Environmental science is an interdisciplinary academic field that integrates physical, biological and information sciences (including ecology, biology, physics, chemistry, plant science, zoology, mineralogy, oceanography, limnology, soil science, geology and physical geography, and atmospheric science) to the study of the environment, and the solution of environmental problems.
- Components
- Impact Assessment
- Ecosystem model{:target=”_blank”} (Ecological Modelling)
- Environmental Restoration{:target=”_blank”}
- Restoration Ecology{:target=”_blank”}
- Book
- Links
- Products
Environmental science emerged from the fields of natural history and medicine during the Enlightenment. Today it provides an integrated, quantitative, and interdisciplinary approach to the study of environmental systems.
A program that focuses on the application of biological, chemical, and physical principles to the study of the physical environment and the solution of environmental problems, including subjects such as abating or controlling environmental pollution and degradation; the interaction between human society and the natural environment; and natural resources management. Includes instruction in biology, chemistry, physics, geosciences, climatology, statistics, and mathematical modeling.
Components
- Atmospheric sciences
- Ecology
- Environmental chemistry
- Geosciences
Impact Assessment
Ecosystem model (Ecological Modelling)
Ecosystem model is an abstract, usually mathematical, representation of an ecological system (ranging in scale from an individual population, to an ecological community, or even an entire biome (生物群落)), which is studied to better understand the real system.
There are two major types of ecological models, which are generally applied to different types of problems:
- Analytic models are typically relatively simple (often linear) systems, that can be accurately described by a set of mathematical equations whose behavior is well-known.
- Simulation / Computational models use numerical techniques to solve problems for which analytic solutions are impractical or impossible.
Modelling and Simulation Links
Species distribution modelling
Environmental Restoration
Environmental Restoration is closely allied with (or perhaps sometimes used interchangeably with) ecological restoration or environmental remediation.
Approaches
Environmental restoration involves many different approaches and technologies depending on the requirements of the situation.
- It can involve heavy equipment like cranes, graders, bulldozers, or excavators, and also hand processes like the planting of trees and other vegetation.
- It can involve high-tech processes such as those applied in the careful environmental control required in fish-hatchery procedures.
- Today, computerized regulation is often being utilized in these processes.
- Computer-based mapping has also become an important dimension of restorative work, as has computer modelling.
Restoration Ecology
Restoration Ecology is the scientific study supporting the practice of ecological restoration, which is the practice of renewing and restoring degraded, damaged, or destroyed ecosystems and habitats in the environment by active human intervention (介入) and action.
Effective restoration requires an explicit goal or policy, preferably an unambiguous (明确的) one that is articulated, accepted, and codified. Restoration goals reflect societal choices from among competing policy priorities, but extracting such goals is typically contentious and politically challenging.
Book
“FOUNDATIONS OF RESTORATION ECOLOGY” by Donald A. Falk, Margaret A. Palmer, and Joy B. Zedler
The restorationist alters:
- The local distribution of light and energy aboveground, and water and chemistry belowground.
- Postrestoration conditions may favor plants with different photosynthetic pathways, as well as species that can tolerate novel microclimatic conditions of temperature and humidity.
- Belowground, plant tolerance for changes in macro- and micro nutrients, as well as exposure to increased concentrations of toxic metals and changes to soil pH, salinity, and water, can be critical to the outcome of restoration.
- The altered hydrological environment can influence plant rooting depth, root/shoot allocation, and the reliance on mycorrhizal symbioses (菌根共生).
- Restoration exposes plants to a wide range of physiological stressors (生理应激源), and outcomes will depend on the ability of species to tolerate altered environments.
Ecological Theory and Restoration Ecology
Ecological restoration is to move a damaged system to an ecological state that is within some acceptable limits relative to a less disturbed system.
Science-based restorations follow:
- explicitly stated goals
- a restoration design informed by eco-logical knowledge
- quantitative assessment of system responses employing pre- and postrestoration data collection
- analysis and application of results to inform subsequent efforts
Broad areas of ecological theory that are foundational to the science of restoration ecology:
- Ecological Theory and the Restoration of Populations and Communities (Page 24)
- Population and ecological genetics
- Ecophysiological and functional ecology
- Demography (人口统计学), population dynamics, metapopulation ecology
- Community ecology
- Evolutionary ecology
- Fine-scale heterogeneity (异质性)
- Restoring Ecological Function (Page 152)
- Food webs
- Ecological dynamics and trajectories
- Biodiversity and ecosystem functioning
- Modeling and simulations
- Invasive species and community invasibility (社区入侵)
- Restoration Ecology in Context (Page 270)
- Research design and statistical analysis
- Macroecology (宏观生态学)
- Paleoecology (古生态学), climate change
Population and Ecological Genetics in Restoration Ecology
“Ecological Informatics”, by Michener, William K. Recknagel, Friedrich
Ecological Informatics is an emerging discipline that takes into account the data- intensive nature of ecology, the valuable information content of ecological data, and the need to communicate results and inform decisions, including those related to research, conservation and resource management.
Ecological Entities range from genomes, individual organisms, populations, communities, ecosystems to landscapes and the biosphere, and are highly complex and distinctly evolving.
- Managing Ecological Data
- Analysis, Synthesis and Forecasting of Ecological Data
- Case Studies
Links
Official
- UN
- Europ
- USA
- Australia
- China
- UK
Website
Projects
- eEcoLiDAR, eScience Center, Netherlands
- BirdRadar, eScience Center, Netherlands
- eEcology, eScience Center, Netherlands
Products
Data
GEDI, NASA, Global Ecosystem Dynamics Investigation
Algorithm Theoretical Basis Documents (ATBDs) | ATBD name | Data products | Resolution | Version | Date |
---|---|---|---|---|---|
L1A-2A | Transmit and Receive Waveform Interpretation and Generation of L1A and L2A products | 1A: Raw waveforms, 2A: Ground elevation, canopy top height, relative height (RH) metrics | 25 m (~82 ft) diameter | 1.0.pdf | 12-2019 |
L1B | Waveform Geolocation for L1 and L2 Products | Geolocated waveforms | 25 m (~82 ft) diameter | 1.0.pdf | 12-2019 |
L2B | Footprint Canopy Cover and Vertical Profile Metrics | Canopy Cover Fraction (CCF), CCF profile, Leaf Area Index (LAI), LAI profile | 25 m (~82 ft) diameter | 1.0.pdf | 12-2019 |
L3 | Gridded Land Surface Metrics | Gridded Level 2 metrics | 1 km (~0.6 mi) grid | 1.0 | TBD |
L4A | Footprint Above Ground Biomass Density | Footprint level above ground biomass | 25 m (~82 ft) diameter | 1.0 | TBD |
L4B | Gridded Biomass Product | Gridded Above Ground Biomass Density (AGBD) | 1 km (~0.6 mi) grid | 1.0 | TBD |
- ORNL, Ridge National Laboratory, Distributed Active Archive Center
- GBIF, Global Biodiversity Information Facility
- OBIS, Ocean Biodiversity Information System
- GENESYS, Plant Genetic Resources for Food and Agriculture (PGRFA)
- BCCVL, Biodiversity and Climate Change Virtual Laboratory
Database
- AR4 (IPCC) database (Subject:: climate, socio-economic and environmental data)
- CRU database (Subject:: climate)
- EDGAR database (Subject:: The Emissions Database for Global Atmospheric Research)
- EU-watch database (Subject:: Climate)
- Enerdata Global Energy & CO2 Data (Subject:: Enerdata Global Energy & CO2 Data)
- FAOSTAT database (Subject:: agriculture, food)
- GAINS database (Subject:: Air pollutants and greenhouse gases)
- GLOBE Digital Elevation Model
- GLWD database
- GTAP database (Subject:: Economic data)
- GlobCover database
- HWSD database (Subject:: Soil properties)
- HYDE database (Subject:: History Database of the Global Environment)
- HydroSHEDS database (Subject:: Elevation)
- IEA database (Subject:: energy)
- IIASA database (Subject:: Land-use)
- IUCN dataset (Subject:: Fishery)
- Lake-Depth Data Set
- S-World database
- WDPA database (Subject:: Protected areas)
- WEC-Uranium (Subject:: World Energy Council - Uranium resource data)
- WHO database (Subject:: health)
- WISE database (Subject:: soil)
- Wildfinder database (Subject:: Distribution of species)
- World Bank database (Subject:: Human Development)
- WorldClim database
Model
- AD RICE model (Subject:: Damage and adaptaptation costs)
- CLUMondo model (Subject:: agriculture)
- DICE model (Subject:: climate change)
- DIVA model (Subject:: Consequences of sea-level rise and socio-economic development)
- EFIGTM model (Subject:: Forestry)
- ENV-Growth model (Subject:: Economy)
- ENV-Linkages model (Subject:: economics and environment)
- FAIR model (Subject:: Policy response)
- FUND model (Subject:: climate change)
- GCAM model (Subject:: climate change)
- GISMO model (Subject:: Impacts on human development)
- GLOBIO model (Subject:: Impacts on biodiversity)
- GLOFRIS model (Subject:: Flood risk assessment)
- GRIP model (Subject:: Roads)
- GUAM model (Subject:: health)
- IMAGE land management model (Subject:: Land management)
- IMPACT model (Subject:: Agricultural economy)
- LPJmL model (Subject:: Carbon, vegetation, agriculture and water)
- Global Urban Air quality Model (Subject:: Global Urban Air quality)
- MAGICC model (Subject:: climate)
- MAGNET model (Subject:: Agricultural economy)
- PCR-GLOBWB model (Subject:: Water balance)
- POLES model (Subject:: energy)
- RICE model (Subject:: Damage costs)
- TIMER model (Subject:: Energy supply and demand)