Safety in numbers? Supplanting data quality with fanciful models in wildlife monitoring and conservation

Abstract

Ecologists and conservation biologists seem increasingly attracted to sophisticated modelling approaches, sometimes at the expense of attention to data quality and appropriateness of fieldwork design. This dissociation may lead to a loss of perspective promoting biological unrealities as conclusions, which may be used in conservation applications. We illustrate this concern by focusing on recent attempts to estimate population size of breeding birds at large scales without any explicit testing of the reliability of the predictions through comparison with direct counts. Disconnection of analysts from ''nature'' can lead to cases of biological unrealities such as that used here to illustrate such trends. To counter this risk, we encourage investment in well-rounded scientists or more collaborative, multi-disciplinary teams capable of integrating sophisticated analyses with in-depth knowledge of the natural history of their study subjects.

Can livestock carrion availability influence diet of wintering red kites? Implications of sanitary policies in ecosystem services and conservation

“…This area was considered to contain a high density of wintering kites (0.905 kites/km 2 , 99.79 kites/ 100 km of transects in 1994, Viñuela et al 1999) and is part of one of the main strongholds for wintering red kites in Europe (northern plateau in central Spain, see Viñuela et al 1999;Cardiel 2006). Population numbers and density have suffered a dramatic decline in the last decades (0.309 kites/km 2 , 31.47 kites/100 km of transects in 2004, Cardiel 2006) that continues today contributing to the decline of the local breeding and wintering populations in the Iberian Peninsula (Blanco and Montoya 2004;Cardiel 2006;Blanco et al 2012).…”

Commonness of not-so-common birds: the need for baseline knowledge of actual population size for the validation of population size predictions

“…Strikingly, a much higher mean population estimate (∼330 000 individuals) was predicted during the breeding season (Carrascal & Palomino 2008). Considering the directly counted population (∼15 000 individuals), the predicted population size showed an accuracy of about 4.5% and an error of about 2100% (see Blanco et al 2012 for definitions of inaccuracy and error as used here). The actual population size falls far below the minimum value of the range (90% confidence interval) of the predicted number of individuals, despite this interval (213 446-475 184 individuals) being argued to be reasonably accurate (Carrascal & Palomino 2008).…”

“…We simply reiterate that, as much as possible, programmes aimed at establishing population size of wildlife by statistical inference should attempt to explicitly test their predictions by comparison with 'actual' directly censused population sizes of particular species in control areas wherever possible (see Blanco et al 2012 for further discussion). We stress that reliable population size estimates of common species, especially those subjected to exploitation, could be particularly relevant to determining the potential decline in numbers of individuals and the impact of depletion events on ecosystem functioning and the benefits that people obtain from biodiversity.…”

“…However, the reliability of predicted population numbers has been rarely tested by comparing them with 'actual' population size derived from direct counts. Also of concern is the fact that sophisticated computational procedures implemented to predict population size at large scales can generate biological unrealities that may be used to propose conservation measures (Blanco et al 2012). …”

“…In fact, carefully designed monitoring programmes can yield population estimates as reliable and accurate as possible (in study areas of variable size) when individuals forming populations can be directly counted (Bibby et al 2000, Sutherland 2006). This kind of baseline knowledge of 'actual' population sizes can subsequently be applied to validate and eventually calibrate the predictions of population size inferred from statistical models in the same areas (Blanco et al 2012).…”