Local species richness may be declining after all

Recently two papers seemed to turn what we thought we knew about changes in biodiversity on their head. These papers by Vellend et al. and Dornelas et al. collated data from multiple sources and suggested that species richness at local scales is not currently declining. This was counter-intuitive because we all know that species are going extinct at unprecedented rates. However, it is possible that the introduction of non-native species and recovery of previously cultivated areas may offset extinctions leading to relatively little net change in local species richness.

This week a paper has been published that calls these findings into question. The paper by Andy Gonzalez and colleagues published in the journal Ecology, suggests that there are three major flaws with the analyses. These flaws mean that the answer to the question ‘Is local-scale species richness declining?’ currently remains unanswered and is unanswerable.

The papers of Vellend et al. and Dornelas et al. were meta-analyses of previously published papers. One issue with meta-analysis is that it is very prone to bias. Like any study if the samples (in this case ecological studies) are not representative of the population (in this case locations around the globe) then any results will be flawed. To test the representativeness of the datasets used by Vellend and Dornelas Gonzalez et al. examined how well they represented biodiversity and threats to biodiversity. This analysis (see below) showed that the papers were not representative of biodiversity or the threats faced by biodiversity (though curiously, the analysis of Dornelas et al. showed an overrepresentation of areas highly impacted by human impacts).

Gonzalez_1.png
Figure 1 – Spatial bias of the Vellend et al. (2013) and Dornelas et al. (2014) data syntheses. For more information see the paper by Gonzalez et al. (2016).

The paper also suggests that using short time series can underestimate losses. By analysing the effect of study duration and changes in species richness (see below) Gonzalez et al. claim that increases in study duration were correlated with a decline in species richness. This supports previous theory which suggests that there is often a time lag between disturbance events and species extinctions – termed ‘extinction debt.’ However, I’d be intrigued to see the results of removing the studies with the longest duration from this analysis since the authors admit that the analysis is sensitive to their inclusion. I’ve seen recent similar work that suggests the same kind of relationship might be seen for studies monitoring individual animal populations.

Gonzalez_2
Figure 2 – The effect of study duration on apparent changes in species richness.

Thirdly, Gonzalez et al. assert that including studies in which ecosystems were recovering from disturbance (e.g. regrowth on former agricultural fields) without taking into account historical losses that occurred during or after the disturbance biases estimates of change. The paper by Vellend et al. in particular combined studies of the immediate response of biodiversity to disturbances such as fire and grazing along with studies of recovery from the very same disturbances. Gonzalez et al. show that once studies of systems that were recovering are removed from Vellend et al’s analysis there is a negative trend in species richness changes.

The biases prevalent in the Vellend and Dornelas papers lead to Gonzalez et al. to suggest that the papers cannot conclude what the net changes in local species richness are at a global scale. However, they note that the results of Dornelas and Vellend are in sharp contrast to other syntheses of biodiversity changes which used reference undisturbed such as those by Newbold et al. and Murphy and Romanuk which reported average losses of species richness of 14 and 18% respectively.

In their conclusion Gonzalez et al. suggest that though meta-analysis is a powerful tool, it needs to be used with great care. Or to put it another way, with great power comes great responsibility. As someone who regularly uses meta-analysis to form generalisations about how nature works I completely agree with this statement. Traditionally scientists have used funnel plots (graphs with study sample size on the y-axis and effect size on the x-axis) to identify biases in their analyses. I’ve always been skeptical of this approach, especially in ecology where there is always a large amount of variation between sites. In the future syntheses would do well to follow the advice of Gonzalez et al. and really interrogate the data they are using to find any taxonomic, geographic, climatic or any other biases that might limit their ability to generalise. I know it’s something I’ll be taking more seriously in the future.

Gonzalez et al. also point out that most ecological research is carried out in Europe and North America. If we want to monitor biodivesity we need to increase efforts in biodiverse tropical regions, as well as boreal forests, tundra and deserts. We need to identify where these gaps need filling most and then relevant organisations need to prioritise efforts to carry out monitoring. I am positive that this can be achieved, but it will cost a lot money, needs to be highlighted as a priority and will ned a lot of political good will. Even with this effort some of the gaps in biodiverse regions, such as the Democratic Republic of Congo, will be extremely difficult to fill due to ongoing armed conflict

My take-home message from this paper is that we need to be more careful about how we do synthesis. However, I also think that species richness isn’t the only metric that we should focus on when talking about biodiversity change. Studies have shown that measures of the traits of species present in a community are generally more useful for predicting changes in ecosystem function than just using species richness. Species richness is the iconic measure of biodiversity, but it probably isn’t the best. Ecologists should view species richness in the same way as doctors view a thermometer – it’s a useful tool but you still need to be able to monitor blood pressure, take biopsies and listen to a patient’s lungs before you diagnose them*.

 


 

*Thanks to Falko Bushke whose analogy I stole from a comment he made on my blog post here.

 

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Is ecological succession predictable?

Over the last few years I have written quite a lot about forest succession. I have published a paper on the topic, have a paper in review about recovery of a forest under multiple stressors and will be starting more work on the it over the next few weeks. All in all, I think I have a reasonable idea what I’m talking about when it comes to succession, at least in forests. However, I’ve just read a paper on tropical forest succession that caught me a bit unawares*.

The paper in question is Natalia Norden and colleagues’ work that was recently published in PNAS. The authors collected data from 72 secondary forest plots monitored for 7-24 years at 7 different sites across tropical South and Central America. They then used this data to look whether we can predict trajectories plot stem density, basal area and species density during forest succession after total clearance. On the whole the paper found that trajectories were poorly predicted by models that looked at change as a function of forest age. From the figure below, you can pick some general trends in the direction of change with age – stem density might have a humped relationship with age for example. However, it is also clear that there is a huge amount of variation and some trajectories bounce around all over the place.

Observed successional trajectories of stem density, basal area and species density for the sites used by Norden et al.
Observed successional trajectories of stem density, basal area and species density for the sites used by Norden et al.

It’s obvious from looking at the figure above that the age of a secondary forest doesn’t really act as a proxy for its successional stage. In fact Norden and colleagues found that on average age only explains 20% of within site variation. Even if that is better than the average ecology paper, it’s still not very good. To explain the rates of change of different variables, Norden et al. fitted a set of different non-linear models for each site. Again, their findings emphasised the large amount of variation between different sites. Due to these idiosyncrasies, the authors of the paper see space-for-time substitution as a flawed method for predicting the dynamics of forests. They also suggest that such approaches should not be used for studies of succession of any sort of vegetation, arguing that previous work these methods has made succession appear as if it is deterministic, and it is not.

Now I’m not sure how the numbers of studies that use chronosequences vs monitoring over time to study succession stack up, but I’d be willing to be bet >80% of these papers use chronosequences, at least in forests. There are good reasons for using them: they take much less time than monitoring (especially in systems containing long-lived organisms), they are much less expensive, the logistics are less complex and as a result of all of these things, they are easier to get funded than a 10-20 year research programme. Norden et al.’s warning against using chronosequences based on their results, begs the question “Do we have other evidence of how well chronosequences perform?” The answer is that we do, and it doesn’t look too good for chronosequences. For example, Ted Feldpausch and colleagues found that space-for-time substitution resulted in overestimates of biomass accumulation for young secondary forests in the Amazon. Recently Mora and colleagues similarly suggested that chronosequences were poor predictors of forest characteristics.

So, is the chronosequence dead? Well, maybe not just yet. However, I think as researchers we need to be more circumspect about their use. In particular I think there are 4 questions that we need to answer to get a more well rounded view of the usefulness of chronosequences:

  1. How much variation in future dynamics do they actually predict? – Chronosequences are far from perfect, but it still offers us some insight into future dynamics. Mora et al. showed that chronosequences can still account for 32-57% of variance in future forest characteristics. There must be a reasonably large number of chronosequences that have been sampled more than once that could be used to test their predictive ability. We need more studies that address this head on. If it turns out that they are very poor at explaining future dynamics, then maybe it is time to switch to better methods.
  2. What variables do they predict most effectively? – Structural components of a system (biomass, stem density etc) should be easier to predict than community composition, since changes in structure are less likely to depend on idiosyncrasies such as the identity of initial colonising species. However, again, this has been tested relatively rarely.
  3. Do chronosequences have more predictive power in some systems than others? – Predictive power should be greatest when abiotic conditions are relatively constant across a landscape, disturbance history at all sites is relatively similar and in regions with relatively small species pools. Under all of these conditions there should be less chance of wildly different successional trajectories occurring.
  4. Where do animals fit into all this? – Predicting animal abundance and community composition is rarely studied in chronosequences, probably because their response to succession is that much less predictable than plant communities. Even though they are likely to perform relatively poorly, a comparison of the predictive ability of chronosequences for animal compared to plant communities would be interesting.

What do you think? Are there any other questions we need to answer to determine the value of chronosequences? Or do you have any views on the use of chronosequences in non-forest systems?

*To be fair, this probably shouldn’t have been that much of a surprise, review papers have been suggesting that chronosequences are far from the best way to do things for a while. Although, there are also papers that suggest that careful use of chronosequences is perfectly ok.

Species richness – what is it good for?

Species richness is the iconic measure of biodiversity. It is simple to interpret* and it is one of the most commonly measured metrics in ecology. From the early beginnings of ecology Darwin, Wallace and von Humbolt noted the striking differences in the number of species found in different places and ecologists are still fascinated by it . However, over the last few months I have begun to question how useful it is for applied research.
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Looking to the past for insights into tropical forest resilience

A few weeks back Lydia Cole and colleagues published a really cool paper exploring recovery rates of tropical forests. Seeing as it’s something I’ve covered a here before in relation to my work on secondary forests recovering after agricultural clearance and recovery from selective logging, I invited Lydia to write a guest post giving a different perspective to a topic I have discussed here before. Thanks to Lydia for stepping up to the plate and I hope you find her post as interesting as I did.


Anyone reading this blog probably doesn’t need reminding of how important tropical forests are!  Birds, bees, berries and a whole load of other plants, animals and services that we probably underestimate our reliance on.  Despite the many arguments in favour of keeping tropical forests standing, vast areas continue to be deforested at rapid rates resulting in changes like that shown below (Fig 1), under pressures of expanding human population, rising consumption and the agricultural footprint to match (Geist & Lambin, 2002).

Borneo-forest
Fig 1 – Forest disturbance like logging can lead to forests such as this one in Borneo being converted from intact (left) to heavily degraded (right).

Disturbance and recovery in tropical forests Despite this widespread clearance as a result of  recent international forest conservation initiatives and rising rural-to-urban migration (Mather, 1992), some degraded tropical forests are being given a chance to recover.  But how long does it take them to recover?  Much recent research has attempted to answer this question (e.g. the great work of Chazdon et al., 2007) but little has monitored change over time scales of >50 years. Since many tropical trees have lifespans much longer than this previous studies have only captured a snap-shot of the ecological process of recovery.  In our study, we attempted to answer the question again; this time by looking into the past to gather data over longer time scales that could offer a more complete picture of forest recovery post disturbance.

The palaeoecological approach

Palaeoecology, otherwise known as long-term ecology, uses fossils to decipher how plants and animals interacted with their environment in the past.  Fossil pollen grains come in all shapes and sizes, and their morphological characteristics can be used to identify the plant family, genus or even the species to which they belong.  When a collection of these grains are identified and counted from a layer of sediment, we can reconstruct what the vegetation was like at that point in time when those grains were deposited. In our project, we were interested in studies that documented disturbance-induced changes in fossil pollen from forested communities across the Tropics, over the last 20,000 years.  Types of disturbances ranged from climatic drying events and landslides, to shifting cultivation and human-induced biomass burning.  We found 71 studies published on tropical forest palaeoecology that satisfied our selection criteria (e.g. within 23oN/S of the equator, possessing a sufficient chronology), documenting 283 disturbance and associated recovery events.  The rate at which recovery was occurring across the different forests and disturbance events was the key variable of interest and was calculated as the percentage increase in forest pollen abundance per year relative to the pre-disturbance level.

How far and how fast have tropical forests recovered in the past?

Our results demonstrate that in the past the majority of forests regrew to less than 100% of pre-disturbance levels, prior to declining again or reaching a new baseline; the median recovery was to 95.5%.  They also recovered at a variety of speeds, ranging from rates that would lead to 95.5% regrowth in less than 10 years to those taking nearly 7,000 years; the average was 503 years.  This is significantly longer than the periods adopted by logging companies between extraction cycles!

What affects the rate of recovery?

Three of the different factors we investigated for their potential effect on the forest recovery rate seemed to be of particular importance: geographical location, disturbance type and frequency of disturbance events. Of the four key tropical regions, Central American forests recovered the fastest and those in Asia the slowest (Figs. 2 & 3).  This is concerning, given that forests in Southeast Asia are currently experiencing some of the greatest rates of deforestation of all tropical regions, primarily due to the economic profitability of oil palm agriculture (check out mongabay for details).

Tropical forest recovery
Fig. 2  Map of tropical forest distribution, the location of studies and relative recovery rates across regions.

The most common form of disturbance, and one from which forest regrowth happened relatively slowly, was anthropogenic impact, i.e. via logging, burning and/or for agriculture (Fig. 3).  The slowest rates of recovery occurred after climatic disturbances and the fastest after large infrequent events, e.g. landslides, hurricanes and natural fire.  This latter result is somewhat intuitive given that these perturbations are a natural part of all ecosystems, leading to the evolution of a dynamic response in the native plant communities.  

Figure 3
Fig. 3  Composite figure showing how the recovery rate varies with different variables.

Insights into resilience

When we looked at the standardised rate of disturbance events (SRD), i.e. the number of disturbance events per 1,000 years, we found that the greater the frequency events occurred in the past, the more quickly the forest responded to each subsequent disturbance.  This runs counter to contemporary theories on resilience that describe slowing rates and diminishing ability to recover with each subsequent perturbation (e.g. Veraart et al., 2012).  Our results suggest that over ecologically meaningful timescales, i.e. over the life-span of entire forest communities rather than single trees, increased exposure results in adaptation to that disturbance over time, leading to a greater ability to recover quickly from the perturbation.

What does this all mean for tropical forests?

From looking back into the past, it seems that tropical forests can take a long time to recover from disturbances, and that different regions may require different management regimes to encourage more complete reforestation after natural or anthropogenic events, such as fire.  Central American and African forests may bounce back from impacts more quickly than the other regions, with disturbances such as tropical hurricanes and climatic fluctuations being a more common component of these ecosystems than in the other tropical regions.  However, all of the forests we looked at demonstrated a greater vulnerability to anthropogenic impacts and climatic changes than large infrequent disturbances: the two major forms of disturbance occurring today and at levels that far exceed those experienced over the past 20,000 years – reasons for caution.

Sustainable management

Identifying and understanding the different ecological requirements of forests across the different geographical regions, and of the forest-types within those regions, is vital for developing more sustainable landscape management plans.  With increasing international concern over deforestation rates, the associated loss of biodiversity and elevated carbon dioxide emissions, the conservation and restoration of tropical forests is becoming more politically and economically feasible.  Indonesia, for example, has introduced ‘ecosystem restoration concessions’ in the last decade, providing a legal means for forest protection from the further expansion of industrial agriculture.  And the potential of Reducing Emissions from Deforestation and Forest Degradation (now REDD+) to save the World’s forests continues to generate international debate. Of importance to all of these programmes and initiatives, is the suggestion from our study that forests take time to recover, and if we give them that time, they will persist, and continue to provide their faunal inhabitants, including us, the greatest collection of biological riches on Earth.

Tropical forest carbon storage is related to tree richness and traits. Or is it?

There’s been a lot said about relationships between species diversity and ecosystem function over the last two decades. The general view of these relationships is that diverse ecosystems are more productive, use resources more efficiently and are more stable.

But, and it’s a big but, almost none of this work has been done in forests and even less in mega-diverse tropical forests. Because of this diversity productivity relationships can’t really be described as general. How do we know what is general across the globe if we have only concentrated on temperate grasslands?

This is something a new paper in Global Ecology and Biogeography by Kyle Cavanaugh and colleagues hopes to set straight. Their study drew on a dataset of carbon storage and tree biodiversity from 59 plots across the tropics produced by members of the Terrestrial Ecosystem Assessment Monitoring  (TEAM) Network.

The great thing about this work is that all plots were surveyed using the same methods, meaning they should be reasonably comparable. All sites collected measures of aboveground carbon storage, genus diversity, functional diversity – by measuring wood density of trees and potential maximum diameter, and the mean value for wood density and maximum diameter for each plot. All of this was then analysed while trying to account for climatic differences between sites.

The general findings of the study were that both genus diversity and the mean potential maximum diversity of species appear to be  positively related to aboveground carbon storage.

Relationships between
Relationships between site (a) elevation and genus richness, (b) precipitation and functional diversity, (c) carbon storage and genus richness and (d) carbon richness and mean maximum diameter of trees. Stolen from the paper.

This enforces the view that diverse ecosystems are more productive and that large species may contribute a disproportionate amount of biomass – as I have written before. Very few studies have shown a relationship between diversity and biomass in tropical systems before, so this is exciting stuff.

And yet, I still have a few queries about some findings. The study failed to find any relationship between climate and carbon storage – a connection that is fairly well established. Also it uses stepwise model selection, which is beginning to become one of my (and others’) pet peeves . I am of the feeling that testing all possible models and then averaging amongst them based on the ones that have greatest support is the best way to do things, and this often comes up with very different findings to stepwise selection.

Previous similar work has suggested that carbon – biodiversity relationships are scale-dependant, with positive relationships in small plots and mixed results at larger plot sizes. Given the increasing number of tropical forest research networks I am sure this study will not be the last of its type. Once these get published we will have a better idea of how general these findings are.  At the moment I am not completely convinced.

Are large, old trees in decline?

I’ve banged on enough about the crisis in forests for people here to know what the deal is.

Anyway, there has recently been a bit of back-and-forth regarding the state of large, old trees at a global scale.

These trees are key in both forest and non-forest ecosystems. The definition of what is ‘old’ and ‘large’ is specific to each region but it is widely accepted that these trees tend to store lots of carbon and are valuable for many species because of their structural complexity.

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David Lindenmayer and colleagues published a note last year on the importance of large, old trees and evidence for their declines, and they expanded on that with an article discussing policy options to deal with these declines.

This is all important stuff and they had me convinced. It makes sense. Large, long lived species are disproportionately vulnerable to threats because they take a long time to reach maturity and they are targeted simply because they are large – for animals see hunting of ungulates, for trees see selective logging.

However, a recent letter by Edward Faison has made me doubt the claims of Lindenmayer. Faison points out that there have been increases in the abundance of large trees in forests in Sweden, Spain, Hungary, Italy and Switzerland. In addition there have apparently been relatively few declines of large trees in North America.

Lindenmayer and colleagues have since rebutted this letter, saying that there is a difference between large old trees and simply large trees.  They point out that there have been increases in Europe and North America but that these increases have been from a very low point since both regions have historically cleared large swathes of forest for agriculture. They also point out the loss of large trees as a result of logging in the tropics as well as in Australia, North America and Siberia.

And yet I am still not entirely convinced.

Don’t get me wrong, I believe that large old trees are probably in decline in the ecosystems they talk about, but is this a general trend all over the place?

I am also a little scared that all of the discourse on this so far has been in the form of reviews/essays that could easily cherry-pick some cases and then craft a nice narrative around them. It is easy to believe the stories we tell ourselves and this is where we as scientists should be most self critical. After all how many beautiful sounding theories have been seen to have nothing to do with how things work in the real world? The only way to confront such problems is with cold, unemotional statistical analysis.

When is a trait not a trait?

Last week I was on a course on using traits for ecological analysis in Coimbra. Verdict: Unimpressed by the course, but impressed by the beauty of the city.

But I digress.

One of the things that kept coming up on the course was what people considered a to be a trait.

Apparently the strict definition that the people running the course was something along the lines of “morpho-physio-phenological traits which impact fitness indirectly via their effects on growth, reproduction and survival, the three components of individual performance” taken from Violle et al 2007.

I agree roughly with this definition.

But there were a few naysayers in our group. Some of them argued that distribution size was a trait or that habitat that a species preferred was a trait. Personally I think these two things are the result of a trait-environment interaction, and are not themselves traits. However,even papers in the Holy Grail of publications, Nature, can get this wrong so I can understand the confusion.

Certain traits may be increase the likelihood of a species found in a region to be found at a particular site
Certain traits may be increase the likelihood of a species found in a region (left) to be found at a particular site (right)

For example, take a regional species pool that is made up of species that vary in traits which impact their fitness. These traits can determine whether a species is present at a particular site.

Trait_filtering 02
Some species may only be found in particular habitats (green patches) and vary in range size compared to others (black line) but we shouldn’t call these traits.

 

If you add up all the areas that a species is present in you have an idea of a species range and also the habitats they occupy. Therefore it is fairly obvious that these two things are not traits but are rather the products of traits.

This is not to say they aren’t useful in some way. Range size (or more accurately area of occupancy or extent of occurrence) is fundamental to one of conservation biology’s flagship projects – the Red List, and knowing the habitats a species uses can be useful in lots of ways.

It would be helpful if we could all agree what we were talking about when it come to traits, as very few of us seem to have thought about it. When people review a paper that uses the word ‘trait’ they should make sure that the term has some meaning and isn’t just used as a sexier synonym for ‘characteristic’ or ‘feature.’

Ecology is fraught with problems of definition (as I have discussed here and here) and personally I think it is one of the things that holds back our science. If our aim is to form meaningful generalisations about how the natural world works, we can’t do it until we agree what the hell we’re talking about in the first place.