How long does it take for logging roads to recover from clearance?

Roads are generally terrible for biodiversity. They fragment habitat, can increase habitat loss and hunting as a result of increased access, and cause direct loss of biodiversity as a result of collisions. However, not all roads are the same. Some are massive, permanent structures, while others are temporary, dirt tracks that may seemingly disappear once they fall into disuse.

One example of ephemeral roads is those that logging companies construct in tropical forests to provide access and transport of logs. There has long been concern that these roads can increase the risk of fires occurring, as well as increasing access for hunting, and other forms of forest exploitation. However, in a recent(ish) paper* has shown that some of the negative effects of logging roads are relatively transient.

In the paper, Fritz Kleinschroth and colleagues showed that in Central African forests, after 30 years of recovery logging roads had similar canopy cover, species diversity, and leaf litter to logged forests nearby* . However, the amount of carbon stored in the form of biomass lagged behind and was only 6% of that seen for logged forests after 30 years of recovery. At this rate, biomass recovery would take more than 300 years.This incredibly slow recovery at first appears puzzling, given that secondary forests, which have had almost all their trees cut down in the past and turned into agricultural fields, tend to take between 60-100 years to recover biomass to pre-disturbance levels (see here for a blog post and here for a recent paper on this). However, the probable cause of this delayed recovery is the compaction of soils on the roads by heavy vehicles which reduces seed germination and root growth***. Taken together the authors suggest these results indicate that logging roads have the potential to act as areas in which timber species could regenerate and that they may become inaccessible to hunters within 10 years.

So how does this study compare to similar ones carried out previously? Firstly, this study is a little different because it is one of the few that used chronosequences to assess recovery, and so the only study I know of which can assess longer-term dynamics on logging roads. However, other studies present a similar picture for the recovery of biomass and forest structure – forest canopy cover recovers relatively quickly (see here and here), but biomass and basal area lag behind (see here and here). The major difference between this study and previous ones is that it presents a more optimistic outlook of biodiversity. Previous studies have estimated that species richness may be 50-95% lower on abandoned logging roads when compared to logged forests (see here, here, and here). As such, the relatively fast recovery of species richness shown by Kleinschroth and colleagues appears to be outside of the norm, and further similar studies will be needed to see whether the pattern of recovery shown in this paper is an outlier. So we can’t really give a solid answer to the question posed in the title of this post – sorry about that.

While results vary from study to study it is obvious that more efforts need to be made to reduce the number of logging roads, their initial impacts to forests, and to help them recover once they are abandoned. In order to reduce the number of roads, reduced-impact logging could be used. This method, which I have been accused of disliking in the past, seems to be very successful in reducing the number of roads in logging concessions where it has been used (see here for an example of this). This is done by producing a plan for road construction prior to any trees being cut, rather than the ad-hoc approach often taken in conventional logging. Reducing the impact of roads could be done by limiting their width. Finally, improving recovery could be done by planting seedlings/saplings on former logging roads, as well as reducing access to roads.

One suggestion that the authors made in their paper that I really like is to re-use logging roads when forests are re-logged. Given that logging typically occurs every 30 years, this would allow some time for recovery of biodiversity on the roads but clearing them would reduce the damage caused by their construction spreading to other areas of the forest.

*I admit it, I’ve been terrible at keeping up with my reading recently.

**John Healy and Fritz have written a nice summary of their paper on the website “The Conversation” which is well worth a read.

***Anecdotal, I know, but I have seen similar things on restored salt marshes in the UK where diggers have been used to breach sea walls. At least for the ones I remember, this resulted in reduced vegetation cover.

 

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Second growth:The promise of tropical forest regeneration in an age of deforestation

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Anyone who knows anything about secondary forests will have come across the work of Robin Chazdon. She has inspired at least one forest ecologist, me, that forests recovering from major disturbances are a subject worthy of study. I’m sure she has done the same for many others out there. So, coming towards the end of my PhD I was excited to see a book that she had written summarising the topic was due to be released and using the last of my NERC funds I bought it. And then I moved house to Spain, where the book sat untouched and unloved in a box for the next year. After I came back to the UK last year, I found the book again and decided I should stop putting off reading it. I read it on trains, buses, on my sofa and occasionally in bed. I once fell asleep reading this book, though admittedly that was on the way back from the BES annual meeting  in Edinburgh, and the gin from the previous night was probably the cause of my sleepiness rather than any bad writing.

The first thing to say is that this book is extremely comprehensive. Though it is not particularly lengthy, running to 316 pages of text, it covers a huge range of topics relating to forest regeneration from traditional knowledge and prehistoric forest transformations by humans to recovery pathways from fire, landslides, volcanic eruptions, logging, and agricultural use. There are also numerous sections on community assembly, functional traits, ecosystem function, and animal and plant interactions. The last section concentrates on reforestation and restoration of degraded forests, making a passionate plea for degraded forests to not be considered as wasteland.

For me the most fascinating parts of the book were those that covered traditional knowledge of forest regeneration and the history of human cultures in tropical forests – both subjects I knew practically nothing about before this book. I was captivated to read that the dayak people of Borneo have five words to define different stages of forest recovery – kurat uraq (1-3 year old scrub that forms after abandonment), kurat tuha (trees > 5 cm in diameter and 5-6 metres in height), kurat batang muda (trees 10-15 cm in diameter), kurat batang tuha (closed canopy secondary forest) and hutan bengkar (primary forest). As Chazdon points out this knowledge shows a striking resemblance to that of forest ecologists. Similarly, Mayan cultures in Central America and Soliga people in the Western Ghats have developed a subtle knowledge of the stages of forest succession. I have always been a bit skeptical of integrating traditional knowledge into ecological science, but this book convinced me that there could be some value to it.

Chazdon masterfully weaves together anthropology, archaeology and ecology in the discussion of prehistorical impacts of humans on tropical forests. She cites evidence of earthworks called geoglyphs similar to the Nazca lines found in the state of Acre in Brazil, swidden agriculture 20,000 years ago in Papua New Guinea and human populations in Central America to dispel the view that any forest is truly untouched. There are probably legacies of human use in most forests, we just can’t identify them. Based on this she, perhaps controversially, critiques recent work suggesting that mature tropical forest biomass density is increasing as a result of atmospheric carbon dioxide. Chazdon’s view is that this increase could well be as a result of recovery from unseen disturbances that happened generations ago.

The section on community turnover during succession is also excellent, with a detailed analysis of the characteristics of short- and long-lived pioneer and shade tolerant, late successional species. At points Chazdon playfully conjures up text resembling Shakespeare’s  “All the world’s a stage” monologue: “The term successional stage is apt. Successional pathways can be viewed as an improvisational drama in several acts, with each act featuring a different set of actors. Some actors perform throughout the drama, but others have cameo appearances of only one act. Although each act sets the stage for the next, forest regeneration has no director and only a roughly sketched script creating a high degree of spontaneity, randomness and uncertainty.” These are amongst my favourite parts of the book, with metaphor mixing with a solid science to help things stick in your mind that might otherwise be easily forgotten.

If I have any criticism of the book, it is that it’s a bit repetitive. This is probably because Chazdon sees succession as ‘an improvisational drama in several acts’ and so the book relies on case studies, rather than synthesising current knowledge to form generalities. However, I think that the repetition helps if you just want to dip in and out of chapters – I don’t think it is necessarily written to be read cover to cover like I did.

That aside if you are interested in the dynamics of forests in any way this book is essential reading. There is no better summary of current thinking on tropical forest succession out there.

New paper: Stand dieback and collapse in a temperate forest and its impact on forest structure and biodiversity

We recently published the first paper from my post-doc in Forest Ecology and Management, so I thought I’d share it here. It marks a bit of shift away from the tropical forests I have previously published about (see posts on that here and here), but it allowed me to continue my work on post-disturbance recovery.


Scientists and policymakers around the world are concerned about the potential effects of forest dieback. Drought and the spread of new pathogens and pests have resulted in increased tree mortality in both the USA and Canada, and these threats are likely to increase in Europe as well. The IPCC recently highlighted forest dieback as a potential major threat, but one about which we know relatively little.  Changes in forest biodiversity and ecosystem services are likely to be particularly severe in ecosystems that show poor resilience. Failure to withstand or recover from drought or pest attack may lead to ‘regime shifts’ resulting in a very different type of system, with many fewer trees.

Luckily for our group my boss, Adrian Newton, found out about a permanent transect that had been set up in the 1950s in a woodland in the New Forest that now appears to be suffering from dieback. The site had been surveyed 4 times between 1964 and 1999, and our team collected more data from the site in 2014. In our recent paper, published in Forest Ecology and Management we used this data to investigate dynamics of the woodland. In particular, we addressed the potential impacts of dieback on forest structure, the causes of these changes and their impact on biodiversity.

Basal area loss in Denny wood from 1964-2014
Basal area loss in Denny wood from 1964-2014

To cut a long story short, the forest lost about a third of its basal area (as you can see above) and over two-thirds of its juvenile trees over 50 years. over 90% of the loss of basal area was due to the death of large beech (Fagus sylvatica) and oak (Quercus rubor) trees.

Climate records from 1964-2014 showed that (a) mean temperature during April-September increased from 1960s to present day; and (b) there were numerous drought yearspost 1976.
Climate records from 1964-2014 showed that (a) mean temperature during April-September increased from 1960s to present day; and (b) there were numerous drought years post-1976 a year which was previously identified as a cause of current mortality.

The external factors causing these changes are not entirely clear, but there have been a number of significant droughts between 1964-2014 as well as increased temperatures (see figures above). In addition, the presence of a number of novel fungal pathogens has been noted in the forest, which may have interacted with drought to further weaken large trees. Recovery in the forest has been very limited, with almost no recruitment of saplings of the canopy dominants (beech & oak) in 50 years. This low recruitment is probably a result of the high density of ponies and deer in the woodland.

Relationship between percentage loss in subplot basal area and (a) percentage grass cover and (b) ground flora species richness.
Relationship between percentage loss in subplot basal area and (a) percentage grass cover and (b) ground flora species richness.

The result of the changes in forest structure is that areas with little tree cover have seen large increases in grass cover and increased ground flora species richness (see figure above). Both of these results indicate that there may be a tipping point at which changes in structure result in rapid increases in grass cover and species richness of ground flora.

Many of the papers on resilience talk about alternative stable states, in which transitions from one type of system to another are difficult to reverse. Though, from the outside, it may appear that our field site shows evidence of a shift to a relatively treeless stable state, we think that this is incorrect. The theory underlying multiple stable states suggests that disturbances causing the regime shift should be a ‘pulse’, when disturbance occurs over a relatively short period and then does not occur again, rather than a ‘press’ disturbance, where the disturbance is present over long periods of time.  However, these conditions are not met by our site where both pulse (i.e. drought) and ongoing press (i.e. overgrazing)  disturbances are present. We think that both of these processes are needed to cause the forest to lose tree cover.

Even if the transition we  have observed is not strictly a ‘regime shift’ it’s still important. Dieback is apparently widespread in the New Forest and is on-going, so the potential impacts could be very significant. As with other cases of dieback it’s difficult to identify appropriate management responses. However, in the case of the New Forest the easiest way to restore resilience would be to protect tree regeneration from the high herbivore pressure in the area.


If you want to read more about our study you can find the paper here and details of our project on forest resilience can be found here. Oh, and here’s a post I wrote about my project a while back. Also, feel free to comment below!

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.

Just what is resilience, anyway?

Last week I organised a workshop bringing together researchers interested in resilience from across the Biodiversity and Ecosystem Service Sustainability (BESS) programme run by NERC. I’ll write about things that came out of it over the next few weeks. Here is my first missive


“Is it real? Is it an obscure object of desire?” my boss Adrian asked during our workshop . Given that  nearly 20 years ago there were 163 different definitions of ecosystem resilience, it is perhaps no wonder that we we having a few problems. Part of this problem is that resilience is a boundary object – a term that is interpreted differently by different communities. During our meeting it became clear, for example, that ecological researchers and policy-makers did not necessarily mean the same thing when they were talking about resilience.

Generally, researchers see resilience as a property of a system. Being researchers, we want to quantify this resilience. However, it turns out that resilience can’t really be viewed as a single thing, since it is made up of a number of different qualities. Along with the expert guidance of Volker Grimm our workshop came up with 3 different elements that are important when assessing resilience for research:

  1. Recovery – The return of a variable to the reference state after a disturbance.
  2. Resistance – A variable staying essentially unchanged despite disturbances.
  3. Persistence – Persistence of the system over time.

Using these three different properties allows researchers to look at different aspects of resilience and compare across systems. Making such comparisons is actually very difficult due to constrains on time and funding, as well as logistical problems. For example, to compare resistance of different communities you would ideally apply different intensities of disturbance in different locations. This may be possible in some relatively ‘fast’ systems such as grasslands but it is unlikely that you would get permission to do this to a woodland where you might have to cut trees down. In order to resolve this, mechanistic models can be exceptionally useful for investigating different scenarios of change. Combining this with empirical data collection in the same system can help us gain a more detailed understanding of resilience. This is something we are aiming to do in our current project as part of my post-doc work.

Policy makers on the other hand generally view resilience as a goal. Recently policy documents have begun to mention the importance of resilience. For example, one of the Convention on Biological Diversity’s 2020 aims is to:

By 2020, ecosystem resilience and the contribution of biodiversity to carbon stocks has been enhanced, through conservation and restoration, including restoration of at least 15 per cent of degraded ecosystems, thereby contributing to climate change mitigation and adaptation and to combating desertification.

Similarly the environment white paper in published by the UK government in 2010 mentions resilience 36 times and the Welsh government is aiming to create:

A biodiverse natural environment with healthy functioning ecosystems that support social, economic and ecological resilience and the capacity to adapt to change.

It is also included in US and Australian policy. So in the case of policy-makers it becomes clear that resilience is seen as a target. While for researchers resilience can mean something very specific policy-makers probably consider it to be closest to the previous definition of persistence.  At our workshop there were plenty of anecdotes about policy-makers saying things like “resilience is the new sustainability” and telling civil servants to “stick some resilience in your report, it’s the new thing.” There were also reports that some policy-makers wanted the production of maps of resilience. I think this is potentially dangerous. Given that the ratio of empirical work to conceptual stuff/reviews and perspectives pieces is about 1:1000 we simply don’t have enough evidence to produce these maps at the moment. If push came to shove then we could probably come up with a best guess based on ecological theory, but even then there would be all sorts of caveats.

I think it’s clear we will never reach a point where there is one definition of resilience that fits everyone’s need. However, when we talk about resilience we need to be clearer about what we mean by it. So next time you use it in a paper, for the love of god, define it.

*Edit #1 – I just came across this nice post by Jeremy Fox on defining stability concepts in ecology, which, if might be a useful companion piece to what I said here.

*Edit #2 – Ambroise Baker who helped organise the workshop with me has a short summary of the meeting over on the Lake BESS blog, you can see that here.

How long does tropical forest take to recover from agricultural clearance?

Secondaryforest4
Intermediate secondary forest in Paragominas, Para, Brazil – Photo credit to the fantastic Ricardo Solar, you can see more of his pics here

Today our work on the recovery of secondary tropical forests got published in Royal Society Proceedings B. I’m really chuffed with this piece of work and in this blog I’m going to summarise what we found out and why I think it’s important. If you want to read the paper you can get it here.

Large areas of tropical forest have been cleared for agriculture over the last 100 years.

Why does this matter? Well it matters because these forests are vital for the unique biodiversity in the tropics but also because humans can benefit from them remaining intact.

Their loss causes extinction, release of carbon into the atmosphere – worsening climate change, and changes the ecosystem services we get from these forests.

Because of the importance of these forests their restoration is seen as a priority by some. There are valiant attempts to restore tropical forests in Brazil and various Central American countries. In addition there are also international initiatives that aim to encourage the restoration of carbon and biodiversity (E.g. CBD & REDD+). These are great and ambitious aims but, until now, we didn’t really know how long these recoveries took, or whether recovery was different for different disturbance and forest types.

To solve all this we collected the biggest dataset yet compiled on recovery of aboveground, belowground and soil carbon as well as plant species richness and community composition following agricultural clearance. All this data came from previous studies.

Carbon_pools_colour

We found that after about 80 years aboveground carbon storage was around 85% of that found in undisturbed forests, while belowground carbon storage seemed to recover more slowly. Soil carbon showed no relationship with time since clearance.

Richness_colour

In terms of biodiversity both tree and epiphyte species richness seemed to increase over time, with tree richness recovering after around 50 years since disturbance but epiphytes took around 100 years.

Prop_sp

However, when we looked at species that are found in the undisturbed forests, relatively few of them are found in the recovering forests. They didn’t seem to accumulate over time either. Given that these species are likely to be more prone to extinction it is worrying that they don’t seem to be doing very well in secondary forests.

We think that carbon recovers relatively well following abandonment of land since there tends to be a rapid influx of woody species. However, we also think that complete recovery of carbon is likely to take more than a century since this is likely to be dependent upon large, slow-growing trees.

Differences between tree species richness recovery and that of epiphytes is likely to be because tree seeds are more easily transported between forests than those of epiphytes. Also epiphytes seem to be found more on big trees, and there don’t tend to be many of these in secondary forests.

The lack of recovery of species found in undisturbed forests is perhaps the most disturbing thing that we found. We think that to improve this situation there may be a need for management of these forests by planting trees and helping to increase dispersal of seeds throughout the non-forest areas.

Disturbed forests like this are not worthless.
Regrowing forests like this are vital if we wish to conserve biodiversity in our human dominated world. Photo credit again to Ricardo Solar

There’s been lots of great work recently on the value of disturbed forests. We hope our work goes into a bit more detail where the soon-to-be-classic work of Luke Gibson etl al  left off which showed that primary forest has greater conservation value than any types of disturbed forest in the tropics. We agree with this, particularly for specialist species. However, most tropical forests are not primary forests and have been logged, cut down or burnt at some point in recent history. Because of this we think that older secondary forests need to be recognised as important for conservation and carbon storage and their clearance should be avoided. These forests are not worthless.