JonathanTonkin Ecologist


As per the twitter #365papers hashtag, I am going to have a go at documenting my paper reading for 2016. I won’t necessarily do 365 papers but it’s a nice goal. I’ll add a sentence summarising the paper and sometimes a little more detailed notes.

  1. Beche, L., McElravy, E., Resh, V., 2006. Long-term seasonal variation in the biological traits of benthic-macroinvertebrates in two Mediterranean-climate streams in California, U.S.A. Freshwater Biology 51, 56–75. DOI:10.1111/j.1365-2427.2005.01473.x. Beche et al. looked at seasonal variability in one intermittent and one perennial Californian Mediterranean stream. There was considerable seasonal turnover, with distinct communities present between the two seasons - more evident in the intermittent stream. They showed that despite high seasonal variation in abundance and composition of benthic invertebrates, there was much less variation in the traits (i.e. greater seasonal stability). However, interannual variation in rainfall influenced the effect of seasonality within years. i.e. There was greater variation between seasons in wet compared to dry years.

  2. Review for journal.

  3. Dalby, L., McGill, B.J., Fox, A.D., Svenning, J.-C., 2014. Seasonality drives global-scale diversity patterns in waterfowl (Anseriformes) via temporal niche exploitation. Global Ecology and Biogeography 23, 550–562. DOI:10.1111/geb.12154. A look at global patterns in waterfowl diversity. Essentially shows that the mid-latitude peak in waterfowl diversity is a function of temporal niche exploitation. The areas with richness peak were dominated by migratory species in both breeding and non-breeding seasons. This reflects shifting environmental conditions, i.e. intra-annual variability and seasonal productivity. Previous work (Hurlbert and Haskell, 2003) demonstrated North American birds track plant production similarly in both breeding and non-breeding seasons - exploiting temporally available niches. Hurlbert and Haskell (2003) also found the greatest number of migrants with the largest seasonal shifts in productivity. This also backs up early predictions (e.g. MacArthur, 1959; Herrera, 1978) that the most seasonal environments (those with the greatest difference in productivity between seasons) will support the highest number of migrants.

  4. Bogan, M.T., Lytle, D.A., 2011. Severe drought drives novel community trajectories in desert stream pools. Freshwater Biology 56, 2070–2081. DOI:10.1111/j.1365-2427.2011.02638.x. Document a catastrophic regime shift in the community of arid-land stream pools corresponding to a shift from perennial to intermittent. Communities did not show any sign of recovery in the four years post-drought. Pre-drying, richness and composition oscillated seasonally between low- and high-flow seasons. Post-drying, abundances were much higher, which may somewhat reflect extirpation of large-bodied predators.

  5. Bogan, M.T., Boersma, K.S., Lytle, D.A., 2013. Flow intermittency alters longitudinal patterns of invertebrate diversity and assemblage composition in an arid-land stream network. Freshwater Biology 58, 1016–1028. DOI:10.1111/fwb.12105. Invertebrate richness was lowest in intermittent reaches, but intermittent reaches harbored distinct taxa with adaptations to intermittency (e.g. egg and⁄or larval diapause). Thus, intermittent reaches contributed clearly to regional diversity. Predators were much more abundant in perennial than in intermittent reaches.

  6. Shimadzu, H., Dornelas, M., Henderson, P. a, Magurran, A.E., 2013. Diversity is maintained by seasonal variation in species abundance. BMC biology 11, 98. DOI:10.1186/1741-7007-11-98. Use 30-y data of monthly sampled estuarine fish assemblage. Seasonal fluctuations in species abundance allow coexistence. Species fall into distinct seasonal groups. Interestingly, this reflects the four seasons, not just a wet-dry or summer-winter pattern. Seasonal variation in richness and evenness linked to shifts in resource availability. Essentially, spatiotemporal shifts in community composition minimize competitive interactions and help stabilize total abundance.

  7. Review for journal. Re-review.

  8. Corliss, B.H., Brown, C.W., Sun, X., Showers, W.J., 2009. Deep-sea benthic diversity linked to seasonality of pelagic productivity. Deep Sea Research Part I: Oceanographic Research Papers 56, 835–841. DOI:10.1016/j.dsr.2008.12.009. Documented latitudinal patterns of North Atlantic deep-sea benthic foraminifera. Fits the typical latitudinal diversity gradient. Regions with low seasonality and more stable food input over an annual cycle have higher diversity, a more even distribution of species and higher richness.

  9. Johnson, R.C., Carreiro, M.M., Jin, H.S., Jack, J.D., 2012. Within-year temporal variation and life-cycle seasonality affect stream macroinvertebrate community structure and biotic metrics. Ecological Indicators 13, 206–214. DOI:10.1016/j.ecolind.2011.06.004. Macroinvertebrates from three rural and three urban streams were sampled monthly in Kentucky to examine seasonal patterns.

  10. Chesson, P., Gebauer, R.L.E., Schwinning, S., Huntly, N., Wiegand, K., Ernest, M.S.K., Sher, A., Novoplansky, A., Weltzin, J.F., 2004. Resource pulses, species interactions, and diversity maintenance in arid and semi-arid environments. Oecologia 141, 236–253. DOI:10.1007/s00442-004-1551-1. Maintenance of diversity in arid and semi-arid environments. Focuses on resource pulses (rainfall) as a temporal coexistence mechanism. Emphasise that variability from pulsed rainfall does not reduce the importance of competition but allows differentiation for species to coexist. Essentially, two coexistence mechanisms at play: the storage effect and relative nonlinearity of competition. In these systems, life histories allowing persistence through bad times are fundamental to coexistence through the storage effect. They also identify other mechanisms of coexistence of these desert plant communities beyond the previous two. They briefly discuss how coexistence might differ when generalists are involved. Key to understand these dynamics to understand effects of global change.

  11. Mathias, A., Chesson, P., 2013. Coexistence and evolutionary dynamics mediated by seasonal environmental variation in annual plant communities. Theoretical Population Biology 84, 56–71. DOI:10.1016/j.tpb.2012.11.009. Really interesting paper, but lost me in the maths at times. Focuses on coexistence of annual plants through seasonal fluctuations of environmental conditions. Compare within-year single and double pulses of rainfall on two-species coexistence. Coexistence is possible on single pulse via the storage effect, but not evolutionarily stable. Double pulse, on the other hand, is stable. Essentially emphasises that seasonal pulses of resources can maintain or promote diversity through the storage effect.

  12. Linke, S., Bailey, R.C., Schwindt, J., 1999. Temporal variability of stream bioassessments using benthic macroinvertebrates. Freshwater Biology 42, 575–584. DOI:10.1046/j.1365-2427.1999.00492.x. Essentially demonstrated the importance of considering season in stream biomonitoring. Consistent differences in stream invertebrate biomonitoring metrics between summer and winter samples. For instance, bioassessment in winter indicates better value than summer. Note that many spp that indicate high water quality are those that favour cold water. They found the best predictive models were those that were built for each season.

  13. Kendall, B.E., 2015. Some directions in ecological theory. Ecology 96, 3117–3125. DOI:10.1890/14-2080.1. A personal account on some fruitful directions in ecological theory and past changes from theory being a source of conceptual ideas to now being used to quantitatively descirbe empirical observations.

  14. McMeans, B.C., McCann, K.S., Humphries, M., Rooney, N., Fisk, A.T., 2015. Food web structure in temporally-forced ecosystems. Trends in Ecology & Evolution 30, 662–672. DOI:10.1016/j.tree.2015.09.001. A look at the role of seasonality on food-webs. They use a case study from the Arctic to demonstrate their point that food webs shift with season. Emphasise this framework can help to understand the consequences of global change.

  15. Merritt, D.M., Scott, M.L., Poff, N.L., Auble, G.T., Lytle, D.A., 2010. Theory, methods and tools for determining environmental flows for riparian vegetation: riparian vegetation-flow response guilds. Freshwater Biology 55, 206–225. DOI:10.1111/j.1365-2427.2009.02206.x. Review of tools for determining environmental flows for riparian vegetation. First outline of the use of riparian vegetation-flow response guilds. Doesn’t go into detail of methods for flow response guilds but outlines five categories of guilds: life history, reproductive strategy, morphology, fluvial disturbance and water balance.

  16. Stromberg, J.C., Merritt, D.M., 2015. Riparian plant guilds of ephemeral, intermittent and perennial rivers. Freshwater Biology. Early view. DOI:10.1111/fwb.12686. Used clustering to identify different plant guilds from floodplains, terraces and uplands in rivers with varying flow: surface flow permanence, depth to ground water and intensity of fluvial disturbance.

  17. RE-READ: Colwell, R.K., 1974. Predictability, constancy, and contingency of periodic phenomena. Ecology 55, 1148–1153. Colwell’s classic paper on measuring the general characteristics of periodic phenomena: predictability, constancy and contingency. As predictability is the converse of uncertainty, it stands to reason that its calculation is based on the mathematics of information theory. Can be calculated very easily using Nick Bond’s R package ‘hydrostats’.

  18. Cauvy-Fraunié, S., Condom, T., Rabatel, A., Villacis, M., Jacobsen, D., Dangles, O., 2013. Technical Note: Glacial influence in tropical mountain hydrosystems evidenced by the diurnal cycle in water levels. Hydrology and Earth System Sciences 17, 4803–4816. DOI:10.5194/hess-17-4803-2013. Outlines the use of wavelets to track glacial influence by looking at power, frequency and temporal clustering of diurnal flow variation.

  19. Smith, L., Turcotte, D., Isacks, B., 1998. Stream flow characterization and feature detection using a discrete wavelet transform. Hydrological Processes 12, 233–249. Demonstrates wavelets as a tool for characterising streamflows. Uses five different hydroclimatic regions to do so.

  20. Keitt, T.H., 2008. Coherent ecological dynamics induced by large-scale disturbance. Nature 454, 331–334. DOI:10.1038/nature06935. Looks at the effects of a press disturbance (pH lowering) on zooplankton in a LTER site in Wisconson. Showed through wavelet analysis that communities were synchronous after the disturbance. This goes agains theory in that compensatory effects should have stabilised communities (they comprised both disturbance-sensitve and -tolerant species). Interesting application of wavelets.

  21. Cazelles, B., Chavez, M., Berteaux, D., Ménard, F., Vik, J.O., Jenouvrier, S., Stenseth, N.C., 2008. Wavelet analysis of ecological time series. Oecologia 156, 287–304. DOI:10.1007/s00442-008-0993-2. Example ways that wavelets can be applied to ecological data. Compares discrete and continuous wavelets. Outlines most of the aspects of wavelets, including the choice of mother wavelet, cone of influence etc. Also looks at the use of wavelets for comparing two time series through coherency and phase difference.

  22. Downing, A.L., Brown, B.L., Perrin, E.M., Keitt, T.H., Leibold, M.A., 2008. Environmental Fluctuations Induce Scale-Dependent Compensation and Increase Stability in Plankton Ecosystems. Ecology 89, 3204–3214. Support for the ability of compensatory dynamics to stabilise communities. This is demonstrated in semi-natural experimental ponds.

  23. Micheli, F., Cottingham, K.L., Bascompte, J., Bjørnstad, O.N., Eckert, G.L., Fischer, J.M., Keitt, T.H., Kendall, B.E., Klug, J.L., Rusak, J.A., 1999. The dual nature of community variability. Oikos 85, 161–169. DOI:10.2307/3546802. A nice review paper on different types of community variability. Breaks variability into compositional (changes in relative abundance of species) and aggregate (changes in summary properties, such as overall abundance, biomass etc.). Compositional and aggregate variability can lead to the following four types: stasis - low compositional, low aggregate variability; synchrony - low compositional, high aggregate variability; asynchrony - high compositional, high aggregate variability; compensation - high compositional, low aggregate variability.

  24. Keitt, T.H., Fischer, J., 2006. Detection of scale-specific community dynamics using wavelets. Ecology 87, 2895–904. Quite similar to the previous nature paper. Looks at synchrony vs. compensation in response to long-term disturbance at an LTER site using wavelets.

  25. Steel, E.A., Lange, I.A., 2007. Using wavelet analysis to detect changes in water temperature regimes at multiple scales: effects of multi-purpose dams in the Willamette River Basin. River Research and Applications 23, 351–359. DOI:10.1002/rra.985. Identifies the temporal scales of variability in temperature that dams disrupt.

  26. Jardine, T.D., Bond, N.R., Burford, M.A., Kennard, M.J., Ward, D.P., Bayliss, P., Davies, P.M., Dougals, M.M., Hamilton, S.K., Melack, J.M., Naiman, R.J., Pettit, N.E., Pusey, B.J., Warfe, D., Bunn, S.E., 2015. Does flood rhythm drive ecosystem responses in tropical riverscapes? Ecology 96, 684–692. DOI:10.1890/14-0991.1. Really nice paper looking at flood rhythm in large tropical rivers. They demonstrated the role of rhythmicity, or predictability of the timing and magnitude, of flood events on biota and other processes. Essentially more rythmic rivers support more diverse fish assemblages, more stable bird populations and greater riparian forest production.

  27. Fahimipour, A.K., Hein, A.M., 2014. The dynamics of assembling food webs. Ecology Letters 17, 606-613. DOI:10.1111/ele.12264. Food web structure develops according to repeatable trajectories that are strongly influenced by colonisation rate. They found webs with different colonisation rate had stable web topologies, despite strong assemblage turnover. This indicates network architecture begins early and remains similar through the assembly process.

  28. Adler, P.B., HilleRisLambers, J., Kyriakidis, P.C., Guan, Q., Levine, J.M., 2006. Climate variability has a stabilizing effect on the coexistence of prairie grasses. Proceedings of the National Academy of Sciences of the United States of America 103, 12793–12798. DOI:10.1073/pnas.0600599103. Evidence of the storage effect coexistence mechanism at work in relation to climatic variability.

  29. Gravel, D., Poisot, T., Desjardins-Proulx, P., 2014. Using neutral theory to reveal the contribution of meta-community processes to assembly in complex landscapes. Journal of Limnology 73, 61–73. DOI:10.4081/jlimnol.2014.807. Uses a combination of graph/network theory and neutral theory. Develop three models to differentiate between neutral, patch dynamics and species sorting using simulated data in four landscape types. Demonstrates the importance of landscape structure and network position.

  30. Economo, E.P., Keitt, T.H., 2008. Species diversity in neutral metacommunities: A network approach. Ecology Letters 11, 52–62. DOI:10.1111/j.1461-0248.2007.01126.x. A network-focused look at metacommunities from a neutral perspective. Demonstrates that spatial structure within a metacommunity can promote gamma diversity.

  31. Economo, E.P., Keitt, T.H., 2010. Network isolation and local diversity in neutral metacommunities. Oikos 001–009. DOI:10.1111/j.1600-0707.2010.18272.x. Another look at neutral metacommunities. Shows diversity increases with node centrality withing a network (graph theory approach). Defines different aspects of network centrality. Highlights the interaction between spatial extrnt and dispersal-evolution tradeoff. i.e. isolation only predicts diversity at a critical scale.

  32. Barson, N.J., Aykanat, T., Hindar, K., Baranski, M., Bolstad, G.H., Fiske, P., Jacq, C., Jensen, A.J., Johnston, S.E., Karlsson, S., Kent, M., Moen, T., Niemelä, E., Nome, T., Næsje, T.F., Orell, P., Romakkaniemi, A., Sægrov, H., Urdal, K., Erkinaro, J., Lien, S., Primmer, C.R., 2015. Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 000, 1–4. DOI:10.1038/nature16062

  33. Lytle, D.A., Merritt, D.M., 2004. Hydrologic regimes and riparion forests: a structured population model for cottonwood. Ecology 85, 2493–2503. DOI:10.1890/04-0282. A fundamental part of our research here. A structured matrix population model for cottonwood.

  34. Review for journal.

  35. Cureton, J.C., Broughton, R.E., 2014. Rapid morphological divergence of a stream fish in response to changes in water flow. Biology letters 10, 20140352. DOI:10.1098/rsbl.2014.0352

  36. Review for journal.

  37. Re-review for journal.

  38. Harper, M.P., Peckarsky, B.L., 2006. Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change. Ecological Applications 16, 612–621. Baetis bicaudatus emerges early in dry years by using water temperature as the proximate cue for metamorphosis. Water temp and discharge are strongly tied (water temp increases with decreasing flow), so they used an additional experiment to determine whether flow or temp was key driver.

  39. Review for journal.

  40. Humphries, P., Baldwin, D.S., 2003. Drought and aquatic ecosystems. Freshwater Biology 48, 1141–1146. DOI:10.1002/9781444341812. Intro to special issue on droughts overlaying some of the key findings and definitions of droughts.

  41. Friendly review for colleagues.

  42. Jocque, M., Field, R., Brendonck, L. & De Meester, L. (2010). Climatic control of dispersal-ecological specialization trade-offs: a metacommunity process at the heart of the latitudinal diversity gradient? Glob. Ecol. Biogeogr., 19, 244–252. DOI:10.1111/j.1466-8238.2009.00510.x

  43. Re-read: Heino, J., Melo, A.S., Bini, L.M., Altermatt, F., Al-Shami, S.A., Angeler, D.G., et al. (2015). A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels. Ecology and Evolution, 5, 1235–1248. DOI:10.1002/ece3.1439

  44. Allstadt, A.J., Liebhold, A.M., Johnson, D.M., Davis, R.E. & Haynes, K.J. (2015). Temporal variation in the synchrony of weather and its consequences for spatiotemporal population dynamics. Ecology, 96, 2935–2946. DOI:10.1890/

  45. Humphries, P., Keckeis, H. & Finlayson, B. (2014). The River Wave Concept: Integrating River Ecosystem Models. Bioscience, 64, 870–882. DOI:10.1093/biosci/biu130

  46. Merritt, D.M. & Poff, N.L. (2010). Shifting dominance of riparian Populus and Tamarix along gradients of flow alteration in western North American rivers. Ecol. Appl., 20, 135–152.

  47. Belmaker, J., Sekercioglu, C.H. & Jetz, W. (2012). Global patterns of specialization and coexistence in bird assemblages. J. Biogeogr., 39, 193–203. DOI:10.1111/j.1365-2699.2011.02591.x

  48. Review for journal.