Research in the time of corona

What a time? Who would have assumed such an unprecedented global disaster? I just hope that as many readers of this blog as possible have remained unaffected by the virus and can continue now in good health.

I was caught by the German lockdown in mid March when re-uniting with my family near Göttingen. Luckily I had just finished all my teaching a month earlier. Of course, all my conferences and scientific visits got cancelled as they were for most of us. On my way between Umeå and Frankfurt I travelled through ghost airports that were only marginally functioning… Glad that I made it in the end.

What was anticipated to be a month in Germany has become three months now, more or less in total isolation from people other than family. It has been a great time for the family to live through this crisis together, of course, and we have taken much comfort from being together.

Surely everybody felt the strange feeling of working from home without much external contact and the confinement of limited living and working space. It was nice to see colleagues from work in Zoom from time to time and to catch up, but otherwise I felt a bit like a monk working quietly in his cell and not to go much beyond the boundaries of the property. When things relaxed a bit, wearing masks in public has become a common habit now and we almost don’t even notice them any more.

Despite many lives lost everywhere, it has certainly been a convenient time to sit down and think about research and to finish some long-standing projects. Luckily research in forest biometrics and quantitative ecology is quite crisis proof: If you have the data, all you need is one or two computers. So I upgraded my home office a bit and simply cracked on.

I came to Germany with an almost finished research project on the spatial correlation between tree species and tree size diversity in highly diverse Chinese temperate woodlands. This topic has intrigued me for quite a while, as I believe the spatial correlation between tree species and tree size diversity is part of nature’s mechanism to maintain high levels of biodiversity. Understanding more about this relationship will allow us to mimic the natural maintenance of biodiversity and this is crucial to our efforts to stem the tide of worldwide biodiversity loss. I collaborated here with Gongqiao Zhang and Xiaohong Zhang from the Chinese Academy of Forestry.

Next I worked on a new principle of quantifying nearest-neighbour size inequality. The idea for this work spontaneously came to me when reviewing methods of modelling asymmetric growth in individual-based models. One of these methods used trigonometric functions and related to another method that was suggested by Oscar García in 2014. When I remembered this, I reached out to Oscar in Chile and we had a good email discussion on this new index, which I much enjoyed. Together with Janusz Szmyt from Poznan University of Life Sciences and Gongqiao Zhang from the Chinese Academy of Forestry we found that the new nearest-neighbour characteristic is a good indicator of spatial size inequality but is also highly correlated with the growth of the subject tree.

Then I considered the intriguing problem of applying modified approval voting to situations where a number of test persons are asked to mark trees for eventual eviction on a sheet of paper or on a tablet computer. This is a situation common in marteloscope research, where all trees of a forest stand are numbered. I reached out to colleagues at Technische Universität Berlin, Markus Brill and his team, and we figured that part of their voting research can be used to work out how a representative list of trees can be calculated as a synthesis of individual marks of a number of test persons. This is a new approach to crowdsourcing with a view to invite experts in a certain environmental field and synthesising their expert knowledge in a representative way through modified approval voting. Such quantitative croudsourcing is very useful whenever new ways in forest management need to be followed and no best-practice guidelines are available. We applied the novel method to 50 marteloscope data sets kindly provided by Jens Haufe from the Technical Development Department of Forest Research at Ae (Scotland, UK).

I much enjoy this interdisciplinary and international work and I am glad that through digitalisation it is still possible to reach out and collaborate despite Corona. There is so much to gain from this kind of cooperation. Somehow research has carried me through this time of change. Let’s just hope that things will have improved over the summer so that we can meet on campus again.

By Arne Pommerening

My background is in forest science with a PhD in forest biometrics (from Göttingen University (Germany) and a Habilitation in forest biometrics (from BOKU University Vienna (Austria). For eleven years I have been working in the fields of quantitative forest management and quantitative ecology at Bangor University (North Wales, UK) before working for a short while in Switzerland. Since 2014 I work as a Professor in Mathematical Statistics Applied to Forest Science at the Swedish University of Agricultural Sciences (SLU in Umeå and my research areas include woodland structure analysis and modelling, spatio-temporal dynamics of plant point patterns, individual-based modelling with a focus on plant interactions, plant growth analysis, methods of quantifying and monitoring biodiversity and the analysis of human behaviour of selecting trees. Much of my research is computer-based using simulation experiments and my research is strongly interdisciplinary and international.

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