The Sutherland & colleagues article is an interesting paper that is a “horizon scan” of conservation issues that are likely to become increasingly important. After I read this paper, I realized that this is an ongoing series that gets regularly updated so I’ll find the latest and review that as well. The 2010 paper is
Sutherland, W. J., et al. (2010). “A horizon scan of global conservation issues for 2010.” Trends in Ecology & Evolution 25(1): 1-7.
They sent out surveys to conservation biologists and put together the top topics. They were:
- microplastic pollution – only 5% of plastics are “recovered” – does that mean recycled? Either way, that’s depressing
- nanosilver in wastewater – I never heard of this but nanosilver particles are used extensively in manufacturing and can eventually end up in aquatic invertebrates where there is some evidence of causing deformities
- synthetic meat – bacteria can be used to produce meat fibers (assuming that’s actin and myosin – not sure about myoglobin). This will be a conservation that if cattle and pigs are replaced by synthetic meats. Thing is, you still need to feed bacteria. There is no free beef lunch. Maybe the efficiency of bacteria are better and that would reduce cropland
- artificial life – this is not killer robots but synthetic microbes and the worry is their effect when released into the environment
- stratospheric aerosols – these particles have a cooling effect on climate and might be used to offset global warming. Problem is they also cause acid rain and, combined with increasing carbonic acid in oceans, will cause problems in the oceans
- biochar – is charcoal that’s placed into the soil. The carbon footprint and effects on soil has not been well studies despite the expansion of the use
- mobile-sensing technology – we will be able to understand much more about organisms and the environment with all the apps available but will take some organizing
- deoxygenation of the oceans – I think this one is obvious why this is a problem
- changes in denitrifying bacteria – we’re putting nitrogen into the oceans and it is changing the nitrogen cycle and often in counter-intuitive ways. Given everything starts with nutrients in the ocean, this one concerns me the most
- high latitude volcanism – this was news to me – there’s lots of volcanic activity (not necessarily volcanoes) around the poles and as we remove the overlaying ice and snow the gases released will likely affect climate
- invasive lionfish – holy cow, they report that lionfish remove up to 80% of coral fishes where they are introduced. Ugh. I saw two in Belize while snorkeling (see photo below) and this was the only species that was allowed to be hunted in the marine sanctuary and for good reason.
- opening of the Arctic – as the ice retreats in the Arctic more organisms will be able to move across continents
- assisted colonization – there are now several cases of humans moving organisms towards the poles to help them adjust to climate change but the effect of these introductions may not be and cannot be fully understood
- sacrificing nonforest biomes – the UN is promoting the preservation of forests to mitigate climate change but perhaps at the expense of other sensitive and ecologically important biomes such as mangroves and savannas
- large scale foreign land acquisitions – large plots in Africa and South America are being purchased by foreign agents and locals have little to say about the use of that land
These are some hefty issues for the planet. It will be interesting to see the updates.
A side note – I record everything I read in Endnote by adding the keyword read and the year. I just searched read2018 and not a single damn paper. Hard to believe but I think I skimmed a bunch. So 2019 is starting out great with three papers! I don’t include manuscripts I reviewed (three of four of those). I started an Endnote folder called “Blog it” for papers I need to review for my own benefit. The three papers so far haven’t been part of that folder and there are currently 421 entries to get to. No pressure.
The paper I just finished was
Creer, S., et al. (2016). “The ecologist’s field guide to sequence-based identification of biodiversity.” Methods in Ecology and Evolution 7(9): 1008-1018.
I thought there would be more tidbits for me but the paper was focused on soil and water sampling. A good read nonetheless to help me converse with my colleagues and to think about ecological communities as functional organisms and genes rather that just plants and birds.
And now on the monster that is the book..
Gearing up to start the Wood Thrush report for the PA Game Commission and digging into the literature. The two papers I just read were:
Kellner, K. F., et al. (2018). “Local-scale Habitat Components Driving Bird Abundance in Eastern Deciduous Forests.” The American midland naturalist 180(1): 52-65.
Ruhl, P. J., et al. (2018). “Characterization of Worm-eating Warbler (Helmitheros vermivorum) breeding habitat at the landscape level and nest scale.” Avian Conservation and Ecology 13(1).
The Ruhl paper on Worm-eating Warblers looks to be a subset of the data presented in Kellner et al. Both are out of Purdue, which is pumping out great ecological papers.
Both use the latest-greatest in analyzing point count data (where you stop at particular distances and count all birds – in their case every 150 m) by using Bayesian methods and incorporate detection probabilities (the probability that you discover a bird that is actually there). They throw a number of landscape variables at abundance data. They used some sophisticated (for me) methods to extract landscape data that I will need to learn. I have used R to many analyses but not really get landscape information from maps. It will be an adventure.
The detection probabilities ranged from 0.08 to 0.83. The detection probability of 0.08 was associated with Brown-headed Cowbird (BHCO), indicating a bird that is more widespread than what encounters would indicate. BHCO is a brood parasite and not territorial so I wonder how that affects the estimates. Interesting compared to my point counts which had many BHCO. On the other were Eastern Wood-Pewee and Ovenbird – which sing consistently during the breeding season.
Canopy height , elevation, and slope were the most important variables for many species – but not Wood Thrush (WOTH). Midstory stem density and slope were most important for WOTH . This species preferred sites with steeper slopes and more open midstory.
Just a word of caution. I worry in using the word “important” for variables and using random sites to find what’s important. If a has a strong relationship to an environmental variable but the value of that preference is centered on the average then that variable might be interpreted as not being important at all. The average value of a variable is entirely dependent on the choice of habitats selected. So, for example, this study only included forested sites but if they had included clearcuts or floodplains then the average would shift and, perhaps, other variables would become important.
This weekend I am tasking myself with figuring out how to download spatial imagery from GloVis and extract land use information from where we are monitoring nests and examining occupancy. A map from GloVis is not just a pretty map – it is a data array of pixels that represent land use. Each 30 m square pixel is coded by one of several states that represents land use. In map speak this type of map is called a raster. The alternative is to have a map composed of lines and shapes.
We’ll plop our points on the map and use those locations as centers of circles within which we will figure out how much of that circle is urban or forest or something else. I’ll do this in R using the package raster and probably a function called extract. The process is about the same as the less precise way of asking yourself how urban a place is by walking around the neighborhood. How large the circle is up for debate but a smaller circle (say 100 m radius) would be what you see as you looked around you. A kilometer around a point would be what you would see on a short walk. If you think about what happens at a nest – it hatches or not – then you might understand why the buffer size is not known. A nest predator, like a Cooper’s Hawk, might have a large territory but its searching behavior might be affected by vegetation directly around a nest.
My plan is to include two measures so we can compare local versus landscape variables because both are probably important – maybe. I’ll use logistic regression to build the models. Logistic regression looks at binary data (in our case fledge or not) and examine the effect of our chosen variables.
Anyway, here’s your reward for visiting: Wood Thrush chicks.