Drone Research Workshop

Recent advances in drone technologies are offering exciting new perspectives for ecology and environmental sciences – for Team Shrub, drone research is an essential part of our work to understand how global change alters plant communities and ecosystem processes. We love hearing about how people from different disciplines are using drones to advance their research, and the visit of our fellow Team Shrub member Jeff Kerby was the perfect occasion to organise an afternoon full of drone science!

Kicking off our drone afternoon was Jeff’s Global Change Seminar talk, titled “Phenology in a changing Arctic: From individuals to landscapes”. Jeff’s talk demonstrated the value of long-term ecological monitoring of both plant phenology and large herbivores. By studying how plant and herbivore communities vary through time, Jeff is offering insight into how changing environmental conditions reflect on how those communities are expressing their phenology across the landscape. As the level of asynchrony between plants and herbivores increases, caribou calf production decreases. For muskox, however, there was a less clear pattern.

It was particularly interesting to think about the trade-offs that occur as a result of the effect of global change drivers on life histories – if plants emerge too early, there are higher chances they will encounter bad weather conditions which may compromise their growth; on the flip side, those early emerging plants will have a longer growing season. Thinking about foraging ecology, opportunistic animals can track “greening signals”, but what is causing greening across the landscape to begin with? Snowmelt, thawing degree days and temperature could all be linked with the changes in plant communities we are observing. An exciting question then becomes whether the greening is propagating at a herbivore-relevant scale.

When trying to disentangle the mechanistic drivers of phenology changes on a biome scale, it becomes a challenge to tie dynamics across time and space – how can we link patterns in satellite observations and on the ground measurements? Does the scale at which we are observing these changes bias our observations? This is where timelapse cameras and drones come (fly) in! “Computer vision” can offer further insight – for example, we can use computer vision to count flowers in drone-acquired imagery.

Building up on Jeff’s great talk, we then found out about  a wide range of drone-facilitated research, as part of our Drone Research Workshop. Here at the School of GeoSciences, we benefit from the excellent NERC recognised Airborne GeoSciences facility.

In line with the Arctic-oriented start of our drone afternoon, Isla presented about the ShrubTundra Project, which aims to quantify the role of climate as a driver of tundra shrub expansion and tundra greening. An exciting development for drone researchers is the establishment of the Drone Ecology Network – a network of high-latitude ecologists using drones to answer ecological questions. The network will share methods, techniques and expertise to improve the collection of drone remotely-sensed data in tundra ecosystems and to enhance the comparison of data in future.

Jeff told us about another fantastic initiative – Conservation Drones, which seeks to share knowledge of building and using low-cost unmanned aerial vehicles for conservation-related applications with conservation workers and researchers worldwide, especially those in developing countries.

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We were thrilled to find out more about Andy‘s exciting recent participation in a workshop in Brazil, as part of a long-term experiment aiming to understand drought effects in tropical rainforests.

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Simon Gibson-Poole demonstrated a great diversity of drone applications – from monitoring the spread of Giant Hogweed to using drones in agricultural trials and disease management.

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Lizzie Dingle‘s talk took us to Nepal where she used drones to map river channels in the foothills of the Himalayan Mountains. Lizzie also gave us very useful insight into what some of the challenges of drone fieldwork are, particularly in remote fieldsites.

Paige dePolo used drones in her Master’s research to collect bedding plane scale photogrammetric datasets for dinosaur footprints located on intertidal platforms on the Isle of Skye.

Zhaoliang Hou talked about his plan  to test the possibility of UAV mapping in hilled areas.

Next up, Team Shrub’s honours student Arabella gave an excellent presentation about the patterns of tundra greenness and soil moisture. Arabella discussed how she assessed the correspondence between soil moisture distribution and vegetation greenness using drone data with different spatial grain.

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Our last talk of the afternoon took us to the Scottish Borders, where Kathryn Murphy used drone imagery and 3D modelling in the study of an overlooked archaeological site.

Visiting our “Arctic from Above” exhibition was an inspirational ending to our drone-filled day – Jeff got to see his exhibited work in person, and we all enjoyed going back to our photos of Arctic fieldsites and wildlife.

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Coding Club goes to Aberdeen and the Impact Awards

It’s been almost a year since we first started pondering the idea of a positive and supportive environment where we can all advance our skills in statistics and programming. We had a vision for a place where we can learn without the pressure of formal assessment, and with the ability to tailor our skills to our needs. For the last few months we have been organising weekly workshops and publishing the materials online on our website, and we are so happy to see Coding Club go from a vision to a real initiative! I, along with Team Shrub alumni John and a great group of PhD students, among which Sandra and Haydn, have been leading workshops on topics such as version control using GitHub, data visualisation, efficient data manipulation, and mixed effects modelling. The workshops are open for everyone to attend, from undergraduates to academic staff, and we are thrilled to have shared our enthusiasm (and sometimes frustration) for coding with people from different disciplines, including ecology, environmental science, geography, and biology.

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Inspired by the positive feedback from our workshops in Edinburgh, we were keen to make links with other people across Scotland that have undertaken similar statistics and programming initiatives. As I’m always curious to see how other people lead such workshops and wouldn’t want to miss a chance to learn something new, I attended the “Data Archiving and Coding Workshop” at the BES Annual Meeting in Liverpool last December. Great things happen at coding workshops, among which the start of exciting new collaborations! Sitting at my table was Francesca Mancini, a PhD student from the University of Aberdeen, who was about to start a coding study group in her department. When I found out that this year’s Scottish Ecology, Environment and Conservation Conference will take place in Aberdeen, I immediately thought of Francesca, and thanks to great work and enthusiasm from her and our Coding Club team in Edinburgh, we organised Coding Club’s first joint workshop that took place just before the opening of the conference.

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With a room full of people keen to learn about efficient data manipulation and data visualisation, we set out to quantify population change based on the Living Planet Index database, and visualise species occurrence data from the Global Biodiversity Information Facility and Flickr. I have been fascinated with the creative use of social media data for conservation research ever since I heard Francesca’s talk in Liverpool, and I, along with the rest of the workshop attendees, were very keen to learn how to make density maps and examine how they differ depending on the data source – GBIF or Flickr. On the Edinburgh side of the workshop, we couldn’t resist an opportunity to share our love for tidy data and efficient workflows when tackling large datasets, like the LPI.

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Although we are teaching at Coding Club, the workshops and preparation of the online tutorials have very much been a learning experience for us as well. Thanks to our interactions with the people who attend the Coding Club workshops, we are learning so many new things, and will continue to improve our work. Some of those improvements even happened “live” during the workshop, when my compulsive desire to put spaces around every plus sign got in the way of the code running smoothly!

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I find it so inspirational when people come together to learn, especially when the material they are learning is often seen as scary and hard (and the dramatic R error messages sure don’t help!). We were very happy to meet new people from Aberdeen and are hoping to continue developing this collaboration through future joint workshops in both Edinburgh and Aberdeen.

Until then, you can find all of the materials from our workshop on the Coding Club website – “Working efficiently with large datasets.

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Shortly after our joint workshop in Aberdeen, we attended the Impact Awards at the University of Edinburgh, where Coding Club was shortlisted in the “Best Student-Staff Collaboration” category. After hearing about many wonderful initiatives improving student learning and experience at university, we left the ceremony with even more inspiration and drive to continue building the academic environment we dream of. We also left with a trophy, as Coding Club was the winner in its category!

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It was great to reflect on our Coding Club journey so far, and now we are very much looking forward to our future workshops and ideas on how to develop quantitative skills among students and staff. Whenever our own code doesn’t run (very often), and we see the same error messages that scare away our workshop attendees, we find motivation in the encouraging feedback of students and staff – we deeply appreciate the support we have received so far, and will continue developing Coding Club with much enthusiasm!

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By Gergana

Theory, meta-analyses and stylised facts in ecology

What is a theory? Is ecology theory-poor and if yes, why? What are the paths to theory development in ecology? Meta-analyses? Data syntheses? Big data? Stylised facts? These are the questions we set out to discuss during  this week’s lab meeting. We extended an invitation to EdGE (the EdEN discussion Group for Ecology) to get more diverse perspectives, and shared our thoughts on these topics, largely inspired by Dynamic Ecology’s posts about stylised facts in ecology and why meta-analyses in ecology often don’t lead to theoretical insight. We also added in Marquet et al.’s 2014 paper “On Theory in Ecology” into our discussion, bringing forward many thoughts on the different types of theory in ecology, and whether theory in ecology is possible to begin with.

We defined theory as a hierarchical framework of postulates, based on a number of assumptions, and leading to a set of predictions. As we set out to do our research, we can use theory as the base on which you build your hypotheses – and if you find enough support for your hypotheses, in time they might grow into a theory, thus prompting more hypotheses – a self-propelling cycle of gathering empirical evidence and developing theory. But is the cycle broken, with empirical evidence (or its synthesis) becoming an endpoint that prompts little theoretical insight?

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We had a mix of undergraduates, PhD students and PIs in the room, and it was interesting to see how our thoughts varied based on our career stage. We started off with a quick quiz on 1) whether we had heard of the theories covered in the paper before, and 2) whether we had thought deeply about them. Here are the results!

How do we find out about theories in ecology to begin with? It was interesting to note that at least in the ecology curriculum here at the University of Edinburgh, most theories are taught pretty late (3rd and 4th year), and many don’t make it into the curriculum to begin with. How do we decide which theories are worth teaching about? Linking back to Marquet et al. 2014, should we be focusing on teaching the most efficient theories? Should we teach ecological theories in year 1?

From our experience, a lot of ecologists don’t like to think about theory too much – after all, ecology is so complex, are generalisations even possible? Some might say yes! We did, however, wonder what is the role of theory in ecology, if it seldom holds true across organisms, ecosystems, biomes. But then again, theories don’t need to be always right to be useful. Neutral theory, for example, can be thought of as a strawman idea that has spurred many interesting discussions (and research) on how reality differs from the simple pattern described by the theory.

We thought that while theories can be useful, a really strong emphasis on theory can bring you astray – stuck in mathematical equations and too far from the real world. According to the undergraduate participants in our discussion, theories are great for conceptualising ecological processes and thinking about how patterns can be generalised across time and space. We then discussed the difference between meta-analyses and data syntheses, with our group being predominantly being in preference of data syntheses – perhaps they are one of the paths towards the development of more ecological theory. Has that happened in the past? Yes! We used species-area curve relationships  that led to the development of the Island Biogeography theory as an example.

So why isn’t there more ecological theory? We thought of a simple answer – ecologists like to hang out outside. We briefly imagined what first year ecology students would say if when they showed up for the Field Ecology course, where you get to run up and down the Pentland Hills and collect data, we tell them that instead, we will be staying inside, thinking, doing lots of maths, and learning how to develop theory. Most of us went into ecology because we love the natural world and want to 1) learn more about it, and 2) experience it relatively often.  Fieldwork is the highlight of ecology for many of us (though for some of us it’s a tie between fieldwork and coding!), and that, together with all the noise in our data and the many complexities of our field, makes us less likely to engage deeply with theoretical work. Finally, most of us are not exposed to much math, especially at the start of our careers, which again makes it hard to think about how we can turn empirical evidence into theory.

Nevertheless, we are jealous of evolutionary biology, where theories abound! We talked about why that is, reaching the conclusion that theory prompts more theory – because in evolutionary biology there is one major unifying theory, other theories can quickly follow from that – a self-propagating cycle.

Are ecologists too critical? For every theory that tries to make its way, there most probably be someone who says that doesn’t apply to their study organism/system. We thought that we shouldn’t expect theories to always be true, instead we should use them as a stepping stone to build our future work.

Coming back to stylised facts, which may or may not lead to theory, we went around the room and each thought of a stylised fact from our field:

  • Plant growth is more temperature sensitive in wetter vs. drier sites (Soil moisture hypothesis, Myers-Smith et al. 2015Ackerman et al. 2016)
  • Biotic interactions shift from negative to positive with increasing environmental severity (Stress gradient hypothesis, Bertness and Callaway 1994)
  • Negative frequency dependence driven by higher trophic levels can maintain diversity (Paine 1966 and the Janzen–Connell hypothesis)
  • Phenology responses to global change drivers are stronger at lower throphic levels than higher (Thackeray et al. 2016).
  • Decomposition has a saturating relationship with temperature (e.g., Sierra et al. 2015).
  • Bigger and older trees are more prone to damage, increasing fungal infection rates (Basham 1958).
  • Plants with bigger foliar volume have more biomass (Greaves et al. 2015Cunliffe et al. 2016).
  • Remotely-sensed plant attributes can’t be accurately estimated at scales finer than the individual level (Cunliffe et al. in prep).
  • Big trees suffer more than little trees in rainforests experiencing drought (Rowland et al. 2015).
  • As the trait diversity of plant communities increases, so does the resource usage efficiency (Lasky et al. 2014).
  • Things that grow fast rot fast (Cornelissen et al. 2007).
  • The effect of agri-environment schemes is moderated by landscape complexity (e.g. Concepción et al. 2008).
  • The effectiveness of conservation interventions is proportionate to the ecological contrast they create (or their additionality) (e.g. Maron et al. 2013).

We finished our discussion where we started – at the definition of what stylised facts are, and whether there is one universal definition – thus showing that ecologists do care about generalisation!

The role of β-diversity in conservation

What indicators should we use in conservation? Why do different biodiversity indicators seem to disagree? What is the role of beta-diversity in conservation? This week we extended our usual TeamShrub lab meeting to hold a discussion on two recent biodiversity papers, as part of the EdEN (Edinburgh Ecology Network) EdGE (EdEN Discussion Group for Ecology) meetings. We talked about what are the best indicators to assess biodiversity change, whether there is a place for β-diversity metrics in guiding conservation actions, and why do different indicators of biodiversity change seem to disagree with one another.

We all had an interesting and jolly discussion, inspired by the following papers:

Socolar, Jacob B., et al. “How should beta-diversity inform biodiversity conservation?.” Trends in ecology & evolution 31.1 (2016): 67-80.

Hill, S. L.L., Harfoot, M., Purvis, A., Purves, D. W., Collen, B., Newbold, T., Burgess, N. D. and Mace, G. M. (2016), Reconciling Biodiversity Indicators to Guide Understanding and Action. CONSERVATION LETTERS, 9: 405–412. doi:10.1111/conl.12291

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As we work in the Arctic, we appreciated how the papers recognised the fact that regions which are not particularly rich in biodiversity still deserve to be on the conservation radar.

We started off by identifying what β-diversity is and how we measure it – we discussed temporal β-diversity (how has species composition changed through time) and spatial β-diversity (commonly known as just beta-diversity, how do communities differ across space – i.e. measures of similarities, etc.) and what are the implications of using β-diversity metrics in conservation. We can mostly agree that one of the goals of conservation is to maximise biodiversity, but what diversity? Alpha, beta, gamma?

Unlike α-diversity (diversity at the local scale) and γ-diversity (diversity at the global scale), β-diversity does not refer to a spatial extent, but to the comparison between communities, and as such is is often used as an indicator of biotic homogenisation.

Calculating β-diversity allows us to understand biodiversity loss from a different perspective – we can look beyond species richness increasing or decreasing, and think about whether communities are becoming more similar, and what the implications of that might be for ecosystem functionality and the provision of ecosystem services. Nevertheless, β-diversity has to be used carefully – if two communities are both changing, β-diversity might stay the same (i.e. they might still have the same amount of species in common), but their current species composition might have changed. We also discussed how increasing the spatial extent of agri-environment management (or other conservation measures) might not always have the desired outcomes – such actions might decrease β-diversity by favouring the same set of species over large spatial extents. Communities can shift in many ways, which don’t necessarily fit in the biodiversity loss toolbox we most often use.

Can we use beta-diversity to link local scale observations to global scale inferences on biodiversity trends?

We thought that this is theoretically a great idea, but logistically, there are difficulties in going from the local scale observations to inferences on γ-diversity – gaps in the data, understudied regions, etc. We also pondered the dangers of promoting rare species at the expense of common species, and also what about disturbance-tolerating species? It is easy to say that e.g. Plot1 has lost/gained one species, but hard to have confidence in how the world has changed over time. Perhaps it is β-diversity that will help us link our local-scale observations to inferences on the global scale.

By Gergana

 

Our BES Annual Meeting highlights

Christmas arrived early for Jakob and I – we attended the British Ecological Society Annual Meeting in Liverpool at the start of December and got to enjoy the jolly and festive atmosphere of hundreds of ecologists keen to share their research. Having just wrapped up Coding Club for 2016, it seemed very appropriate to start the BES conference with their Best Practices for Code Archiving workshop. I was very keen to learn more about code archiving, but I also wanted to see how other people teach coding and organise workshops. I will be leading a GitHub and version control workshop for Coding Club soon, and I’m looking forward to sharing the knowledge and skills I gained at BES with the Coding Club members.

czacjgzwiaalapbThe Coding workshop communicated a great message – writing reproducible code and archiving it is not hard. I wouldn’t say it’s easy, but it’s certainly not hard, either, and it’s something we all could (should) do. I particularly liked this graph, as it conveys what we’ve been trying to tell Coding Club members (and ourselves) – little investments in learning good coding practices can deliver big benefits. It’s even better if there is a community around you which is also keen to learn. When I was wrapping up my dissertation, I was feeling a bit intimidated by Markdown and decided that I couldn’t learn it in a day (since the dissertation was due the following day). This year, I went to a Markdown workshop led by PhD students from the Australian National University, and after and hour, I could make a beautiful report of my code and results. It was great to see students pick up Markdown quickly at the Coding Club workshop, too – if you are keen to learn it as well, check out our online tutorial here. Similarly, syncing RStudio with GitHub doesn’t take long, and is a great way to keep track of your code and its many versions (you can check out Coding Club’s Github tutorial here).

There were many great talks in the following days, and I was particularly impressed by the PhD talks. It was so interesting to learn about Francesca Mancini‘s interdisciplinary conservation research on how social media images can be used to infer eco-tourism hotspots – and good to know that my photos on Flickr could have been used for science! Sarah Scriven gave a very well presented talk on butterfly movement through oil palm plantations (and in the spirit of #BEScode, the data and code are publicly available). Great to highlight not just connectivity between fragmented landscapes, but also functional connectivity – even if butterflies can move through agricultural land, their larval host plants might not occur there, thus preventing breeding.

czjqnpewiaa8hnmThe conference was great at prompting me to think about topics that hadn’t crossed my mind before – for example, whether mountain bikes are good at seed dispersal, and what implications that might have for plant colonisation and perhaps even the spread of invasive species. Prof Anne Chao delivered a fantastic plenary talk on biodiversity estimators and rarefaction, from which we all learned a lot, and I’ve put down exploring the R package, iNEXT, as a reward for after I’ve finished the first draft of my manuscript. You can also check out their Shiny app online, where you can upload your own data and get plots and values for the different biodiversity estimators. I also got to meet Prof Chao at the Meet the Speaker session after the plenary talk, which only inspired me further for biodiversity analyses.

Chatting with keen ecologists over lunch was super fun (and the food was tasty, too!), the Science Comedy Slam was hilarious, and in general we loved the dynamic of the whole conference – we came home inspired and thankful that we get to be a part of the ecology research community.

By Gergana and Jakob