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1
Communicating the properties of marine
organisms as the second dimension of marine
biodiversity Wulf Greve German Centre for Marine
Biodiversity Research (FIS) and Federal Maritime
Agency for Shipping and Hydrography (BSH),
Hamburg
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine Biodiversity
Research
2
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Introduction The research process from
DESCRIPTION via ANALYSIS to PROGNOSIS Properties
of marine organisms, a case study Helgoland
Roads Zooplankton NICHE model requirements indiv
idual, 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
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
3
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
disciplines e.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.
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
4
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine 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
organisms e.g. ontogeny, physiology, ethology to
biodiverse community properties trophodynamics
to stability
The second dimension of biodiversity
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
5
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
The time-series Helgoland Roads Zooplankton
documents the abundance changes on a weekly
basis for 400 populations
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
6
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Coscinodiscus concinnus
Fig. Calanus Fig. PLPI limerick mutual
exclusion stability manifold
Pleurobrachia pileus
Calanus helgolandicus
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
7
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
8
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Numeric definition of interpopulative
trophodynamics REAGENT RESPONSES
REAGENT CALANUS
REAGENT CALANUS
AGENT PLEUROBRACHIA
AGENT PLEUROBRACHIA
REAGENT PLEUROBRACHIA
REAGENT PLEUROBRACHIA
AGENT CALANUS
AGENT CALANUS
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
9
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity

• In the NICHE model the following processes have
  been regarded as common to all zooplankton
  populations
• the ontogenetic development through specifiable
  discrete stages
• the recruitment into earlier stages (juveniles)
  from later stages
• - the dependence of growth, starvation and
  recruitment from the nutritional state
• the species-specific limitation of each of these
  processes
• the 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
The trophodynamic parameter matrix
The physiological parameter matrix is composed of
the following requested entries the size (?gC?
developmental stage? species??,) maximal feeding
rate (?gC?day-1?developmental stage?
species??) reproduction (recruits ? day??
) survival (days without nutrition) minimal
residual time (maximal growth) until reaching the
following stage
Agent
Reagent
NICHE -MODEL
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
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
10
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
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
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
11
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Besides individual properties such as 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
properties such as ecosystem equilibria and
stability define the functional
relationships within ecosystems which are the
information resources from which causal
ecological models are derived
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
12
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
13
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Property communication Definition unifying
concepts or specific demand Standardisation
Computers need defined numbers, reliability
controls access and recompensation Data
mining research programs official information
inventories numeric bye catch retrieval,
measurement property rights, individual
recognition and control via indexing and
attributes
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
14
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
Perspective relational attributing new
recompensation systems new ways of
communication , advanced retrieval
programs automated knowledge management
networks and automated operative prognoses
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research
15
Wulf Greve Communicating the properties of
marine organisms as the second dimension of
marine biodiversity
operative prognoses of the phenology of
zooplankton based on automated retrieval
of daily internet reports of SST temperature by
the German weather service
Ocean Biodiversity Informatics Hamburg 11/29 -
12/1 2004
Senckenberg German Center for Marine
Biodiversity Research