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Ecology
Data Analysis for Ecologists
It is said that every living organism has a relationship with every other element that makes up its environment. The interactions among organisms and their environments are mutual: the environment influences organisms and organisms alter their environment. Life is continuously changing in response to interactions from living organisms and resources and VSNi is committed to helping ecologists understand these interactions so that they can optimize real-world outcomes.
How Can Data Science Advance Ecology Research?
Designed by statisticians with non-statisticians in mind, our products are ideal for users looking for exceptional decision-making tools that are able to accommodate increasingly large and complex datasets.
Our data analysis tools are everything that you need to bring viable research and exceptional analyses to your ecology data. They can:
- Analyse large, complex datasets easily and efficiently
- Assist in defining factors that affect biodiversity
- Identify key attributes which determine certain behaviours I.e. habitat adoption or species success rateÂ
- Discover patterns in vast sets of dataÂ
- Determine risk factorsÂ
- Define interactions between organisms and the environmentÂ
- Determine whether observed effects are ecologically significantÂ
- Integrate ecological, agricultural and climatic dataÂ
- Visually present data and results in an interactive environment
Our Ecology Software Solutions
VSNi create statistical software to help your ecology research achieve the right answers from your data. Our products are supported by fully documented user guides, knowledge bases and video tutorials, making VSNi’s products straightforward to use – but should you need more assitance you can even get help directly from the team who developed the software (us!).
Genstat
Genstat’s easy-to-use environment is used by many in the ecology sector, particularly its Generalised linear models (GLMs) for analysing non-Normal data, such as counts and proportions. Likewise, ecologists often use multivariate methods for analysing and interpreting biological and environmental ecological data, including principal components analysis, bi-plots, multi-dimensional scaling, canonical correspondence analysis, canonical correlation analysis, discriminant analysis, redundancy analysis and cluster analysis. Many ecology-focused analyses can be found within Genstat’s dedicated ecology tools including investigating and modelling species abundance, calculating diversity indices and estimating the number of species.
In just a few steps or selections from the options menu you can undertake simple or more complex analyses, bringing reliable and accurate analytics to your research.
AsReml
ASReml offers a flexible approach for analyzing non-Normal data when random effects are present.
ASReml is powerful statistical software specially designed for mixed models using Residual Maximum Likelihood (REML). You can choose either ASReml-SA as a stand-alone tool, or ASReml-R to work in an R environment. Linear mixed-effects models provide a rich and flexible tool for the analysis of many data sets commonly arising in animal, plant and aqua breeding, agriculture, environmental sciences and medical sciences. ASReml is used in commercial applications worldwide for its reliability, speed and efficiency when making sense of large, often messy data sets.
Genstat’s easy-to-use environment is used by many in the ecology sector, particularly its Generalised linear models (GLMs) for analysing non-Normal data, such as counts and proportions. Likewise, ecologists often use multivariate methods for analysing and interpreting biological and environmental ecological data, including principal components analysis, bi-plots, multi-dimensional scaling, canonical correspondence analysis, canonical correlation analysis, discriminant analysis, redundancy analysis and cluster analysis. Many ecology-focused analyses can be found within Genstat’s dedicated ecology tools including investigating and modelling species abundance, calculating diversity indices and estimating the number of species.
In just a few steps or selections from the options menu you can undertake simple or more complex analyses, bringing reliable and accurate analytics to your research.
ASReml offers a flexible approach for analyzing non-Normal data when random effects are present.
ASReml is powerful statistical software specially designed for mixed models using Residual Maximum Likelihood (REML). You can choose either ASReml-SA as a stand-alone tool, or ASReml-R to work in an R environment. Linear mixed-effects models provide a rich and flexible tool for the analysis of many data sets commonly arising in animal, plant and aqua breeding, agriculture, environmental sciences and medical sciences. ASReml is used in commercial applications worldwide for its reliability, speed and efficiency when making sense of large, often messy data sets.
Case Studies
Our analytics software and consulting services are chosen by seed, plant, aqua and animal breeding companies worldwide to support and inform the development of new varieties, strains, stocks and breeds.
Enhancing agronomic research through precise statistical analysis with Genstat
Deben Agronomy is dedicated to giving potato and vegetable growers…
Elephants and Bees Project: conservation with added benefits
The conservation of the African elephant provides tremendous opportunities for simultaneously conserving…
KWS: supplying seeds to the farming industry
KWS is one of the world’s leading suppliers of seeds to the farming industry and it is therefore no surprise that research into plant breeding and seeds is a crucial part…
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Need a statistics tool for ecology?
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