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              <h1 class="">
      Population ecology, monitoring and management</h1>
              
      
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                          <p>Contact person: <a href="mailto:t.h.ergon@ibv.uio.no">Torbj?rn Ergon</a>&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;<br/>
Keywords: Nature management, Complex dynamic latent variable models, Stochastic structured population models, Decision theory and adaptive management, Efficient computation for model fitting&nbsp;&nbsp; &nbsp;<br/>
Research groups: Centre for Ecological and Evolutionary Synthesis (CEES), Integreat<br/>
Department of Biosciences, Department of Mathematics, Department of Informatics, Department of Technology Systems<br/>
&nbsp;</p>

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                          <p>Our natural environments are rapidly changing due to anthropogenic influence of land use, climate change, harvesting (e.g. fisheries), spread of invasive species and pollution. This has huge implications for human societies and sustainable development around the globe. To understand, predict, mitigate and adapt to such changes, we need good models for how natural populations increase and decline in space and time in response to environmental change or management actions. Such models involve complex interactions, temporal and spatial dependencies, and time-delays in demographically structured populations. We also need to make good use of existing data sources and make use of new technologies for population monitoring. We welcome proposals from candidates with a strong background in modeling and data science to work with quantitative ecologists (and collaborators from their own fields) to develop widely applicable models or methodologies, or to solve specific problems in monitoring, conservation and management of natural populations.</p>

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                          <h4>Topics from methodological research:</h4>

<ul>
	<li>Hierarchical statistical (state-space) models with spatio-temporal covariance structures</li>
	<li>Stochastic structured population models</li>
	<li>Decision theory</li>
	<li>Machine-learning</li>
	<li>Efficient computation for complex model fitting</li>
</ul>

<h4>Topics from natural sciences or technology:</h4>

<ul>
	<li>Optimal management of harvested, endangered (red-listed) or invasive (black-listed) populations</li>
	<li>Control of infectious diseases (wildlife and zoonotic diseases)</li>
	<li>Adaptive management (https://en.wikipedia.org/wiki/Adaptive_management)&nbsp;</li>
	<li>Understanding and mitigating effects of climate change</li>
	<li>Citizen science (https://en.wikipedia.org/wiki/Citizen_science, https://www.citizenscience.gov/#)&nbsp;</li>
</ul>

<h4>External partners:</h4>

<ul>
	<li>The Norwegian Institute for Nature Research (NINA)</li>
	<li>Norwegian Veterinary Institute (NVI)</li>
	<li>Norwegian Institute of Bioeconomy Research (NIBIO)</li>
	<li>Institute of Marine Research (IMR)</li>
	<li>The Norwegian Computing Center (NR)</li>
	<li>Equinor ASA<br/>
		&nbsp;</li>
</ul>

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