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A South African rehabilitation centre for illegally kept vervet monkeys Chlorocebus aethiops Linnaeus, 1758 required an evaluation of the genetic status of vervet monkeys, to determine whether animals from different geographical areas may be mixed. We studied animals originating from three geographical regions and used biochemical genetic and morphological approaches to address this question. The most prominent trend from allozyme data was derived from the locus Prt-2 (an unspecified serum protein), where each of the three populations could be characterised by the absence or presence of unique alleles. Nevertheless, statistical coefficients indicated little genetic divergence, with genetic distance values of 0.001-0.003 and an overall fixation index value of 0.046. Average heterozygosity did not differ appreciably among populations (2.5-3.3%). The morphological study identified suitable traits, free from the influence of growth allometry, that can be used for inter-population comparisons. No significant morphological differences between con-specific populations were however found. It is concluded that vervet monkeys from the species' wider distribution range is relatively monotypic, but that monkeys from different geographical areas should not be unduly mixed, pending the results of finer grained molecular studies.
Subject and purpose of work: The objectives of the elaboration are the following: 1) to analyze the regional changes (at the level of poviats) in the number of farms involved in milk production over the period 2002-2010; 2) to present the main factors affecting the ongoing changes in Polish farms oriented at milk production; 3) to determine the impact of the measure 121. “Modernization of agricultural holdings” under the RDP 2007-2013 and the applied system of direct subsidies for the development of farms oriented at milk production. Materials and methods: The work has been prepared on the basis of the analysis and synthesis of the source literature, statistical data collected and the author’s own reflections. Results: In Poland, in the years 2002-2010 there was a distinct regional differentiation in the pace of the ongoing changes in the dairy sector. The regions, where we observe the development of milk production, include almost the entire Podlaskie Province, the northern part of the Mazowieckie Province and the south-eastern part of the Warmińsko-Mazurskie Province. Conclusions: Within the RDP 2007-2013, significant funds were allocated to support the modernization of agricultural farms. Mainly under the measure 121 “Modernization of agricultural holdings” the investments were carried out in relation to the purchase of mobile equipment, they represented 89% of all investments. This was partly due to the actual demand and administrative procedures that stimulated these types of investments.
Sea Surface Temperature (SST) maps derived from NOAA weather satellites for the period 1990–2004 were used to investigate seasonal and inter-annual variations in the Baltic Sea. A comparison between monthly mean SST and in situ measurements at the MARNET station ‘Arkona Sea’ showed good agreement with differences in July and August. Monthly means reflect strong seasonal and interannual variations. The yearly means show a slight positive trend with an increase of 0.8 K in 15 years. In particular, summer and autumn months contribute to this positive trend, with stronger trends in the northern than in the southern Baltic. The winters are characterised by a slightly negative trend. The winter minimum SST in the Arkona Sea correlates best with the WIBIX climate index derived for the Baltic region.
Accurate and efficient identification of bat (Microchiroptera) echolocation calls has been hampered by poor knowledge of the intraspecific variability in calls (including regional variation), a lack of call parameters for use in separating species and the amount of time required to manually identify individual calls or call sequences. We constructed and tested automated bat call identification keys for three regions in New South Wales, Australia, using over 4,000 reference calls in ≈300 call sequences per region. We used the program AnaScheme to extract time, frequency and shape parameters from calls recorded with the Anabat system. Classification trees were built to separate species using these parameters and provided the decision rules for construction of the keys. An ‘Unknown’ category was included in the keys for sequences that could not be confidently identified to species. The reliability of the keys was tested automatically with AnaScheme, using independent sets of reference call sequences, and keys were refined before further testing on additional test sequences. Regional keys contained 18–19 species or included species groups. We report rates of sequence misidentification (accuracy) and correct identification (detection) relative to all sequences (including ‘unknowns’) used to test each version of a key. Refined versions of the keys were accurate, with total misidentification rates of 0.5–5.3% for the three regions. Additionally, total correct identifications for regions were 56–75% (> 50% for most species), an overall high rate of detection. When ‘unknowns’ were ignored, as is common in many published studies, correct identification for regions increased to 91–99%, rates which compare favourably to the most successful classifiers tested to date. The future use of AnaScheme for automated bat call identification is promising, especially for the large-scale temporal and spatial acoustic sampling to which Anabat is particularly suited.
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