaud, Cemagref LISC, Clermont Ferrand) (ppt)

The spatial library: to manage more complex stands, need for new models. Tree individual based models (IBM) with local neighbourhood. Spatial structure possibly for locations or local neighbourhood. structure characterises neighbourhood: aggregated, random, regular structures. Knowing the local conditions, we know they influence the natural processes and anthropic actions which alter in return the spatial structure.

IBMs need detailed initial states to model the evolution of each individual. From aggregate data (N, G, V...), simulate initial structures (a virtual stand) to feed the IBM.

Crucial issues: (1) How to describe the structure of a stand? (2) How to simulate it? (3) How does it influence the dynamics? (4) How to take it into account in the models? (1) and (2) are processed by the spatial library in Capsis: to characterise and to simulate initial states.

Pure and regular stands: One population only: a set of points:
Characterised by Clark and Evans index (distance to nearest neighbour) or Ripley L(r) function (number of neighbours at distance < r): Examples:
- clumped: CE = 0.57, L(r) positive,
- random: CE = 1.05, L(r) near zero,
- regular: CE = 1.44, L(r) negative.
Simulated by Poisson, Neyman Scott or Gibbs.

Mixed and unevened stands: different populations = different sets of points, with high variability of spatial structure and interactions between populations: repulsion, independance, attraction.
Characterisation: define the populations (species, dbh...), characterise the structure of each population and the relative structures between populations. Two additional methods in the spatial library: Inter population CE12 index and Intertype function L12(r). Examples:
- repulsion CE12 = 3.36, L12(r) negative,
- independance CE12 = 1.89, L12(r) near zero,
- attraction CE12 = 0.65, L12(r) positive.
Simulation: intertype Gibbs process (ex: from younger to older trees).
1. number of sub populations
Then species code ex: 1 for Spruce, dbh, height, wether location is dependant from others or not (first is inependant) -> Random, Neyman Scott or Gibbs ;
Then species code ex: 2 for Fir, dbh, height, related to Spruce (ex: repulsion).
-> Aggegates of Spruce, Fir far from Spruce, etc.
-> Check with L12(r) function.

Applications to Benoit Courbaud's Samsara module (Corentin Lhuillier).
- Spruce-Fir mixed stands,
- there is a sensibility to initial spatial structure with pure regular stands,
- what about initial mixed stands?

Using a real plot (example plot from Benoit Courbaud): Saisie, 1ha, 375 spruce, 53 fir ; change locations only of trees: keep spruce locations and change fir, keep fir location and change spruce, change independance, repulsion, attraction.

Results on spruce regeneration: sapplings in Samsara, the evolution of young trees is different according to initial structure due to availability of light. Changing the location of fir (with repulsion from spruce) may lead to less openings, less light and less regeneration.

Results on fir regeneration: fewer fir in the stand and also variability due to the initial state influence.

Basal area changes: few influence for spruce (lot of trees) but lower basal area for fir in case of fir attraction because fir experiments more competition by spruce (higher basal area in case of repulsion).

Next steps: improve spatial lib, add options, improve user interfaces, possibly develop new tools, how to make it easy to integrate the spatial tools in the modellers work (interact...) ? Simulate realistic initial states: PhD of Marie-Ange Ngo-Bieng.

Discussion: M.-A. Ngo-Bieng showed that spatial structure was highly variable from one stand to another. There is a need first to characterize this spatial structure into a typology and then for each type, create a point process to simulate as realistic as possible virtual stands. The oscillations in the Samsara graphs may be an artifact resulting of the regeneration process in the mountain module because seeds are not produced every year, should be checked. The competition in Benoit Courbaud's model depends on the amount of light: growth depends on the light the tree receives, light is explicit: light rays.

8. A logging module for oak connected to the Fagacees model (Frédéric Mothe, INRA LERFoB, Nancy) (pdf)

Goal: improve the quality assessment of the modelled trees by considering a logging strategy and target products. Simulate the logging process using stem taper for the Fagacées, PP3 and Eucalypt models (Fagacées for collaboration with the french CTBA, Emmanuel Bucket). There is also a generic logging module in progress.

Oak: logging oriented towards a list of products: sliced veneers, staves (barrels), unedged sawing, sawing, LVL, particle boards, fire wood, with a priority.

Selection using the data available in Fagacées: growth rings, sapwood/heartwood, knotty core, bark, crown base.

Each product: several criteria established in connexion with CTBA:
- number of logs (ex: max 1),
- length (min / max values),
- diameter (medium or small end diameter),
- criterium linked with wood quality (ex: width of heartwood free of nodes).

Each tree is considered from bottom to the top. Outputs are mainly text files: tree data file, log data file (may be big), Dbh class: result by product. To be completed with prices.

Experimental generic logging module: same but no product names: p1, p2... with basic rules for geometry (dimension, length...) depending on the growth model detected capabilities. May be completed. Possibly define custom rules: write new java classes. Minimal requirements for using Geolog: the method named getTreeRadius_cm (GTree t, double height_m, boolean overBark). If the method getCrownBaseHeight () can be found, then the knotty core information is made available.

Discussion: No file export towards WinEpifn. This connection could be hard to do because branches are important to have knots for quality classes.

DEMO+CHAT: The Wood Quality Workshop in Capsis (F. Mothe)

Fagacées simulation with evolution according to a sylvicultural scenario from an initial rdi of 0.4 and a final rdi of 0.6 with a final age of 180 years. Graph showing the evolution of rdi over time.

Opening the Wood Quality Workshop on a chosen step in the scenario (ex: final step), make a tree selection: the listed trees are the trees alive on the reference step, with possible addition of the thinned trees.

Choose Geolog for Oak. Sort the list of products by decreasing priorities, check options to save in text files and keep logs in memory. Validation launches the job for the selected trees. Results can be seen in the Logs tab with an inspector (see all the values of the logs properties) or a Viewer in 2D.

The Generic Logger uses generic products (+ particle and fire) and generic criteria.

9. Interactions between gene flow and adaptive divergence in populations of guppies (Poecilia reticulata): an individual based modelling approach (Jacques Labonne, INRA ECOBIOP, Saint Pée sur Nivelle) (pdf)

Theory of evolution predicts that ecological speciation arises when one species is distributed in two contrasted environments and when adaptation occurs. Adaptation is the process that improves the fitness of resident individuals compared to immigrant individuals.

Guppies populations in the watersheds of Trinidad are a good example to test this prediction: watersheds present contrasted environment, where predation occurs strongly downstream, and is usually absent upstream.

These environment thus provides different selection pressures, and are separated by obstacles such as waterfalls. The distribution of male phenotypes differs between these environments: males display colorful patterns upstream in Low Predation sites (LP), whereas they are far more cryptic downstream in High Predation sites (HP). This is the result of a trade-off between sexual selection that favors male colour, and natural selection that counter selects colourful males. Such a divergent selection thus leads to phenotypic adaptation in the wild, and transplant experiments have shown that this process could be reproduced.

In order to produce ecological speciation, this adaptation is expected to limit gene flow efficiently between HP and LP sites, by building pre and post zygotic reproductive barriers. Still, a recent study by Crispo et al. (2006) found no genetic isolation due to difference in predation between sites. Our purpose is to model the evolutionary process of adaptation in guppies population, accounting for neutral and non-neutral genetics, environmental contrasts, and behaviour. Thanks to the Genetics Library provided by CAPSIS, we are able to model explicitly the transmission of phenotype. The model utilizes various sets of sexual and natural selection functions (based on real data), and evaluates the potential for adaptation in these populations under different dispersal conditions between environments. We aim at demonstrating that 1) phenotypic adaptation can occur under various gene flow conditions, 2) adaptation may also prevent gene flow on the long term, but very strong diverging selection is required, such conditions are not likely to be found in the wild on a long term scale.

This model is still in progress, but examplifies a realistic approach for evolutionary problems, accounting for individual variation, behaviour and phenotype, genetics,  demography, environmental contrasts.

DEMO+CHAT: The fish models in Capsis (J. Labonne)

Demo of the Guppy and Bidasoa modules in Capsis. Bidasoa has one end-user in Spain (the Spanish region partner in the project). Demo of the Dynet module with the river network generator, characterised by indices.


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