abstract |
The article deals with the dynamics of increasing natural history collections on the example of one of the regions of Ukraine, the fauna of which is under constant attention of researchers. This region is the Middle Dnipro Region, namely Cherkasy Oblast in general and Kaniv Nature Reserve in particular, which are the sites of long-term monitoring studies of fauna and bases for conducting field research and field practices of students. The dynamics of collections development is considered on the example of the collections of the National Museum of Natural History of the National Academy of Sciences of Ukraine. The article shows the continuity of specimen income to the collections and, at the same time, significant changes in the dynamics of such income. Several indicators that can reflect the dynamics of research efforts are proposed. The decades (1900–1919, etc.) are chosen as time periods, and the variables are the total number of specimens per decade and the total number of families they represent. These indicators can be used to evaluate three dependent notions: in terms of fieldwork, the completeness of the captures (records); in terms of research history, the intensity of research; and in terms of museology, the abundance of collections. Among the indicators tested are the geometric mean (SQRT (Nfam × Nsp)), the quadratic mean (SQRT [(Nfam2 + Nsp2) / 2]) and the Simpson diversity index (1 / ∑ (pi)2). The first two indicators are highly dependent on sample sizes and therefore vary widely; and for this reason, the author recommends sticking with Simpson's diversity index. It can be used to estimate the distribution of not only the number of samples by family for each decade (essentially a comparison of family abundance), but also any other distributions, replacing families with genera or orders and changing the analysis periods depending on the amount of available data. The term ‘research efforts’ can be used as a synonym for ‘collection efforts’, which can be found in the publications of English-speaking colleagues. The algorithm for assessing 'research effort' is an important tool in analysing the history of collections, levels of research on regions, and the history of research. |
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