The Science of Environmental Ecology involves the study of species and their relationships as well as the species interactions with their environment. Our services in Environmental Ecology include: Data Analytics Training Courses, Project Workshops, and Data Analysis. Our books include quantitative ecology, community ecology, and general data science using Excel and R: the statistical programming language.

Our training courses deal with the Data Science aspects of Environmental Ecology, giving you the skills you need to explore and interpret ecological and environmental data. Our Training Courses can be tailored to produce bespoke training, to best suit your requirements. Training courses can be held in the UK or online.

Project Workshops are a data-led alternative to training, where the focus is on your project data. Improve your data interpretation and data analysis skills for future projects.

Our Books on Environmental Ecology highlight the Data Science aspects of Quantitative Ecology and Community Ecology, and include topics such as: statistical analysis, data visualisation, predictive analysis, ecological diversity, and multivariate analysis (Ordination).

Environmental Data Analytics

The Science of Environmental Data Analytics involves Analysis of environmental data. In ecology this might also be linked to species habitat requirements. Our services in Environmental Data Analytics include: Training Courses, Project Workshops, Books, and Data Consulting.

Our training courses in Data Analytics can include:

• Predictive Analysis; e.g. linking species abundance to environmental factors and habitat requirements.
• Multivariate Analysis; e.g. exploring Community ecology and environmental factors.

Courses can be tailored to produce bespoke training to best suit your requirements. Courses are held in the UK or online.

Our Project Workshops are a data-led training approach where you can improve your skills in data analysis and interpretation by exploring environmental and ecological data in context.

Our Data Analytics Consulting services can explore and report on your data project for you.

Our Books cover many topics in Data Analytics. Some are specific to ecology and cover Quantitative ecology, Ecological Diversity and Community ecology. Others cover more general aspects of Data Science, using Excel or R: The Statistical Programming Language.

Quantitative ecology

The Science of Quantitative Ecology involves the exploration of biological species and their relationships to each other and their environment. In theoretical ecology you are concerned with fundamental mechanisms and descriptions. Quantitative Ecology, as the name suggests, involves numbers, and helps to provide evidence to support ecological theory.

Quantitative ecology allows you to answer questions about species and their environment or habitat, using methods that include:

• Statistical hypothesis tests.
• Predictive analysis and machine learning.
• Ecological diversity analysis.
• Multivariate analysis (Ordination).

These are all topics covered in our Training Courses, Project Workshops and Books.

Community ecology

The Science of Community Ecology involves looking at biological species that live in proximity, and the environmental variables in their habitat. The Data Analytics of Community ecology are often more challenging than when dealing with individual species, and have led to specific methods of data analysis such as:

• Ecological Diversity.
• Community similarity (and dissimilarity).
• Multivariate Analysis (Ordination).

These are all topics covered in our Training Courses, Project Workshops and Books.

Ecological diversity

The Science of Ecological Diversity involves exploration of the number of different biological species in defined areas or habitats, as well as their relative abundance. Exploration of Ecological Diversity is a branch of both Quantitative Ecology and Community Ecology and there are various methods of data analysis associated with biological diversity, including:

• Species Richness: how many different species.
• Diversity Indices: takes into account relative abundance.
• Beta Diversity: important in Conservation, β diversity is a measure of diversity between habitats.
• Similarity (and dissimilarity): compositional comparison between communities.

These are all topics covered in our Training Courses, Project Workshops and Books.

Species habitat requirements

All biological species have environmental requirements for survival. Species habitat requirements vary, with some having wide tolerance of certain environmental conditions, and others having narrow tolerance (and so preference).

A species habitat requirements can be explored by experimentation, and by data collection in the field. The two approaches actually measure different things:

• Fundamental Niche: the range of environmental (habitat) variables that a species can tolerate.
• Realised Niche: the range of conditions that are actually occupied in the field, due to competition between species.

Various data analytics can be used to help explore these niche requirements, including multivariate analysis, predictive analysis and machine learning. These are all topics covered in our Training Courses, Project Workshops and Books.

Ecology & Data Analytics Books

Our Ecology & Data Analytics Books cover a wide range of topics using both Excel and R: The Statistical Programming Language. Our books include web support in the form of downloads, online exercises and supplementary notes.

The R program is a powerful Open Source project and is widely used by Universities and Professionals. Our data analytics books feature R prominently, as it is such a useful and widely used tool for data analysis and data visualisation.

Our general Data Analytics books include: Managing data using Excel, R Programming, Data Visualisation, Predictive Analysis, Machine Learning, and Statistical Hypothesis Testing.

Our books about Data Analytics for Ecology, Conservation & Environmental Science, include:

• Excel.
• Statistics.
• R Programming.
• Data Visualisation.
• Predictive Analysis.
• Community analysis.
• Hypothesis testing.

These books cover topics in Data Analytics that are more specific to Ecology and Environmental Science but include many examples that would be readily understood by workers in other disciplines.

Ecology & Data Analytics Courses and Workshops

Our Training Courses in Data Analytics for Ecology, Conservation & Environmental Science are in two main forms:

• General Data Analytics Courses: suitable for any discipline.
• Ecology Data Analytics Courses: aimed at Ecology, Conservation & Environmental Scientists.

Ecology & Data Analytics Training Courses cover a range of topics including: data visualisation, predictive analysis, machine learning, statistical hypothesis testing, and R programming. We can also tailor our training courses to produce bespoke training in ecological data analysis to best suit your requirements. See the Training Course Prospectus for more details of available courses.

Ecological and Conservation data Project Workshops help improve your data interpretation and data analysis skills. Project Workshops are a data-driven approach to data analytics for Ecology, Conservation & Environmental Science.

Project Workshops in Data Analytics for Ecology & Conservation are data-led and can cover the topics most important to you, such as:

• Data Cleaning and validation.
• Summary Statistics.
• Predictive Analysis.
• Machine Learning.
• Data Visualisation.

Project Workshops can utilise your own data, giving you the skills you need to complete your current project as well as future ones.

Training courses and project workshops are held in the UK and online.