CSEE 2017 Highlights

This year the ecoblender lab attended CSEE 2017. The conference was great and covered four days of talks, workshops, and networking events. I attended a free workshop that taught some basics in mapping spatial data and different packages to use in R. There was also a wide range of talks that mostly seemed interdisciplinary. This included discussions of uncertainty in ecology, estimate the value of natural resources, and developing models of habitat selection. Here are some of the highlights I took away from the conference:

Modelling:

There was discussion over the usage and power of mechanistic vs. phenomenological models. This is a topic discussed often in ecology (see of that discourse here), but can be defined here as:

mechanistic: includes a process (physical, biological, chemical, etc) that can be predicted and described.

phenomenological: Is a correlative model that describes trends in associated data but not the mechanism linking them.

The discussion mostly described the relationship between phenomenological and Mechanistic models as not binary and rather a gradient of different models that describe varying amounts of a particular system. However, it did touch upon models such as GARP and MaxEnt that are often used for habitat selection or SDM but neglect the mechanism that is driving species occurrence. Two techniques I would like to learn more about are Line Search MCMC and HMSC which is a newly developed method for conducting joint species distribution models.

Camera traps:

There was also a morning session that described benefits and tools for using camera traps. These sessions are always great as they give a chance to see some wildlife without disturbance. Topics focus around deer over abundance harming caribou populations, how wildlife bridges do not increase predation through the Prey-Trap Hypothesis and techniques for using wildlife cameras or drones. One talk that was particularly interested used call back messages when triggered to see how animals respond to noises such as human’s talking or a mating call.

One of the more useful things I believe to have taken out of the session is how to estimate animal abundance and movement when the animals in your camera traps are unmarked. One modelling technique using Bayesian modelling and was found to be equivalent to genetic surveys of animal fur for estimating animal abundance. This is in contrast to the more frequent spatial capture-recapture (SCR) methods that either mark individuals or supplement camera trap data with other surveys. I also discovered there the eMammal project at the Smithsonian that is an Open Access project for the management and storage of camera trap data.

Ecology and climate change:

Climate change as always is a big topic at these conferences. There was a good meta-analysis out of the Vellend lab that show artificial warming of plant communities does not result in significant species loss. However, there was evidence that changes in precipitation does significant impact plant communities. The results are very preliminary, but I look forward to seeing more about it in the future. I also liked a talk that is now a paper in Nature that models networks in the context of climate change. The punchline of the results being that species composition in communities is dependent on dispersal, and high dispersal rates can maintain network structure although members of the community may change.

I presented results from our upcoming paper modelling positive interactions in desert ecosystems:

Overall I learned a lot from the CSEE 2017 conference and thought it was a health balance of size and events. Victoria was also a great city and made hosting the conference very easy. Next year it will in the GTA and I plan on connecting with the organization committee to potentially host an R workshop at the beginning of the conference. Until then!

ESA 2016 – my highlights

Functional traits

I have known for a while that functional traits are at the core of ecology. Unfortunately, for most of my experiments I focus solely on biomass and abundance. However, at ESA this year I noticed many researchers who measured community abundance and used a secondary database such as TRY for extracting functional traits per plots. This is a great re-purposing of already collected data to be reused to answer different questions. I am definitely going to consider analyzing data sets I currently have the species composition for to answer questions about functional diversity rather than typical species richness.

functional traits

Statistics

There was a considerable amount of NMDS usage this year, furthering that ecological analyses are becoming more complicated and requiring ordinations. Although ecologists may love NMDS, there is a preference in the statistical world to avoid it. I won’t get into the pros and cons here, but I believe ordinations such as PCoA, CA and RDA can accomplish the same as NMDS with less limitations. I will need to explore this further but I found this document a good starting point. Permuted ANOVAs were also another particularly popular statistical test and one I need to find a good R package for.

Another great talk from the conference discussed the advantages of the Negative Binomial distributions particularly for species abundance distributions. The talk discussed the tendency to fit discrete count data into log-normal distributions or Poisson. Often these distributions do not fit the data, while negative binomial does. The author A. Rominger promised me that he would be publishing an article detailing this commonality later in the year. I will hold him to that! In the mean time, here is an R package that he developed for species abundance distributions and the negative binomial distribution called pika.negative binomial distribution

Species distribution modeling

I had the opportunity to sit in on a talk by C. Merow that discussed used “expert maps” to further refined predictions of species distributions. It was a great talk and introduced a new concept to refine species predictions. Using the Map of Life (MOL), ecologists create species boundary maps that are would go into an SDM. The maps are compatible with MaxEnt and were shown to be effective at better predicting species occurrence. While a much better technique, I think the major limitation is that specific species will not have these maps delineated yet. However, until MOL catches up, big picture questions can be addressed with a greater degree of accuracy. The talk also reminded me I need to learn more Point Process Poisson modeling

The other instance SDMs that I thought was extremely informative was by Leung discussing co-occurrence models for invasion. This models have strong similarities with our work except instead of testing how an invasive species co-occurs with native species, we are trying to determine how a facilitating benefactor species interacts with neighbouring species. The way this is done is either using a proxy measurement or by using multi-species models. The example Leung used for a proxy measurement was boat movement in Ontario as a function of invasibility for a particular non-native species. I though this was a great idea and something I will consider for my next SDM experiment. The multi-species models is something that was a bit more complicated and that I will need to explore further.

Species distributions

General

Overall ESA went well! The attendance appeared a bit lower than last year, but I felt I was still super busy. It was a great experience and I learned a lot more that the highlights I am listing here. We also received some great feedback on micronet on how to improve it and I go some ideas to develop an R package that hopefully satisfies everyone’s micro-environmental challenges. A full list of my participation at ESA below:

A test of the stress-gradient hypothesis including both abiotic stress and consumer pressure during an extreme drought year

How to Set Up Automated Sensors Arrays for Measuring Micro-Environmental Characteristics and Synthesize to Larger Scales

Microenvironmental change as a mechanism to study global change

The use of shrubs as a tool for re-establishing native annuals to an invaded arid shrub land

 

esa2016

Selecting a journal for submission, case study: Journal of Arid Environments is ‘hot’ for facilitation

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Preamble
We are currently working on a manuscript exploring the importance of microenvironmental conditions versus seed source for desert annual plants.  Plant facilitation is a central tenet of the paper, however, we are more focussed on plant-seed/seedling interactions and less on plant-plant interactions.  There are some confirmatory findings, i.e. that positive interactions are likely species-specific and that microenvironmental differences are important, but there are also some novel findings (teaser so you read the paper).  An exceptional collaborator did this research as part of her honor’s thesis project, and it is absolutely publishable and technically correct. This study adopted a similar protocol to a recent contribution from the ecoblender team in Austral Ecology but with different species and a different purpose (and in fact, it predates this publication and was the pilot for the protocol). However, it is sometimes a challenge to publish a good idea demonstrated empirically with either mixed results, a single protocol (i.e. controlled conditions and not field), repeated testing of previously published similar research, or limited in extent of capacity to explore either full range of variation or extensive sample sizes. I think this study is great, and it is so tempting to overinterpret because the idea is so attractive and I like it. Nonetheless, it is prudent to select an appropriate framing of the problem and matching journals for submission. In discussing the writing, we are also concurrently considering the outlet.
Here is the workflow we used in selecting the journal.
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Generalized journal-choice workflow
1. Write first-second-third draft.
2. Edit, repeat, and begin discussions on relationship to larger literature landscape and ideas.
3. Make a list of top journals that fit the scope of study to test hypothesis.
4. Check each journal for contemporary papers on topic to ensure that we are correct in estimate of fit/niche.
5. Check lit cited of current ms to see if certain journals are cited more frequently. Add to list and explore/rule out journals that we may cite frequently for big, specific ideas that are likely beyond out reach.
6. Make a list of journals entitled ‘journal pipeline’ recognizing and reminding ourselves that rejection is part of the process and beneficial. Remind again 🙂
7. Select journal.
8. Check lit cited within manuscript for journal citation matching patterns.**Rule of thumb – a good fit should have a few key papers cited from that journal. The rationale is NOT to ingratiate with editors, but to ensure that the current research offering matches previous/related research.  Some editors do however check the lit cited of submissions, and if not a single citation to a previous publication in that journal, can consider rejection for offerings that are outside her/his primary research expertise.
ratchet
Disclaimer: I am not a fan of ratcheting from higher-tier journals to lower. This wastes time all participants in the peer review process. Sometimes however, this is a disservice to my junior collaborators as we end up in lower-tier placements but waste less time. Efficiency-impact trade-off, but it is difficulty to predict handling times by perceived impact of journal. I also strongly advocate for OA journals and this also sometimes leads to non-ISI placements. I do recognize that we each have different career needs, but I am confident that strong work – regardless of journal -can be found online easily now and will capture interest.
Case study
Linking back to preamble that got me thinking of our collective workflow, that always include discussion within team, we generated a short list of three journals to consider.
PLOSONE
Journal of Plant Ecology
Journal of Arid Environments
I have enjoyed many, many papers from all of these journals. A cursory search of the lit cited, online offerings, and discussion indicates that all three are viable with some caveats.
PLOSONE – High impact, great visibility, open access, and reviewed for technically correct designs.  However, it is our collective opinion that this could be a stretch. There are many general plant facilitation papers, but we have a narrower scope.  Whilst reviewing for technical correctness only and not impact, PLOSONE is nonetheless very reductionistic in their experimental/result/analyses reviews.  I have had perfectly appropriately, well-designed experiments rejected. Never for impact reasons.  There is no perfect experiment, but PLOSONE is nonetheless handling a very, very high number of experiments and thus seeks substantiative experimental designs.
Journal of Plant Ecology – A solid, mid-tier ecology journal. Interesting papers on facilitation. More emphasis on ecology then we necessarily tackle in this particular ms, and we are also focussed on plant-seed interactions.  Seeds are the key life-stage in this study.
Journal of Arid Environments – I have read many papers over the years and always enjoyed.  Sometimes less ecological and lower impact relative to previous two options.
How to decide – In summary, all three are certainly viable with difficult probabilities to estimate associated with both acceptance rate and handling time. We decided to examine the following questions explicitly to move forward, and in doing so, found the perfect fit (and a surprise too).
1. In PLOSONE are there a few seed biology/ecology papers or ecotype/reciprocal common garden papers that are comparable in sample size and number of species tested?
2. In JoPE, are there any seed biology/seed ecotype papers or is it more plant focussed?
3. In J of Arid Envts, are there a few plant facilitation papers or seed ones?
Surprise
No other reason than assuming it was less ecological and more broad.  There were many perfect papers related to our topic and design in the Journal of Arid Environments!
Sample connectance publications 
Summary
Journal of Arid Environments is a great fit for this paper. Concerns include lowest IF, non-OA journal, and handling times.  We will keep you posted, but I thought it would be interesting to share how we approached submission of an interesting, well-executed experiment that is a mix of confirmatory and insightful findings.
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Additional info & collaboration invite: Nurse-plant effects on the seed biology and germination of desert annuals

Here is a nice simple study that we did in the lab this last Fall: http://onlinelibrary.wiley.com/doi/10.1111/aec.12144/abstract

Collaboration
If anyone is interested in doing the experiment again for their shrub-understorey system, please feel free to contact us.  The protocol is well explained in the paper, but we are happy to provide additional details. Furthermore, we do have 6 nice chambers that we can program to emulate contrasting conditions. If you do not have access to a set of chambers, we would love to collaborate and run a set of them for you this Fall, 2014. If you do have chambers, let’s all get together and run a globally replicated version of this experiment for lot’s of different species from different deserts.

Steps
1. Collect seeds from 5 different species of plants that are found both under shrubs in arid systems and in the open nearby. A total of 2000 seeds per species is recommended as a minimum.
2. Pop out hobo loggers (we used pro v2s) or comparable microenvironmental loggers and record at least a seasons worth of conditions under your shrub species and nearby in the open (non-canopied sites where your target species also occur).
3. Record plant densities at the end of that season.
4. Petri dish trials in chambers (reciprocal design) and Tz tests on seeds etc as described in the paper.

Additional info
Simplified data can be found on figshare here: http://bit.ly/seedbiol

 

 

 

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open effect

Ally Updates

Big week, finally submitted my systematic review: “A systematic review of the attractant-decoy and repellent-plant hypotheses: do plants with heterospecific neighbours escape herbivory?” to the Journal of Plant Ecology for review. Also submitted the pollen/green roof paper I’ve been working on as a co-author to Urban Ecosystems this week. Fingers crossed!

Let the review process begin…

 

 

Net interactions & climate

 

Exploring the importance of net interactions and a changing climate from a synthesis perspective. This is a was a great collaboration. We got together in the coldest, darkest place ever (Scotland in the winter), and we cranked it out.

Michalet, R., Schöb, C., Lortie, C. J., Brooker, R. W. and Callaway, R. M. 2014. Partitioning net interactions among plants along altitudinal gradients to study community responses to climate change. – Functional Ecology 28: 75-86.

accum zone Panmah

 

Bidirectional facilitation interactions publication out too

It is always a please to work with a large team. I had the good fortune and seeing many of the sites and doing some of the data collection. The alpine is magical. It is nice that plants interact up there (unless you go too high to the extreme perhaps : ).

Schöb, C., Michalet, R., Cavieres, L. A., Pugnaire, F. I., Brooker, R. W., Butterfield, B. J., Cook, B. J., Kikvidze, Z., Lortie, C. J., Xiao, S., Al Hayek, P., Anthelme, F., Cranston, B. H., García, M.-C., Le Bagousse-Pinguet, Y., Reid, A. M., le Roux, P. C., Lingua, E., Nyakatya, M. J., Touzard, B., Zhao, L. and Callaway, R. M. 2014. A global analysis of bidirectional interactions in alpine plant communities shows facilitators experiencing strong reciprocal fitness costs. – New Phytologist 202: 95-105.

Also, a commentary by another Canadian scientist:

McIntire, E. J. B. 2014. Being a facilitator can be costly: teasing apart reciprocal effects. – New Phytologist 202: 4-6.

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