Tag Archives: grassland

Seasonal not annual rainfall determines grassland biomass response to carbon dioxide

After a brief hiatus, journal club is back and this time we’re discussing a paper by Hovenden et al from Nature in May exploring the interaction between carbon dioxide and rainfall on plant biomass.

At this point it seems that we ecologists have a reasonably good idea of what effect many environmental variables – like water, temperature, and carbon dioxide – have on certain ecosystem parameters, though always with a few caveats and exceptions thrown in to keep it interesting.  However, our understanding of how these variables interact and the effects of these interactions, especially over various temporal and spatial scales, is still pretty woeful.

For example, we know that plants need water to grow, and when there isn’t enough water they stop growing – very straightforward. Plants also need CO2 to grow, and in general higher CO2 levels lead to higher plant biomass.  This is because increased CO2 allows for higher rates of photosynthesis and greater water use efficiency.  Due to the greater water use efficiency, we also expect that the effect of elevated CO2 (eCO2) on plant growth will be greater when water scarce.  Basically, with higher CO2­, plants can photosynthesize more per unit available water, so will be able to grow more before the water runs out compared to plants grown at lower CO2 levels.

As with so many things in ecology, what we predict is exactly what we see … except when we don’t.  If the relationship between water availability, eCO2 and plant biomass is so straightforward, biomass responses to eCO2 would always be positive and we would see the strongest responses in the driest years.  I bet you can see where this is going…

TasFACE ring

Photo credit: TasFACE website

Hovenden et al looked at data from a nine year FACE experiment in Tasmania (TasFACE) and found that the eCO2 effect was far from consistent across years.  Some years there was no discernable eCO2 effect on biomass, some years it was positive (like we’d expect) and one year it was actually strongly negative; and these responses were not correlated with annual rainfall or soil water availability.

Instead, Hovenden et al found that the biomass responses to eCO2 were strongly correlated with seasonal rainfall variability.  Higher rainfall in the summer resulted in a positive effect of eCO­2 on biomass, as we would expect.  Summer rain at the site tends to come in short, sharp bursts, so the increased water use efficiency would allow the plants to maintain growth for longer between rain events.  However, increased rain during the spring and autumn were correlated with a negative effect of eCO2 on biomass.  During these cooler, wetter periods plants don’t grow as much and it is likely that increased rain would leach nutrients from the soil.  This was supported by a strong negative relationship between spring rain and soil nitrogen availability.

It seems probable that such a relationship between seasonal rainfall and eCO2 effects on biomass could be seen throughout temperate and seasonally wet systems, and that this could have big implications for global carbon models.  It also highlights the importance of looking beyond plants to fully understand the mechanisms that drive responses to climate change.

I would love to see similar analyses of other FACE datasets to see if these trends are replicated in other systems.  It’s an important finding, but opens up lots of other interesting questions: How does vegetation type or soil type effect the relationship between seasonal rainfall and eCO2 effects on biomass?  Does seasonal temperature variability affect the relationship significantly?  What about increased nitrogen pollution or fertilisation – would increased nitrogen deposition overturn the negative relationship between high spring/autumn rain and the eCO2 effect on biomass?

As always, we’d love to hear what you think about the paper.  Is it the best paper you’ve ever read or do you think it contains some fundamental flaw? Does it raise interesting questions or link well with something else you’ve read recently?  Would you use similar methods or could you propose a better protocol?  Let us know in the comments or on twitter with hashtag #psejclub!

Finally, don’t forget about our joint meeting with the Plant Environmental Physiology group coming up in October.  All the details, including links for registration and abstract submission, are available here.  It’s going to great!

Advertisements

Soil biodiversity and soil community composition determine ecosystem multifunctionality

This paper, by Cameron Wagg et al., which was published online early in PNAS last month, describes the results of a very interesting experiment in which the authors manipulated soil biodiversity and measured the effect of these manipulations on a range of ecosystem functions.

More specifically, they created a gradient of reduced soil biodiversity (including a range of faunal and microbial groups) by sieving the soil through a number of decreasing mesh sizes, adding the fraction that passed through the sieve to sterilized soil, while also adding the sterilized fraction that remained on top of the sieve. They then grew plant communities consisting of common grasslands species in the soil for 14 and for 24 weeks, in two separate experiments. At the end of the first experiment, and after 12 and 24 weeks of the second experiment, they measured plant diversity and productivity, carbon sequestration, litter decomposition, nitrogen turnover, N2O emission, phosphorus and nitrogen leaching as ecosystem functions, and fungal and bacterial diversity (by TRFLP), mycorrhizal root colonization (microscopically), and nematode abundance (microscopically).

They then used these data to relate the ecosystem functions measured to the soil biodiversity treatments. In addition, they calculated z-scores for the range of ecosystem functions measured as well as for all groups of organisms quantified, and regressed these against each other to answer the question whether ecosystem multifunctionality is related to soil biodiversity. This approach, of summarising a number of ecosystem processes into one ecosystem multifunctionality index, has been used previously by Maestre et al. (2012).

Their findings are very interesting and will make a lot of soil ecologists very happy: they find that a number of the individual ecosystem functions are reduced with declining biodiversity, but also that ecosystem multifunctionality is positively correlated with overall soil biodiversity.

When taking a closer look at the data, it becomes clear that the reduction in soil biodiversity varies between groups and isn’t linear with the decreasing mesh sizes – mycorrhiza and nematodes drop down sharply after the third ‘dilution’, whereas the other parameters show a more gradual decline. The authors have taken this into account by not only relating ecosystem functioning to the diversity treatments, but also to the abundance and diversity of individual groups. When taking a closer look at this, it becomes clear that the microbial properties measured have a far stronger effect than nematode abundance. In addition, the effect of reduced soil biodiversity on a range of functions is indirect, through effects of plant productivity and diversity.

Of course, it is very easy to criticise aspects of this study. You can question whether bacterial and fungal diversity, microbial biomass, mycorrhizal colonization, and nematode abundance together are a realistic representation of soil biodiversity. For example, why was nematode diversity not assessed? And why not higher trophic levels, such as Collembola and mites? Microbes and nematodes are only a fraction of the soil food web (Fig. 1). With the current analyses, the title ‘Soil microbial diversity and community composition determine ecosystem multifunctionality’ might have been more appropriate.

A (simplified) example of a soil food web, with the groups measured by Wagg et al. (2014) indicated by the dashed line.

A (simplified) example of a soil food web, with the groups measured by Wagg et al. (2014) indicated by the dashed line.

Also, it would have been interesting to see root biomass in addition to mycorrhizal colonisation – a number of recent papers point to the importance of roots for ecosystem functioning (e.g. Orwin et al. 2010, Grigulis et al. 2013)

A more technical comment relates to the measurement of nitrogen turnover – this was assessed by measuring the uptake of 15N from Lolium multiflorum litter into aboveground L. multiflorum biomass. So, this measurement might be a proxy for L. multiflorum biomass, which decreases with decreasing soil biodiversity, rather than for nitrogen turnover.

On another note, and I would be very interested in other people’s opinion, I am wondering about the value of using an index for ecosystem multifunctionality. True, this averages across ecosystem functions and can therefore inform management to optimize overall ecosystem functioning. However, are the ecosystems that have the greatest average functioning really the most sustainable, and thus, desirable ecosystems? Are all ecosystem functions equally important? There might be trade-offs between different ecosystem functions – for example between crop yield and nitrogen retention, or between decomposition and carbon sequestration. We might want to optimize a certain function in a certain area, of which we already know that it has potential in delivering a certain function, rather than promoting multifunctionality across the board. For example, peatlands store large amounts of carbon because of their low decomposition rates, and agricultural production systems have high yields but low carbon sequestration.

However, in this paper, the multifunctionality index serves the purpose of summarizing overall ecosystem functioning, which shows a strong and positive relationship with soil biodiversity. Done like this, it summarizes a range of measurements that non-specialists might struggle to interpret – thus, it simplifies and reinforces the message of the paper that soil biodiversity determines ecosystem functioning.

Experiments like this require an enormous amount of work, and you simply can’t include everything. It is incredibly difficult to modify soil biodiversity without simultaneously changing soil properties, and the authors of this paper have achieved this by used an elegant method of reducing soil biodiversity. Thus, in contrast to many earlier studies, they were truly able to mechanistically elucidate the role of groups of soil organisms in ecosystem functioning.

This paper adds to the growing body of literature that soil biodiversity plays a crucial role in ecosystem functioning, and highlights the importance of conserving, and promoting, soil biodiversity. That’s what I like to hear!

Eutrophication weakens stabilizing effects of diversity in natural grasslands

This letter, by Yann Hautier and many others, appeared in Nature ten days ago. Its focus is grasslands, and what happens to their [above-ground] diversity when you add fertiliser. I was drawn to this paper by the simple message communicated in the title, and the universality implicit in ‘natural grasslands’. Excellent; a succinct study of the effects of excessive nutrients on the modulation ecosystem functioning by diversity – read on!

It’s immediately apparent that the strength of this work lies in the size and global reach of its dataset. The authors utilised an established network of experiments looking at the relationships between fertilization, diversity and production in grasslands: the Nutrient Network (NutNet). This allowed the authors to address their hypotheses using data collected from 41 different grasslands, spanning five continents. One of the major advantages of using sites in an established network is that methods are broadly standardised; this goes some way towards ensuring that, while the sites encompass a wide range of variation in grassland types, the data are comparable between sites. In the extended methods section, the authors describe the sensitivity analyses they performed to check that distinctive sites (subject to strong seasonality, or anthropogenic influence, for example) did not unduly influence their results.

So what did the authors measure? They chose above-ground net primary productivity (ANPP) as their response variable, which they estimated by measuring above-ground live biomass at each site. The authors also introduced two related concepts: the stability of ANPP and species asynchrony; stability of ANPP increases as species asynchrony increases and the productivity of individual species fluctuates in response to the environment at different rates. This is a neat idea: in an asynchronous community, a decline in the productivity of one species is more liekly to be compensated for by another, and so the productivity of the community as a whole is more likely to remain stable.

To arrive at their finding that the application of fertiliser weakens the stabilising effect of diversity, the authors observed that, while the temporal variation of ANPP decreased at higher diversities in the unfertilised communities, it increased at higher diversities in the fertilised communities. The increased variation in ANPP, combined with lower species asynchrony in fertilised communities, led the authors to conclude that [over]-fertilisation of grasslands can reduce the stability of their productivity. Importantly, the authors showed that the loss of diversity caused by fertilisation didn’t affect species asynchrony.

While I initially found this article difficult to get to grips with, due to the introduced concepts and number of scatterplots and lines to compare, but now that I get it, I agree with the results. One of the best aspects of this study is that it draws its conclusions from a controlled experiment, rather than observational correlations. I think the work also raises a number of further questions, which would be interesting to address using NutNet or a similar project.

  • The authors used species richness as their measure of diversity. What about functional diversity? Perhaps some groups (grasses, forbs, legumes) respond to fertilisation more than others?
  • While ANPP is certainly likely to be related to below-ground productivity, it would be interesting to see whether stability of below-ground productivity showed the same patterns in response to fertilisation. Are there other ecosystem functions that are worth measuring? What about carbon and nitrogen cycling? These functions obviously come with the caveat that they are much more difficult to measure (you can’t just see them, unlike plants), but if it was feasible, what patterns might we expect to see?
  • The amount of fertiliser applied in the study was quite high. Do we see the same results at lower concentrations?
  • There were no sites in South America – do we think this is likely to have biased the result significantly?

Now that I’ve had my say, it would be great to hear yours; did you find this paper interesting, do you think its conclusions are valid? How might you have done things differently? Do you think there are specific lessons to be learnt? Please get in touch by commenting on this post, or on Twitter or Facebook using the hashtag #psejclub. I’m looking forward to hearing from you!