The Science of Environmental Ecology involves the study of species and their relationships as well as the species interactions with their environment. Our books include quantitative ecology, community ecology, and general data science using Excel and R: the statistical programming language.

As of July 2026 I am retired and am no longer offering training courses or workshops.

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 books on Data Analytics include:

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

As of July 2026 I am retired and no longer offer training courses or workshops.

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 Books.

From July 2026 I am retired and no longer offer training courses or workshops.

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 Books.

As of July 2026 I am retired from teaching and no longer offer training courses or workshops.

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 Books.

From July 2026 I am retired and am no longer offering training courses or workshops.

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 Books.

From July 2026 I am retired and no longer running training courses or workshops.

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

As of July 2026 I am retired and am no longer offering training courses or workshops.