Abstract

Theory recognizes that a treatment of the detection process is required to avoid producing biased estimates of population rate of change. Still, one of three monitoring programmes on animal or plant populations is focused on simply counting individuals or other fixed visible structures, such as natal dens, nests, tree cavities. This type of monitoring design poses concerns about the possibility to respect the assumption of constant detection, as the information acquired in a given year about the spatial distribution of reproductive sites can provide a higher chance to detect the species in subsequent years. We developed an individual-based simulation model, which evaluates how the accumulation of knowledge about the spatial distribution of a population process can affect the accuracy of population growth rate estimates, when using simple count-based indices. Then, we assessed the relative importance of each parameter in affecting monitoring performance. We also present the case of wolverines (Gulo gulo) in southern Scandinavia as an example of a monitoring system with an intrinsic tendency to accumulate knowledge and increase detectability. When the occupation of a nest or den is temporally autocorrelated, the monitoring system is prone to increase its knowledge with time. This happens also when there is no intensification in monitoring effort and no change in the monitoring conditions. Such accumulated knowledge is likely to increase detection probability with time and can produce severe bias in the estimation of the rate and direction of population change over time. We recommend that a systematic sampling of the population process under study and an explicit treatment of the underlying detection process should be implemented whenever economic and logistical constraints permit, as failure to include detection probability in the estimation of population growth rate can lead to serious bias and severe consequences for management and conservation.

Highlights

  • In its essence, management and conservation of wildlife populations are mostly aimed at affecting the rate and direction of population change over time

  • We present the case of wolverines (Gulo gulo) in southern Scandinavia as an example of a monitoring system with an intrinsic tendency to accumulate knowledge and increase detectability

  • Despite the strong population decline over time (63% reduction in population size in 20 years), the simulated monitoring system erroneously produced the image of an increasing population size for several years after the beginning of the monitoring process (Fig. 2), due to the fact that the count process was influenced both by the decreasing trend in population size and the increasing trend in the ability to detect the study species

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Summary

Introduction

Management and conservation of wildlife populations are mostly aimed at affecting the rate and direction of population change over time. Managers often aim at regulating populations, to ensure that the provision of those services can be sustained while balancing wildlife population persistence and human well-being (Murdoch 1994). In all these instances, an accurate and timely assessment of population trends over time is of obvious importance to any adaptive management system, as it provides crucial information on the system’s response to human actions (Keith et al 2011; Bunnefeld et al 2013)

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