Dear colleagues,
Registration is open for the course Species distribution models and 
fuzzy logic: Combining model predictions into threshold-free estimates 
of diversity and change. This course will be held live online 
(synchronous). Max 18 participants.
Dates: April 26th-27th, 2022 from 15:00 to 18:00 (Madrid time zone)
Instructors: Dr. A. Márcia Barbosa & Dr. Alba Estrada (Instituto de 
Investigación en Recursos Cinegéticos, IREC[CSIC-UCLM-JCCM] Spain)

COURSE OVERVIEW
Live beings have continually changing distributions, and they occur with 
varying frequency across space. Hence, categorical occurrence maps, 
whether observed or model-derived, are always incomplete and 
oversimplified representations of species’ actual distributions. 
Moreover, categorical occurrence derived from model predictions usually 
depends on largely arbitrary user-specified thresholds. Analyses that 
build on such categorical information, such as most indices of 
diversity, overlap, (dis)similarity and change, thus omit important 
gradations in species occurrence and can be visibly conditioned by 
threshold choice. Fuzzy logic is a simple tool to eliminate the need for 
these thresholds and formally incorporate the locational uncertainty and 
gradual variations that characterize natural biodiversity patterns. This 
course will show how fuzzy logic can be easily integrated into 
biogeographical analyses to improve the prediction and combination of 
species distribution patterns, with applications in (macro)ecological 
interaction, global change, biodiversity and biotic regionalization 
studies.

We will use presence-(pseudo)absence models that produce presence 
probability values (e.g. generalized linear and generalized additive 
models; tree-based classification and regression methods), which can be 
mathematically converted to favorability or fuzzy membership values. We 
will see how these values allow direct comparison and combination of 
gradual distribution patterns across species, regions and time periods. 
Finally, we will see how diversity and (dis)similarity indices, which 
normally require binary presence/absence information, can be generalized 
to work with fuzzy (degree of) occurrence values. This allows the use of 
presence probability models without depending on thresholds to convert 
them into binary predictions, thus avoiding the compounded effects of 
threshold choice on the results and conclusions.

The course will include both theoretical lessons explaining the concepts 
behind the described procedures, and practical hands-on sessions where 
participants will put these procedures into practice using R. In this 
short version of the course, we will not cover data preparation and 
model building. We will provide some already-made species distribution 
models as examples for participants to work with. Participants are also 
encouraged to bring their own presence-(pseudo)absence models, with 
their observed and predicted values, for different (ecologically 
related) species or time periods.

You can find more information in  
https://www.transmittingscience.com/courses/biogeography/species-distribution-models-and-fuzzy-logic/ 
  or writing  [log in to unmask]

Best regards

Juanvi

-- 
Juan Vicente Bertó Mengual
Administration
Transmitting Science
www.transmittingscience.com

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