Assessing biological realism of wildlife population estimates in data‐poor systems

Abstract

Summary Large carnivore management is often contentious, particularly in jurisdictions where hunting and conservation efforts collide. Regulated hunting is a common management tool, yet relevant decisions are commonly taken in the absence of reliable population data and are driven by factors other than biological considerations. We used European large carnivore (brown bear Ursus arctos, wolf Canis lupus and Eurasian lynx Lynx lynx) management to evaluate the biological plausibility of reported population estimates used in hunting decisions. We used Romania as a test case as this region is not only data‐poor, but the public and private game managers are beneficiaries of revenue from hunting activities. We assessed the following: (i) how population growth rates calculated from reported abundances between 2005 and 2012 compared to published growth rates empirically derived from European and North American populations; (ii) whether biological unrealism compounded through time by testing whether reported estimates fell within the bounds of biologically plausible trajectories; and (iii) the relationship between the occurrence of biologically unrealistic estimates and financial incentives (amount of hunting). For U. arctos, which generates high revenue, estimated annual population growth rates were frequently greater than maximum published growth rates (up to 1·5 for reported versus 1·136 in the literature). Reported estimates were greater than maximum simulated populations in 32% of cases, and the difference was positively correlated with hunting (rs = 0·576). Population growth rates for C. lupus overshot the maximum published growth rate (1·35) less frequently, reported estimates were within the bounds of biologically plausible estimates (91% of cases), and there was a weak correlation between hunting and biologically unrealistic estimates (rs = 0·182). L. lynx population growth rates derived from reported estimates were lower than minimum simulated populations (60% of cases), and there was a weak correlation between hunting and biologically unrealistic estimates (rs = 0·164). Synthesis and applications. Our study suggests that comparing population estimates used by management agencies to demographic data obtained through rigorous peer‐reviewed studies is a useful approach for evaluating the biological plausibility of wildlife data in data‐poor systems, especially when management decisions might be influenced by non‐scientific incentives.

Political populations of large carnivores

“…In contrast, growth rates implied by government population estimates for less commercially valuable species (wolves [ Canis lupus ]; Eurasian lynx [ Lynx lynx ]) rarely exceeded maxima in the literature (Popescu et al. ). This suggests the potential inflation of population sizes of brown bears may not be a function of limited scientific capacity or error, rather, it may be deliberate to justify a politically profitable policy.…”

“…Evidence for political populations is emerging in scholarly scrutiny of government reporting on wildlife population sizes, trends, and associated policy. For example, Popescu et al (2016) estimated that the Romanian government's population estimates for brown bears (Ursus arctos)-the most profitable trophy species in the country-require annual growth rates of up to 50%. This growth rate contrasts sharply with the highest ever reported for the species globally (8% [95% Confidence Limit 3.2-13.6]) (Hovey & McLellan 1996).…”

Bounding reproductive rates in state‐space models for animal population dynamics

“…We have modified a Gompertz state‐space model so that annual growth rates are forced to be smaller than a maximum growth rate determined from biological knowledge (Popescu et al. ). By excluding biologically unrealistic growth rates, the model can aid in the separation of process variance and observation variance, one of the key challenges in the application of state‐space models to time‐series data (Dennis et al.…”

Mainstreaming human and large carnivore coexistence through institutional collaboration

“…For example, the disciplines of ecology, geography, and statistical modeling can yield robust results on the population dynamics of large carnivores (Popescu et al. ), but these results may be perceived with skepticism by other sectors (e.g., wildlife management, as happened in Romania; T.H. & L.R., personal observation).…”