Future Directions

Making informed decisions on preserving biodiversity and sustainable environments in spite of pollution, eutrophica-tion, and climate change is of vital importance for the habitat Earth in the twenty-first century. Ecological informatics is challenged to contribute ecological understanding and tools for integrating, analyzing, and synthesizing the wealth of ecological knowledge and data for making an informed decision at local, regional, and global scale.

It is anticipated that at the next stage ecological informatics will distinctively focus on: (1) integrated

14

<n <n

12

a

fc o 3

10

8

iy o

e ~

4

1

2 0

OR

(PO4-P < 306.68)

THEN

ELSE

r

Microcystis = (WT-p1)/Secchi

Microcystis = (Secch

* p2 - WT) * NO3-N

p1 = ln(WT/17.527)*(WT + 1.551)

p2 = WT

14.419

9.49 <= p1<= 15.82

324.43 <= p2 <= 563.91

100 50

Secchi: 0.27-0.64 m O NO3-N: 0.75-2.46 mg l-1 -WT: 22.59-25.57 °C

Figure 16 Structure and input sensitivity analysis of a rule-based agent for 7-day-ahead forecasting of Microcystis biomass discovered in merged time-series data of the South African lakes Hartbeespoort, Roodeplaat, and Rietvlei by HEA.

Lake

Microcystis pg l 1 — Measured — 7-Day-ahead forecast

Hartbeespoort (South Africa) 150 1991-2004

_ JL A^x A. PK A/V AjJLJA

Roodeplaat

(South Africa) 150 1991-2004

'—^—_____Ml

600 450

(South Africa) 1991-2004 150

. JL. ___ _Jl —. A- .

Figure 17 k-Fold cross-validation of a rule-based agent for 7-day-ahead forecasting of Microcystis biomass by means of merged time-series data of the South African lakes Hartbeespoort, Roodeplaat, and Rietvlei.

analysis of genomic, phenotypic, and ecological data in order to better understand biodiversity and ecosystem behavior in response to habitat and climate changes; (2) facilitating data sharing by www-based generic data warehouses tailored for ecosystem categories at global scale; and (3) implementing hybrid model libraries generic for ecosystem categories at global scale by object-oriented programming and interactive www-access.

See also: Artificial Neural Networks: Temporal Networks; Animal Defense Strategies; Evolutionary Algorithms; Multilayer Perceptron; Wireless Sensor Networks Enabling Ecoinformatics.

10 Ways To Fight Off Cancer

10 Ways To Fight Off Cancer

Learning About 10 Ways Fight Off Cancer Can Have Amazing Benefits For Your Life The Best Tips On How To Keep This Killer At Bay Discovering that you or a loved one has cancer can be utterly terrifying. All the same, once you comprehend the causes of cancer and learn how to reverse those causes, you or your loved one may have more than a fighting chance of beating out cancer.

Get My Free Ebook


Post a comment