communicating the properties of marine organisms as the second dimension of marine biodiversity

Communicating the properties of marine organisms

as the second dimension of marine biodiversity

Wulf GreveGerman Centre for Marine Biodiversity Research (FIS)

and Federal Maritime Agency for Shipping and Hydrography (BSH),

Hamburg

Ocean Biodiversity Informatics Hamburg 11/29 - 12/1 2004Senckenberg German Center for Marine Biodiversity Research

Ocean Biodiversity Informatics Hamburg 11/29 - 12/1 2004Senckenberg: German Center for Marine Biodiversity Research

Introduction:

The research process: from DESCRIPTION via ANALYSIS to PROGNOSIS

Properties of marine organisms, a case study:

Helgoland Roads Zooplankton

NICHE model requirements

individual, inter-individual and community properties

The second dimension of biodiversity

Property communication:

definition, standardisation, data mining,Definition: unifying concepts vrs. specific demand

.Standardisation: computers need numbers, “bye catch retrieval”, measurement property rights, individual recognition and control via indices

new ways of communicatrion,

Perspective:

From knowledge management networks to automated data mining

Wulf Greve: Communicating the properties of marine organisms as the second dimension of marine biodiversity



The research process:

from DESCRIPTION via ANALYSIS to PROGNOSIS

Biodiversity is the basis to most biological disciplinese.g. taxonomy, systematics, evolution research, ecology to molecular genetics.

Each discipline is interested in a specific set of organic properties of the taxonomic units generally understood as species richness or biodiversity.

The specific set of organic properties requested by ecological research is used as an example of the specific species inherent information needs of any discipline.

Ecology can prognose future biodiversity.



A case study:

species list Helgoland Roads Zooplankton

DESCRIPTION via ANALYSIS to PROGNOSIS

e.g. mutual predation property needs of the NICHE model

Properties of marine organismse.g. ontogeny, physiology, ethology to biodiverse community properties: trophodynamics to stability

The second dimension of biodiversity



The time-series „Helgoland Roads Zooplankton“ documents the abundance changes on a weekly basis for 400 populations



Fig. CalanusFig. PLPIlimerickmutual exclusionstability manifold

Calanus helgolandicus

Pleurobrachia pileus

Coscinodiscus concinnus



Numeric definition of interpopulative trophodynamicsREAGENT RESPONSES:

AGENT: PLEUROBRACHIA AGENT: PLEUROBRACHIA

AGENT: CALANUS AGENT: CALANUS

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The NICHE model (Equation 1) calculation of metabolic activity (Equation 2) calculation of growth (Equation 3) calculation of reproduction (Equation 4) calculation of starvation (Equation 5) calculation of change for the reagent Ri

The trophodynamic parameter matrix

In the NICHE model the following processes have been regarded as common to all zooplankton populations: the ontogenetic development through specifiable discrete stagesthe recruitment into earlier stages (juveniles) from later stages- the dependence of growth, starvation and recruitment from the nutritional statethe species-specific limitation of each of these processesthe limitation of the nutritional state by satiation the definability of trophic interaction through e.g. the ARE standard

The NICHE model therefore is a general individual based model (IBM) for any combination of zooplankton populations. The distinctions of these are represented in the parameter values, the model requires. These consist of two groups of parameter values: the trophodynamic parameter matrix and the physiological parameter matrix.

INTERACTION-MATRIX

Agent

Reagent

NICHE -MODEL

The physiological parameter matrix is composed of the following requested entries:the size (gC developmental stage species,)maximal feeding rate (gCday-1developmental stage species)reproduction (recruits day )survival (days without nutrition)minimal residual time (maximal growth) until reaching the following stage



The sensitivity analysis

of all model parameters

ranks the entries

of the ARE-matrix,

the physiological matrix and

the initial values

according to their influence

on the model performance



Besides individual properties suchas size, age, generation-time, growth-speed, food-utilisation, reproduction-rate, starvation-resistance

intra- and inter-individual properties such as food-preference, enemy-avoidance

and community propertiessuch as ecosystem equilibria and stability

define the functional relationshipswithin ecosystems which are the information resources from whichcausal ecological models are derived



Property communication:

Definition: unifying concepts or specific demand

Standardisation: Computers need defined numbers,reliability controls access and recompensation

Data mining:research programsofficial information inventories“numeric bye `catch` retrieval”, measurement property rights,individual recognition and control via indexing and attributes



Perspective

relational attributing

new recompensation systems

new ways of communication,

advanced retrieval programs

automated knowledge management networksand:automated operative prognoses



operative prognoses of the phenology of zooplankton based on automated retrieval ofdaily internet reportsof SST temperatureby the German weather service

communicating the properties of marine organisms as the second dimension of marine biodiversity

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