Estimation of mortality parameters from (biased) samples at death: are we getting the basics right in wildlife field studies? A response to Lovari et al. (2007)

摘要: In a recent paper dealing with wolf mortality in Italy (Lovari et al., 2007), the authors used sample of 154 dead wolves incidentally found during 11-year period to infer population parameters (e.g. sex and age ratios, patterns, survivorship) provide way assess populationscale responses conservation strategies. our comment, we offer explanations as why Lovari al.’s (2007) has basic methodological flaws inferences at level from an opportunistic death use static life-tables under violation assumptions) that weaken results, so its conclusions are not warranted should be cautiously interpreted. Generalizing this specific case, hereby argue or convenience sampling (in animals) is acceptable encouraged, especially if results modelling applied perspective these do, many sources bias can distort statistics parameters. Wildlife biologists working endangered, low-density elusive species such large carnivores constantly challenged obtain robust reliable population-scale datasets. These needed reliably structure dynamics populations, project their future trends apply models management problems (Chapron 2003). However, obtaining statistically, methodologically biologically sound datasets scale for long time frames trivial matter. Although researchers, endangered threatened species, strive make most out any source data, proper methodology acknowledgment potential common practice ‘to get basics right wildlife field studies’ (Anderson, 2001) order ‘reliable knowledge’ (Romesburg, 1981). on address important topic estimation critical (i.e. structure, reproduction, survivorship mortality) wolfCanis lupus central Italy, relating current By analysing carcasses, they conclude ‘an extensive, routinely collection analysis carcasses relatively cheap but effective method state population, when data living missing’ 2007). We definitively concur theirs worthwhile effort, lack information undermines rational approach well other European countries where currently expanding range (Boitani, firmly believe carcasses) biases adequately addressed. recognize some limitations dataset, concerns fall short do seem have been stressed enough analyses. major flawed by considered both discussion sections. letter, explain nature death, warrants comments criticism, particular & Arlettaz, 2006). (1) truly representative animals, each dying same probability being reported, irrespective sex, age, social status, location, proximity humans cause deaths. The wolves, different observers (foresters, game wardens, etc.)