Summary
Changes in natural patterns of animal behaviour and physiology resulting from anthropogenic disturbance may alter the conservation status of a population if they affect the ability of individuals to survive, breed or grow. However, information to forecast population‐level consequences of such changes is often lacking.
We developed an interim framework to assess the population consequences of disturbance when empirical information is sparse. We show how daily effects of disturbance, which are often straightforward to estimate, can be scaled to the disturbance duration and to multiple sources of disturbance.
We used expert elicitation to estimate parameters that define how changes in individual behaviour or physiology affect vital rates and incorporated them into a stochastic population model. Model outputs can be used to evaluate cumulative impacts of disturbance over space and time. As an example, we forecast the potential effects of disturbance from offshore wind farm construction on the North Sea harbour porpoise (Phocoena phocoena) population.
Synthesis and applications. The interim framework can be used to forecast the effects of disturbances from human activities on animal populations, to assess the effectiveness of mitigation measures and to identify priority areas for research that reduces uncertainty in population forecasts. The last two applications are likely to be important in situations where there is a risk of unacceptable change in a species' conservation status. The framework should, however, be augmented with empirical data as soon as these are available.
Summary
1.Behavioural change in response to anthropogenic activities is often assumed to indicate a biologically significant effect on a population of concern. Disturbances can affect individual health through lost foraging time or other behaviours, which will impact vital rates and thus the population dynamics. However, individuals may be able to compensate for the observed shifts in behaviour, leaving their health and thus their vital rates and population dynamics, unchanged. 2. We developed a mathematical model simulating the complex social, spatial, behavioural and motivational interactions of coastal bottlenose dolphins (Tursiops truncatus) in the Moray Firth, Scotland, to assess the biological significance of increased rate of behavioural disruptions caused by vessel traffic. 3. We explored a scenario in which vessel traffic increased from 70 to 470 vessels a year in response to the construction of a proposed offshore renewables' facility. Despite the more than sixfold increase in vessel traffic, the dolphins' behavioural time budget, spatial distribution, motivations and social structure remain unchanged. 4. We found that the dolphins are able to compensate for their immediate behavioural response to disturbances by commercial vessels. If the increased commercial vessel traffic is the only escalation in anthropogenic activity, then the dolphins' response to disturbance is not biologically significant, because the dolphins' health is unaffected, leaving the vital rates and population dynamics unchanged. 5. Our results highlight that behavioural change should not automatically be correlated with biological significance when assessing the conservation and management needs of species of interest. This strengthens the argument to use population dynamics targets to manage human activities likely to disturb wildlife.
This paper introduces a fast algorithm for randomized computation of a low-rank Dynamic Mode Decomposition (DMD) of a matrix. Here we consider this matrix to represent the development of a spatial grid through time e.g. data from a static video source.DMD was originally introduced in the fluid mechanics community, but is also suitable for motion detection in video streams and its use for background subtraction has received little previous investigation. In this study we present a comprehensive evaluation of back-
Appropriate management of the effects of human activities on animal populations requires quantification of the rate at which animals encounter stressors. Such activities are heterogeneously distributed in space, as are the individual animals in a population. This will result in a heterogeneous exposure rate, which is also likely to vary over time. A spatially explicit analysis of individual exposure is therefore required. We applied Bayesian spatially explicit capture-recapture models to photo-identification data to estimate the home range of well-marked individuals in a protected coastal population of bottlenose dolphins. Model results were combined with the estimated distribution of boat traffic to quantify how exposure to this disturbance varied in time and space. Variability in exposure between individuals was also investigated using a mixed-effects model. The cumulative individual exposure to boat traffic varied between summers, depending both on the overall area usage and the degree of individual movement around the activity centres. Despite this variability, regions of higher risk could be identified. There were marked inter-individual differences in the predicted amount of time dolphins spent in the presence of boats, and individuals tended to be consistently over-or underexposed across summers. Our study offers a framework to describe the temporal, spatial and individual variation in exposure to anthropogenic stressors when individuals can be repeatedly identified over time. It provides opportunities to map exposure risk and understand how this evolves in time at both individual and population levels. The outcome of such modelling can be used as a robust evidence base to support management decisions. bs_bs_banner Animal Conservation. Print
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