Monitoring_Lynx-lynx-carpathicus

2. Princípy monitoringu rysa / Principles of lynx monitoring________________________________________________________________________________________area, for example the compartment, the country orthe population.Reference areas need to be large enough to berepresentative of the respective compartment (ormanagement unit). The largest reference area inSwitzerland (the north-western Alps) is 1 281 km²and includes 61 locations with 122 camera traps.7. Analyses of data and reportingEach data set compiled in the frame of the lynxmonitoring requires specific analysis andinterpretation. The most reliable informationcomes from deterministic camera trapping (Fig.10), but this is for limited areas (reference areas)and in most cases is only gathered every third year.Compiling chance observations (e.g. dead lynx,killed livestock and random findings; see below)allows the continuous collection of informationover the whole country, but each data set has itsown bias. However, their presentation in parallel(without prior merging of different data sets!)allows trends to be seen or discrepanciesdiscovered in the data sets (Fig. 11).Combination of reliable density estimations forreference areas and consistently collected chanceobservations over the entire country allowsextrapolation of the lynx population in the entirecountry (Fig. 12). This is done by means of a habitatmodel and the usual 10 x 10 km raster. Each gridcell with chance observation (C1 or C2) for at leasttwo consecutive years within a 3-year window isconsidered “occupied”. Assuming that lynx densitywithin the suitable habitat of a large carnivorecompartment is equal to the density in therespective reference area (or the average densityin reference areas if the compartment includesmore than one), we can then extrapolate thenumber of lynx in each compartment and in thewhole country.Good monitoring requires good reporting. Ourreporting consists of: 1) specific reports to wildlifeauthorities; 2) feedback to game wardens, huntersand naturalists helping with monitoring;3) scientific publications whenever adequate; and4) presentations of all monitoring data to the widerpublic on the KORA website (www.kora.ch).Furthermore, all monitoring data are archived in acentral mammal database, Centre Suisse de laCartography de la Faune (CSCF), for subsequentuse and analyses.8. ConclusionsFor the monitoring of lynx in Europe at the levelof populations and countries, the following aspectsshould be considered:• No single data set or methodology aloneprovides a complete picture and can answer allquestions. Each data set has its intrinsic biasthat needs to be considered when interpretingthe data.• Data of different quality and presentingdifferent parameters should not be pooled, butshown side by side to allow a directcomparison. This allows detecting errors,shortcomings and biases if the data set deviate,but also increases the confidence in theinterpretation if the data sets confirm eachother (e.g. with regard to the populationtrend).• Methods providing scientifically robust results(e.g. abundance or density) including anestimation of the performance (e.g. standarderror or 95% confidence interval) are also themost costly and can therefore often only beapplied to a limited extent in time and space(e.g. in a reference area every third year).• The solution of the dilemma to choosebetween “precise but expensive” and“imprecise but cheap” is a “stratifiedmonitoring” approach with several levels ofdifferent resolution and methods allowingcontrolling and calibrating the data from alllevels. At the largest level (low resolution),“cheap” information is collected, at thesmallest level (high resolution), “expensive”methods are applied.• Most methods require the cooperation andcontribution of many trained staff or laymen –hence a network of observers – to be applied________________________________________________________________________________________Monitoring Lynx lynx carpathicus, Rigg & Kubala (2015) 30