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Data from: Anonymous faecal sampling and NIRS studies of diet quality: problem or opportunity?


Corlatti, Luca (2021), Data from: Anonymous faecal sampling and NIRS studies of diet quality: problem or opportunity?, Dryad, Dataset,


Investigating the drivers of diet quality is a key issue in wildlife ecology and conservation. Faecal near infrared reflectance spectroscopy (f-NIRS) is widely used to study dietary quality since it allows for noninvasive, rapid and low-cost analysis of nutrients. Samples for f-NIRS can be collected and analyzed with or without knowledge of animal identities. While anonymous sampling allows to reduce the costs of individual identification, as it neither requires physical captures nor DNA genotyping, it neglects the potential effects of individual variation in dietary quality and may suffer severe issues of pseudoreplication. I investigated the relationship between crude protein and ecological predictors at different time periods to assess the level of individual heterogeneity in dietary quality of 22 marked chamois Rupicapra rupicapra monitored over two years. Models with and without individual grouping effect were fitted to simulate identifiable and anonymous faecal sampling, and model estimates were compared to evaluate the consequences of anonymizing data collection and analysis. The variance explained by the individual random effect and the value of diet repeatability varied with seasons and peaked in winter. Despite the occurrence of individual variation in dietary quality, ecological parameter estimates under identifiable or anonymous sampling were consistently similar. This study suggests that anonymous faecal sampling may provide robust estimates of the relationship between dietary quality and ecological correlates. However, since the level of individual heterogeneity in dietary quality may vary with species- or study-specific features, inconsequential pseudoreplication should not be assumed in other taxa. When individual differences are known to be inconsequential, anonymous sampling allows to optimize the trade-off between sampling intensity and representativeness. When pseudoreplication is consequential, however, no conclusive remedy exists to effectively resolve non-independence.