Thursday, December 19, 2013

More links for 2013: the 'new' conservation, the IPCC report in haiku, and more.

Conservation science has been at the receiving end of some harsh criticisms in the last couple of years, particularly from the current chief scientist of the Nature Conservancy, Peter Kareiva (e.g. 1).  They have suggested that conservation science needs to be redefined and refocused on human-centred benefits and values if it is to be successful. Some pushback in the form of TREE article from Dan Doak et al. suggests that reframing conservation in terms of its human benefits is not the best or only solution.

In a similar vein, another new paper in TREE asks what issues should the conservation community be addressing. A short-list of 15 issues suggests highly specific problems that should be addressed soon, including the exploitation of Antarctica, rapid geographic expansion of macroalgal cultivation for biofuels, and the loss of rhinos and elephants.

Even if the official IPCC report proves too long or dry for the average person to read before the end of the year, there is also a haiku version. The pretty watercolour illustrations don't make the report any more cheerful, unfortunately.

Finally, a new journal, "Elementa: Science of the Anthropocene" seems positioned to focus precisely on these kind of issues. According to their website: 

"Elementa is a new, open-access, scientific journal founded by BioOne, Dartmouth, Georgia Tech, the University of Colorado Boulder, the University of Michigan, and the University of Washington.
Elementa represents a comprehensive approach to the challenges presented by this era of accelerated human impact, embracing the concept that basic knowledge can foster sustainable solutions for society....Elementa publishes original research reporting on new knowledge of the Earth’s physical, chemical, and biological systems; interactions between human and natural systems; and steps that can be taken to mitigate and adapt to global change. "

It will be interesting to see how it develops.

Tuesday, December 17, 2013

Holiday caRd 2013

A holiday pResent made of competition from the EEB & Flow :-)

(Easy to copy and run if you choose "view raw" in the lower right hand corner. Just copy and paste into R, it will do all the work. You will need to download and install R if you don't already have it.)

Tuesday, December 10, 2013

Ecological processes may diffuse through evolutionary time: an example from Equidae

Body mass evolution and diversification within horses (family Equidae). Lauren Shoemaker, Aaron Clauset. 2013. Article first published online: 5 DEC 2013. Ecology Letters. DOI: 10.1111/ele.12221

One of the things that community phylogenetic approaches have tended to overlook is that how we interpret phylogenetic relationships depends on a model of evolution. For example, the assumption that closely related species also are similar in their traits is implicitly relying on a particular model of trait evolution. One downside to this approach is that different models of evolution may provide different conclusions about macroecological patterns and processes (competition, environmental filtering, facilitation). 

For example, a new paper in Ecology Letters provides an example of how patterns of trait divergence and adaptive radiation can evolve as a result of diffusion evolution, rather than from a single strong ecological pressure. The paper by Shoemaker and Clauset focuses on the Equidae (horse) family, which underwent an adaptive radiation 56 million years ago, resulting in massive increases in diversity and in trait variation, particularly in body size, habitat type and range size, diet, life span and reproductive traits. Several explanations have been proposed for this radiation and in particular the great increase in body size variation (species are estimated to have ranged between 10-1200 kg). A diversity-focused model explains body size divergence as the result of macroecological competition for niches. A limited number of niches at a given size are assumed to be available, and these niches vary in quality or attractiveness. Increasingly extreme body sizes (and presumably less desirable niches) evolve as niches are filled at more desirable sizes. The result is a correlation between diversity and body size variation, much like the one seen in Equidae. The alternative model considered suggests that trait space is filled via diffusion or a random walk, with the only assumption being that there are some physiological constraints – here a hard limit on minimum size, and an assumption of increasing extinction risk as maximum size increases.
From Shoemaker + Clauset, 2013.
Using mathematical models of Equidae body size evoluation, the authors’ results were very clear (figure below): “Using family Equidae as a model system, we found that macroevolutionary ‘diffusion’, in which selective effects on species body size vary independently of the occupation status of nearby niches, explains substantially more of the observed changes in the Equidae body mass distribution over 56 Myr (Fig. 5) than does a diversity-driven mechanism...”. The results are interesting because they are a reminder that the relationship between macroecological patterns (for example, of traits like body size) may be related to evolutionary history in a much more nuanced way than ecophylogenetic studies sometimes assume. Rather, Shoemaker and Clauset suggest that the better performance of the diffusion model--rather than indicating that competition is *not* important--may be effective at capturing many independent ecological interactions and selective effects all driving body size evolution. A macroevolutionary model of competitive effects on trait divergence is may simply be unrealistic, since competition and ecological interactions may be more localized and less generalized in their effects across the entire Equidae family.
From Shoemaker and Clauset, 2013. Left - competition model, Right - diffusion model

“A large role for diffusion does not undermine the general ecological importance of competition, but rather clarifies its role in generating broad-scale patterns for horses in particular, and for evolving systems in general. Macroevolutionary diffusion is an effective large-scale description of many roughly independent ecological interactions and evolutionary constraints on species size variation. Short-term selective effects on size for a particular species can stem from any number of specific mechanisms, including but not limited to competition over ecological niches. So long as the magnitude and direction of these effects, as defined at the species-level, are roughly independent across the taxonomic group, the large-scale pattern will be well described by diffusion. Ecological competition may thus be crucial for individual species, but its effects are more diffuse at the large scale because competition is typically a local process.”

This is a reminder that many phylogenetic hypotheses (trait divergence or convergence in communities, etc) are too simplistic in their assumptions that broad macroecological processes dominating, and instead need to recognize that ecological processes are often numerous, independent, and local, making outcomes more nuanced than usually assumed. 

Thursday, December 5, 2013

What can the future of ecology learn from the past?

Ecology has been under pressure to mature and progress as a discipline several times in its short life, always in response to looming environmental threats and the perception that ecological knowledge could be of great value. This happened notably in the 1960s, when the call for ecology to be better applicable occurred in relation to the publication of Silent Spring and fears about nuclear power and the Manhattan Project. Voices in academia, government, and the public called for ecology to become a “Big Science”, and focus on bigger scales (the ecosystem) and questions. And yet, “[Silent Spring] brought ecology as a word and concept to the public…A study committee, prodded by the publication of the book, reported to the ESA that their science was not ready to take on the responsibility being given to it.”

Arguably ecology has grown a lot since then: there have been advances in statistical approaches, spatial and temporal considerations, mechanistic understanding of multiple processes, in the number and type of systems and species studied, and the applications being considered. But it is once again facing a call (one that frankly has been ongoing for a number of years) to quickly progress as a science. The Anthropocene has proven an age of extinctions, human-mediated environmental changes, and threats to species and ecosystems from warming, habitat loss and fragmentation, extinctions, and invasions abound. Never has (applied) ecology appeared more relevant as a discipline to the general public and government. This is reflected in the increasing inclusion of buzzwords like “climate change”, “restoration”, “ecosystem services”, “biodiversity hotspot”, or “invasion” as keys to successful self-justification. Also similar to the 1960s is the feeling that ecology is not ready or able to meet the demand. Worse, that the time ecology has to respond is more limited than ever.

This first point--that ecology isn’t ready--is repeated in Georgina Mace’s (the outgoing president of the British Ecological Society) must-read editorial in Nature. The globe is in trouble, from climate change, disease, overpopulation, loss of habitat and biodiversity and Mace argues that ecology is incapable in its current form of responding to the need. She suggests that unless ecology evolves, it will fail as a discipline. Despite the growth of ecology that followed the 1960s, it is still a 'small' discipline: collaborations are mostly intra-disciplinary, data has been privately controlled, and the tendency remains to specialize on a particular system or organism of interest. However, this 'small' approach provides very little insight into the big problems of today - particularly understanding and predicting how the effects of global change on ecosystems and multispecies assemblages. To Mace, the solution, the undeniable necessity, is for ecology to get bigger. In particular, collaborations need to be broader and larger, with data sharing and availability (“big data”) the default. Ecological models and experiments/observations should be scaled up so that we can understand ecosystem effects and identify general trends across species or systems. In this new 'big' ecology, “[g]oals would be shaped by scientists, policy-makers and users of the resulting science, rather than by recent publishing trends”. Making research more interdisciplinary and including end-product users would allow the most important questions to receive the attention they deserve.

The difficulty with the looming environmental crises and the pressure on ecology to grow, is that the important decisions to be made have to be made rapidly and perhaps without complete information. Often scientific progress is afforded the time for slow progression and self-correction. After all, change is costly and risky, it requires reinvesting effort and funding, and may or may not pay off, and so science (including ecology) is often conservative. For example, a conservative mind would note that Mace’s suggestions are not without uncertainty and risk. Big data, for example, is acknowledged to have its strengths and its weaknesses, it may or may not be the cure-all it is touted as. Regardless of the amounts of data, good questions need to be asked and data, no matter how high quality, may not be appropriate for some questions. Context is often so important in ecology that attempts to combine data for meta-analysis may be questionable. Long running arguments within ecology reflect the fear that making ecological research more useful for applications and interdisciplinary questions may come at the expense of basic research and theory. It seems then that ecology is in an even worse scenario than Mace suggests, since not only must ecology change in order to respond to need, but it also must predict with incomplete information which future path will be most effective.

So ecological science is at an important junction with choices to make about future directions, limits on the information with which to make those choices, little time to make them, and much pressure to make them correctly. Perhaps we can take some comfort from the fact that ecology has been here before, though. There are some lessons we can draw from ecology’s last identity crisis, both the successes and failures. The last round resulted in ecology gaining legitimacy as a science and being integrated into policy and governance (the EPA, environmental assessments, etc). It appears, particularly in some countries, that ecology is more difficult to sell to policy and government today, but at the very least ecology has established a toehold it can take advantage of. Ecology also tried to focus on bigger scales in the 1960s--the concept of the 'ecosystem' resulted from that time--but the criticism was that the new ideas about ecosystems and evolutionary ecology weren't well integrated into ecological applications, and so their effect wasn't as broad as it could have been. Concepts like ecosystem services and function today integrate ecosystem science into applied outputs, and the cautionary tale is the value of balancing theoretical and applied development. It also seems that ecology must first consider what its duty as a science is to society (Mace’s assumption being that we have a great duty to be of value), since that is the key determinate of what path we decide to take. Then, we can hopefully consider what have we done right in recent years, what have we done wrong, and then decide where to go from here.
Page from "Silent Spring", Rachel Carson.

Tuesday, December 3, 2013

Biodiversity hotspots: are we missing other priorities?

ResearchBlogging.orgBiodiversity hotspots are regions that harbour disproportionate biodiversity, especially of species with small ranges, and regarded as major conservation priorities (Zachos and Habel 2011). Biodiversity hotspots occur in some of the most exotic and romanticized regions around the world, such as Madagascar, the Caribbean Islands, the Western Ghats of India, and the Succulent Karoo of South Africa. By preserving these regions, we disproportionately preserve the diversity of life on Earth, and thus these conservation efforts are seen as critically important.

However, some argue that the emphasis on global biodiversity hotspots leaves other unique or less diverse regions open to human impacts since they have a perceived low natural value, and certainly not valuable enough to stem other economically motivated activities. This mind set may put large habitats under increased risk. This conflict is front and center in a recent paper by Durant and colleagues in Diversity and Distributions (Durant et al. 2013). In this paper, Durant et al. argue that large, globally relevant systems like hot deserts are under-protected, leading to potentially major collapses in these systems.

Ahaggar Mountains Oasis, from Wikipedia

They use the Sahara desert as the case study and show that while conservation efforts have been focused on hotspots, the majority of large vertebrates in the Sahara desert are now extinct or critically endangered.  System like hot deserts are important for human economic well-being, but our activities there have greatly reduced the amount of intact, undisturbed habitat.

Durant et al. argue, that had there been greater conservation effort and scientific interest in the Sahara, the catastrophic declines in large vertebrates may have been averted. This paper highlights the reality that we often undervalue certain ecosystems, regardless of the important ecosystem services and functions that they deliver.

S. M. Durant, T. Wacher, S. Bashir, R. Woodroffe, P. De Ornellas, C. Ransom, J. Newby, T. Abáigar, M. Abdelgadir, H. El Alqamy, J. Baillie, M. Beddiaf, F. Belbachir, A. Belbachir-Bazi, A. A. Berbash, N. E. Bemadjim, R. Beudels-Jamar, L. Boitani, C. Breit (2013). Fiddling in biodiversity hotspots while deserts burn? Collapse of the Sahara's megafauna
 Diversity and Distributions DOI: 10.1111/ddi.12157

Tuesday, November 26, 2013

Can you teach an old bird new (migratory) tricks?

Jennifer A. Gill, José A. Alves, William J. Sutherland, Graham F. Appleton, Peter M. Potts and Tómas G. Gunnarsson. 2013. “Why is timing of bird migration advancing when individuals are not?” Proc. B. Vol. 281, no. 1774.

Phenological responses have been used as one of the major indicators of climate change. The timing of flowering and fruiting, the return of migrant birds and insects from winter habitats are easily and often measured, and records going back decades or centuries sometimes exist. Most importantly, shifts in phenological indicators are some of the strongest connections between rising temperatures and biological and ecological responses (for example). There is plenty of evidence, for example, that some migrant bird species are returning to their breeding grounds earlier than ever. These migratory birds may be responding (via migration timing) to warming temperatures in several ways: there may be plasticity or flexibility in individual timing of migration which allows them to respond to changing temperature cues; or species may also show adaptation via changes in the frequency of individuals with different migratory timings (microevolution). In cases where migratory species are responding to climate change, distinguishing the mechanisms allowing them to do so is surprisingly hard. Early arrival of migratory bird species is often explained as being due to individual plasticity or flexibility in “choosing” the date of migration, but the majority of studies of this phenomenon include little or no information about individual behaviour, only changes in the mean date of arrival for the entire population.

For this reason, Gill et al. looked at individual, rather than average population, arrival dates for Icelandic black-tailed godwits in south Iceland. Icelandic black-tailed godwits (“godwits” for the sake of brevity) have shown significant advances in the last 20 years in the timing of their spring arrival to the shores of Iceland, and these advances appear to relate to increasing temperatures. The population has also been banded such that 1-2% can be individually identified and tracked throughout their migratory range. Although only adults (of unknown age) were banded at the start of the experiment in 1999, recently chicks have also been banded and released and so a wide range of demographic classes are included with the banded birds.
From Gill et al. 2013.

When Gill et al. looked at date of arrival across 14 years for each individual, their results were surprisingly clear and cohesive. As previously reported, the population mean date of arrival in South Iceland had advanced as much as 2 weeks. But, this advance is not reflected in individual timing of arrivals over that same period – if a bird tends to arrive on a given day, they will continue to arrive on approximately that day every year, independent of temperature conditions. Instead, the population trend appears to be driven entirely by birds born in recent years – young individuals (recently hatched) tend to have arrival dates much earlier than older individuals. At least for the godwits, population wide trends in migration dates are actually driven by only a subset of the individuals.

From Gill et al. (2013)
Often it is assumed that migratory birds are responding to warming temperatures on an individual level: individuals respond to changing cues, resulting in shifts in arrival date. This study suggests otherwise, and finds that the important mechanism is not individual plasticity or microevolution but rather related to demographic shifts in arrival time. As to why younger birds arrive earlier, it is not clear, but may relate to the observation that nest building and hatching dates are also advancing. It may be that natal conditions are important – the authors observed a variety of possibly inter-related changes such that hatching dates are advancing and chick sizes are increasing, and the suggestion that mortality rates of later arriving individuals may also be higher. "Environmentally induced advances in arrival dates of recruits could operate through: (i) carry-over effects of changing natal conditions, (ii) changing patterns of mortality of individuals with differing arrival times, or (iii) arrival times being initially determined by conditions in the year of recruitment and individuals repeating those timings thereafter."

These results make some predictions about which populations of migratory birds might have the most ability to respond to warming climate - most likely those with shorter migratory distances, shorter times to reproduction and shorter-lifespans (hence decreasing the lag-time required for the population to catch up to temperature). It may also have relevance for other non-bird species that also rely on careful timing between phenology and temperature. Correspondingly, it suggests limitations - if individual behaviour is so inflexible and constrained, our hopes that some species may respond to climate change with behavioural changes seem far to simplistic.

Thursday, November 14, 2013

How many traits make a plant? How dimensionality simplifies plant community ecology.

Daniel C. Laughlin. 2013. The intrinsic dimensionality of plant traits and its relevance to community assembly. Journal of Ecology. Accepted manuscript online: 4 NOV. DOI: 10.1111/1365-2745.12187

Community ecology is difficult in part because it is so multi-dimensional: communities include possibly hundreds of species present, and in addition the niches of each of those species are multi-dimensional. Functional or trait-based approaches to ecology in particular have been presented as a solution to this problem, since fewer traits (compared to the number of species) may be needed to capture or predict a community’s dynamics. But even functional ecology is multi-dimensional, and many traits are necessary to truly understand a given species or community. The question, when measuring traits to delineate a community is: how many traits are necessary to capture species’ responses to their biotic and/or abiotic environment? Too few and you limit your understanding, too many and your workload becomes unfeasible.

Plant communities in particular have been approached using a functional framework (they don't move, so trait measurements aren't so difficult), but the number and types of traits that are usually measured vary from study to study. Plant ecologists have defined functional groups for plants which are ecologically similar, identified particular (“functional”) traits as being important, including SLA, seed mass, or height, or taken a "more is more" approach to measurements. There are even approaches that capture several dimensions by identifying important axes (leaf-height-seed strategy, etc.). Which of these approaches is best is not clear. In a new review, Daniel Laughlin rather ambitiously attempts to answer how many (and which) traits plant ecologists should consider. He asks whether the multi-dimensional nature of ecological systems is a curse (there is too much complexity for us to ever capture), or a blessing (is there a limit on how much complexity actually matters for understanding these systems)? Can dimensionality help plant ecologists determine the number of traits they need to measure? 
From Laughlin 2013. The various trait axes (related to plant organs) important for plant function.
Laughlin suggests that an optimal approach to dimensionality should consider each plant organ (root, leaves, height, figure above). Many of the traits regularly measured are correlated (for example, specific leaf area, leaf dry matter content, lifespan, mass-based maximum rate of photosynthesis, dark respiration rates, leaf nitrogen concentration, leaf phosphorus concentration are all interrelated), and so potentially redundant sources of information. However, there are measurements in the same organ that may provide additional information – leaf surface area provides different information than measures of the leaf economic spectrum – and so the solution is not simply measuring fewer traits per organ. Despite redundancy in the traits plant ecologists measure, it is important to recognize that dimensionality is very high in plant communities. Statistical methods are useful for reducing dimensionality (for example, principle coordinate analysis), but even when applied, Laughlin implies that authors often over-reduce trait data by retaining to only a few axes of information.

Using 3 very large plant species-trait datasets (with 16-67(!) trait measures), Laughlin applies a variety of statistical methods to explore effective dimensionality reduction. He then estimates the intrinsic dimensionality (i.e. the number of dimensions necessary to capture the majority of the information in community structure) for the three datasets (figure below). The results were surprisingly consistent for each data set – even when 67 possible plant traits were available, the median intrinsic number of dimensions was only 4-6. While this is a reasonably low number, it's worth noting that the number of dimensions analyzed in the original papers using those datasets were too low (2-3 only).
From Laughlin 2013. The intrinsic number of traits/dimensions
necessary to capture variation in community structure.
For Laughlin, this result shows that dimensionality is a blessing, not a curse. After all, it should allow ecologists to limit the number of trait measures they need to make, provided they choose those traits wisely. Once the number of traits measured exceeds 8, there appears to be diminishing returns. The caveat is that the traits that are important to measure might differ between ecosystems – what matters in a desert is different than what matters in a rainforest. As always, knowing your system is incredibly important. Regardless, the review ends on a highly optimistic note – that complexity and multi-dimensionality of plant communities might not limit us as much as we fear. And perhaps less work is necessary for your next experiment.

Monday, November 11, 2013

Exploring the intersection of conservation, ecology and human well-being

I've seen a number of articles recently that explore in different way the intersection of environment and ecology, conservation and human societies. In particular, Frontiers in Ecology and Evolution (the free ESA journal you are gifted as a member) has dedicated an entire issue to the question of climate impacts on humans and ecosystems, and the papers cover important topics relating to changing climate and its effects on biodiversity, ecosystem integrity and human societies. Economic predictions suggest costs from fires, drought, and rising sea levels: whether protecting ecosystems will preserve their function and so mediate these costs to humans and other organisms is explored in depth. Of course, scholarly papers can be impersonal, but another article about the struggles of Inuit in the north to adapt (or not) to changing ecosystems provides a smaller, more human look at climate, development, and cultural change. Another study predicts that for some cultures, climate change (and the resulting difficulties growing food, maintaining livelihoods, obtaining water and human health risks) may be too much for them to withstand.

Finally, a long-form story by Paul Voosen in The Chronicle of Higher Education asks "Who is conservation for?". While not a novel question, through interviews with Gretchen Daily and Michael Soule, Voosen does a thorough job of illuminating conservation biology in the context of real-world limitations and realities, historical precedents, ongoing tensions between new and old approaches to conservation, and economic development. In the end it asks what motivates conservation: do we conserve purely for the sake of biodiversity alone, for economic and functional benefits, for aesthetic reasons, for charismatic and at-risk species? As Voosen subtly hints in the article, if leading conservation biologists can't agree on the answer, will it ever be possible to be effective?

Slightly unrelated, but there is a great short film online about the life of Alfred Russel Wallace, the less celebrated co-discoverer of natural selection.

Thursday, November 7, 2013

Managing uncertain restoration outcomes*

Human activity has impacted ecosystems around the globe, and the value of intact, functioning habitats is increasingly appreciated. One of the most important management options to maintain or increase the amount of functioning habitat is to restore destroyed, disturbed and degraded habitats. However, there is much concern about how predictable restoration efforts are and the management strategies that will maximize success. The reality that systems may reach very different, alternative ecosystem states is a problem for managers when they desire well defined outcomes. Thus the ability to understand and predict how different factors affect restoration outcomes would be an important development.

In the current issue of the Journal of Applied Ecology, Grman and colleagues examine how different factors influence prairie restoration outcomes –specifically the diversity and composition of the restored habitat. They considered several management, historical and environmental factors. For management, they compiled information on the type of planting, the diversity and density of sown seeds and fire manipulation. For local environmental variables, they considered different soil characteristics, shade levels, and site area. The historical influences included land-use history, rainfall during seed sowing and site age. Finally, they also considered the landscape context; specifically what habitats surrounded the restoration site.

Grman and colleagues show that restoration outcomes are most influenced by management decisions and site history. The density, composition and diversity of sown seeds had the greatest impact on restoration outcomes. Species richness was highest in sites sown with high diversity. High sowing density resulted in high beta diversity among sites. Site history had significant effects on non-sown diversity, but did not influence the diversity of sown species. Site characteristics failed to predict local diversity, but they were important for among site beta-diversity.

If success is measured in terms of species diversity, then this work clearly shows that management decisions directly influence success. Surprisingly, site characteristics had a minor influence on success, despite conceptual and theoretical models that predict system sensitivity to abiotic influences. This work reinforces the need to develop the best management options for prairie restoration and that the influences of site history and local conditions can be overcome by sowing decisions and site management.

Grman E., Bassett T. & Brudvig L.A. (2013). Confronting contingency in restoration: management and site history determine outcomes of assembling prairies, but site characteristics and landscape context have little effect. Journal of Applied Ecology, 50, 1234-1243.

Wednesday, November 6, 2013

Community structure - what are we missing?

Some of the most frequently used ecological concepts can be difficult to define. Sometimes this lack of clarity leads to a poor understanding and a weak base for further research. A great example is “community structure”, a concept frequently mentioned and rarely defined that probably changes a lot from use to use. The phrase “we’re interested in how communities are structured” is tossed around a lot, and I suppose an understood definition is that community structure encompasses the species that are present in a community and their abundances. Community structure may refer to  both a very simple concept (the abundances of species present in a community) and a very complicated one, connecting as it does mechanisms and models, observational data, and statistical measures. As a result, the precise way that ecologists delineate community structure and quantify it is both varied and vague.

The connection between models, community
structure and metrics.
In the literature, it seems that there are two ways of approaching “community structure”: bottom-up, in which community structure is a predicted outcome of theoretical models of different mechanisms, and top-down, in which community structure is measured in a relatively statistical or descriptive fashion. Both are valuable approaches: while statistical metrics often are interpreted as providing evidence for particular models or mechanisms, the reverse logic – that a model predicts particular results for a given metric – is rarely explicitly considered. Making connections between the model results and the descriptive metrics might actually be fairly difficult. Model predictions are often complex and multidimensional, predicting changes through time, growth rates, the combinations of species that can or cannot coexist (but only if assumptions hold), or particular relationships between measures like diversity, abundances, and range sizes. Metrics are necessarily confined to a few dimensions (or perhaps are ordination approaches), focus on straightforward observational measures like abundance and presence, and further include observational error (sampling, etc). Because community structure means something different to these two approaches, the connections between metrics and models are poorly explored. A theoretician might find it difficult to relate ordinations of communities with the typical predictions from a mathematical model (which might be something like growth rates in relation to changes in abundance), while someone collecting field data might feel that the data they can collect is difficult to relate to the predictions of models.

Part of the problem is that for a long time, the default focus was on what types of interactions structured communities (environment, competition, predation, mutualisms), and niches were assumed to be necessarily driving community structure. The type of measurements and metrics used reflected this search for niches (e.g. comparing environmental gradients with community structure). Many quantitative metrics may tell you something about how community structure relates to different variables (spatial, environment, biotic) and how much variation is still unexplained. The consideration that niches might not always be important eventually led ecologists to compare patterns in community structure to random, null, or neutral expectations. As a result, in the simplest cases the answers to questions about community structure and niches are binary – different from random (niches matter), or not. Looking for complex patterns predicted by models-for example, the relative contribution of niche based and neutral processes to community structure-is difficult using common metrics of community structure (although there are some papers that do a good job of this).

It is interesting that this problem of disconnection between theoretical models of community structure and community structure metrics received the most attention through criticisms of phylogenetic metrics of diversity. There, patterns of over- and under-dispersion were criticized for not being the necessary outcome from models of competition or environmental filtering (i.e. Mayfield and Levine 2010). While those criticisms were mostly fair, they are equally deserved in most studies of species diversity, where patterns in ordinations or beta-diversity are frequently used to infer mechanisms. In contrast, one of the best approaches thus far to integrating model predictions for community structure with metrics of community structure are null models. Though they differ greatly in ecological realism and complexity, null models suggest expected community structure or metric values if none of the expected processes are structuring a community.

One of the greatest failings of the top-down approach is that recognizing patterns outside of the expected, such as those that include stochasticity or a combination of different processes, or the effects of history, is nearly impossible. Models that can incorporate these complexities provide little suggestion of how the patterns we can easily record in communities might reflect complex structuring processes. Ecological research is limited by the poor connection between both top-down and bottom-up approaches and its vague definition of community structure. Patterns more complicated than those that the top-down approach searches for are likely being missed, while relations between models and metrics (or development of new metrics) aren’t considered often enough. One solution might be to more meaningfully define community structure, perhaps as the association (or lack thereof) between the combination of species present in a community and the combination of abiotic and/or biotic processes present. This association is generally compared to an association between species and processes that might arise from random effects alone. The difference is that structure shouldn’t be considered separately from the processes that produce it, and the connections should be explicitly rather than implicitly made.

Thursday, October 31, 2013

What scares ecologists?

In the spirit of Halloween, a non-comprehensive list of a few of the things that have frightened ecologists. The things we are scared of vary, with career trajectory and stage (graduate student, post-docs, faculty, non-academic), educational background, and goals. And even if the business of ecology doesn't scare you, some of the things we study should...

A few scary things

-That ghostly thesis - will it ever solidify?

-Vampire reviewers: they've been around forever, they've seen everything, and they're looking for blood. (uncommon)
The whole process is pretty frightening.

-The job market (or lack thereof?)

Fun but troublesome

-That our work is invisible

And a few (of many) ecological topics that are truly scary


And the incredibly deadly mosquitoes?

(and all the pathogens it carries)

Monday, October 28, 2013

Waste not, want not? How human food waste changes ecosystems

Daniel Oro, Meritxell Genovart, Giacomo Tavecchia, Mike S. Fowler and Alejandro Martínez-Abraín. 2013. Ecological and evolutionary implications of food subsidies from humans. Ecology Letters. Volume 16, Issue 12, pp 1501–1514. DOI: 10.1111/ele.12187

Humans have always been connected to their environment, directly and indirectly. Ecologists in particular, and people in general, have been thinking about the causes and consequences of these connections for hundreds of years. One form of interaction results when human food resources become available to other animals – for example, through waste dumps, crop waste, fishery by-catches, bird feeders, or road kill. Starting with middens and waste piles in early human settlements, our food waste has always passed t
Garbage dump in India.
o other species. And while rarely considered compared to human impacts like habitat destruction and climate change, a new review by Daniel Oro and colleagues argues that these subsidies have shaped ecosystems around the globe.

Human food waste (aka subsidies) may come from a variety of human activities, with the three most prominent being crop residuals (remnants of harvest remaining on fields), waste dumps, and fishery discards (by-catch thrown overboard). Each of these forms of subsidy occurs globally and large numbers of species rely partially or completely on them for food. For example, dumps are global in distribution, and contain enough edible waste to attract 20-30% of all mammal and bird in a region (particularly omnivorous and carnivorous species). Crop residues usually attract herbivorous or granivorous species (particularly birds), while fisheries’ waste alter marine ecosystems. Eight percent of all catch (~7 million tonnes!) is simply released back into the ocean, and this supplements species across the food web, including half of all seabirds.

Food waste from human activities may not seem so terrible – after all, they are predictably available, easy to access, fast to forage, and can lead to increased condition and fertility among species that take advantage of them. For example, seabirds foraging among fishing boats for by-catch take advantage of the predictability of boat (and food) appearances and as a result have decreased foraging time and areas, higher individual fitness and reproductive success, and ultimately increased population growth. But the authors suggest that these benefits must be considered in a more complicated web of interactions. After all, human food subsidies tend to be much more predictable than natural sources of food and quickly have large effects spanning from individuals, communities, ecosystems, and evolutionary pressures.

Individuals often, though not always, experience positive effects from subsidies – increased biomass, fertility, and survival, accompanied by changes in dispersal and ranges. If food waste draws in high densities of individuals, it may be associated with greater disease occurrence, or draw in predators attracted to easy pickings. Populations also often respond positively to food subsidies, and become larger and more stable as food waste availability increases. But this boon for one species can cascade through the food web, and have large negative effects in communities and ecosystems. For example, yellow-legged gulls are found around dumps and fishing trawlers, taking advantage of the quantities of food available there, and as a result have increased greatly in population. The downside is that in turn these larger populations increase predation pressure on other vulnerable seabird species. Seabirds in particular can create complicated interactions between human food waste and far-flung ecosystems, connecting as they do both terrestrial and marine systems, moving nutrients, pollution, and calories between systems and through trophic levels.

Snow goose exclosure in northern Canada.
Only the small green rectangle has avoided goose grazing.
A famous example of the unexpected consequences of waste subsidies is the snow goose (Chen chen caerulescens). Snow geese have moved from feeding predominantly on marsh plants to landing en masse in farmers’ fields to feed on grain residues. This new and widespread source of food lead to a population boom, and the high numbers of geese stripped away the vegetation in the arctic habitats where they summer and breed. Agriculture food subsidies in southern habitats were felt far away in the arctic, as migratory snow geese tied these systems and food webs together. Though snow geese are unlikely to lose their new source of food, other animals may face plummeting populations or extinctions if food sources disappear. Until the 1970s, in Yellowstone, grizzly bears fed nearly exclusively at a local dump that then closed: the result was both increased mortality and rapid increases in foraging distances and behaviours.

Finally, and of most concern, food waste subsidies can alter the selective pressures a population faces. Species that become reliant on dumps or fields for food may experience changes in selective pressures, leading to selection for traits necessary to exploit these subsidies, and a loss of genotypic/phenotypic variation from the population. Changes in selective pressure change with the situation, of course. In the case of Yellowstone, the dump closure and loss of food source seemed to have large effects on traits important for sexual attractiveness in males, suggesting potential effects on reproductive success. In the best known (and my favourite) example of the selective effect of human food waste, dogs eventually were domesticated from wolf ancestors. Of course dumps can also relax selective pressures, if they allow individuals in poor condition (juveniles, the elderly) to successfully feed and reproduce.

Though food waste subsidies are clearly important and can have wide ranging effects, it is worth noting that the effect and importance of food subsidies is context-dependent. Studies seem to indicate that effects are greatest when food is low naturally or habitat quality is poor; in high quality systems, food waste may only be used by juveniles or individuals in poor condition. Unfortunately, as humans degrade natural habitats, subsidies are only likely to increase in importance as a food source for species. The extent and effects of human food waste are yet another legacy of the global alterations the human species has made. Unfortunately, like so many of the changes we have made, the issues are complex and transcend political and regional boundaries. Practices in one system or nation are tied to effects in another nation, and this complexity can make it difficult to monitor and measure the effects of subsidies as thoroughly as is necessary. This review from Oro et al. certainly makes a case for why our garbage needs to receive more attention.
One example of the ecosystem wide effects of subsidies: here, fisheries inputs.

Thursday, October 24, 2013

Biodiversity and ecosystem functioning: now with more spatial scales, more functions, and more measures of diversity.

1) Karel Mokany, Hugh M. Burley, and Dean R. Paini. β 2013. Diversity contributes to ecosystem processes more than by simply summing the parts. PNAS. 110:43.
2) Jae R. Pasari, Taal Levi, Erika S. Zavaleta. 2013. Reply to Mokany et al: Comprehensive measures of biodiversity are critical to investigations of ecosystem multifunctionality. PNAS. 110:43.

One of the big topics in ecology in recent years is ecosystem services and functioning. In particular, the question has been how diversity (in its many forms, including species, intraspecific, phylogenetic, or functional) relates to ecosystem function (often, but not always, measured in terms of productivity). Most often, this is framed as a question about how (alpha) diversity at the local scale affects one or two functional responses. Because diversity can be measured at multiple scales (local, regional or landscape, etc), because how we measure diversity is scale-dependent (i.e. alpha, beta, and gamma diversity), and because a functional ecosystem relies on many different services, the obvious next step is to think of biodiversity and ecosystem functioning in a framework that incorporates multiple spatial scales, multiple functions, and multiple measures of diversity.

A new paper in PNAS takes advantage of David Tilman’s long running Cedar Creek biodiversity experiment to explore how multiple functions in a landscape relates to local and regional diversity, and beta-diversity. In Pasari et al. (2013), the authors use five years of data collected for 168 9x9 m plots in the Cedar Creek experiment. These plots contained 1, 2, 4, 8, or 16 perennial plant species, and had measurements for 8 ecosystem functions (invasion resistance, aboveground NPP, belowground biomass, nitrogen retention, insect richness and abundance, and change in soil C and plant N). The authors simulated combinations of these plots to create 50,000 landscapes composed of 24 local plots. Multi-functionality in this case was the (scaled) mean of each of the 8 functions minus their standard deviation, for the landscape. The authors then asked whether the average alpha-diversity of the local plots, the beta-diversity between plots, and the gamma-diversity of the landscape were important predictors of this multi-functionality.

Not surprisingly, when considering the different functional responses individually, the average alpha-diversity of plots in a landscape was the most important determinant. Past research has shown that as local diversity increases, niches may be filled, or functional redundancy may increase, and so ecosystem functioning tends to increase. When considering all 8 ecosystem functions using a single measure though, beta- and gamma-diversity also appeared to be important, although alpha diversity remains the dominant predictor (figure below). It should be noted though that the total explained variance in functionality was always low. Increasing either alpha- or gamma-diversity increased multi-functionality, while the effect of beta-diversity on ecosystem functioning was not linear. “[O]nly experimental landscapes with low β diversity were capable of achieving very high multi-functionality, whereas high β-diverse experimental landscapes more consistently achieved moderate multi-functionality”. One important conclusion suggested by these results, then, is that even at larger scales the most important determinant of ecosystem function is how local communities are assembling, since this determines local diversity.

These results are an important update to the current state of biodiversity ecosystem function research, and add to the large body of research that says that all types of diversity are important insurance for functioning natural systems. It is difficult from this study to get a clear picture of how important each type of diversity is, and when alpha, beta, and gamma diversity might be more or less important. This is in part because despite the upsides of having multiple years of tightly controlled data from the Cedar Creek data, experimental communities artificially combined into landscapes lack realism. For example, beta-diversity captures turnover between communities that may result from spatial dynamics (environmental heterogeneity, dispersal, biotic interactions). All of these characteristics may be very important for functioning at the landscape scale. The response from Mokany et al. expresses some of these concerns, noting that artificially creating landscapes like this may omit important spatial and temporal connections found in real systems.

In addition, and this is a more technical concern about how alpha, beta, and gamma diversity are defined, I’m not clear on what the implications of using all three measures as explanatory variables in the same model may be. Mostly because under the strictest definitions of diversity, these three terms should be dependent on each other – changes in alpha and beta diversity necessarily alter gamma diversity. The authors didn’t use this definition in their study, but to understand the mechanisms that relate diversity and functionality, it may be more informative to take this inter-relationship into account.

Despite any caveats, I think that a role for beta-diversity in ecosystem functioning will be shown in further work, and perhaps its role will prove to be much greater than these initial results show. As we expand our understanding of the scales at which diversity matters, unfortunately this will no doubt highlight the limitations in our conservation focuses even more.

Monday, October 21, 2013

Is ecology really failing at theory?

“Ecology is awash with theory, but everywhere the literature is bereft”. That is Sam Scheiner's provocative start to his editorial about what he sees as a major threat to modern ecology. The crux of his argument is simple – theory is incredibly important, it allows us to understand, to predict, to apply, to generalize. Ecology began as a study rooted in system-specific knowledge or natural history in the early 1900s, and developed into a theory-dominated field in the 1960s, when many great theoreticians came to the forefront of ecology. But today, he fears that theory is dwindling in importance in ecology. To test this, he provides a small survey of ecological and evolutionary journals for comparison (Ecology Letters, Oikos, Ecology, AmNat, Evolution, Journal of Evolutionary Biology), recording papers from each journal as either containing no theory, being ‘theory motivated’, or containing theory (either tests of, development of, or reviews of theory). The results showed that papers in ecological journals on average include theory only 60% of the time, compared to 80% for evolutionary papers. Worse, ecological papers seem to be more likely to develop theory than to test it. Scheiner’s editorial (as the title makes clear) is an indictment of this shortcoming of modern ecology.

Plots made based on data table in Scheiner 2013. Results combined for all evolution and all ecology papers.
The proportion of papers in each category - all categories starting with
 "Theory" refer to theory-containing papers.
Plots made based on data table in Scheiner 2013. Results for papers from individual journals.
The proportion of papers of each type - all categories starting with
 "Theory" refer to theory-containing papers.
This is not the kind of conclusion that I find myself arguing against too often. And I mostly agree with Scheiner: theory is the basis of good science, and ecology has suffered from a lack of theoretical motivation for work, or pseudo-theoretical motivation (e.g. productivity-diversity, intermediate diversity patterns that may lack an explanatory mechanism). But I think the methods and interpretation, and perhaps some lack of recognition of differences between ecological and evolutionary research make the conclusions a little difficult to embrace fully. There are three reasons for this – first, is this brief literature review a good measure of how and why we use theory as ecologists? Second, do counts of papers with or without theory really scale into impact or harm? And third, is it fair to directly compare ecological and evolutionary literature, or are there differences in the scope, motivations, and approaches of these fields?

If we are being truly scientific, this might be a good time to point out that The 95% confidence intervals for the percentage of ecology papers with theory overlap with the confidence intervals for the percentage of evolutionary papers with theory suggesting the difference that is the crux of the paper is not significant. [Thanks to a commenter for pointing out this difference is likely significant]. While significant at the 5% level, the amount of overlap is enough that whether this difference is meaningful is less clear. (I would accept an argument that this is due to small sample sizes though). The results also show that choice of journal makes a big difference in terms of the kinds of paper found within – Ecology Letters and AmNat had more theoretical papers or theory motivated papers, while Oikos had more tests of theory and Ecology had more case studies. This sort of unspoken division of labour between journals means that the amount of theory varies greatly. And most ecologists recognize this - if I write a theory paper, it will be undoubtedly targeted to a journal that commonly publishes theory papers. So to more fully represent ecology, a wider variety of journals and more papers would be helpful. Still, Scheiner's counterargument would likely be that even non-theory papers (case studies, etc) should include more theory.

It may be that the proportion of papers that include theory is not a good measure of theory’s importance or inclusion in ecology in general. For example, Scheiner states, “All observations presuppose a theoretical context...the simple act of counting individuals and assessing species diversity relies on the concepts of ‘individual’ and ‘species,’ both of which are complex ideas”. While absolutely true, does this suggest that any paper with a survey of species’ distributions needs to reference theory related to species’ concepts? What is the difference between acknowledging theory used via a citation and more involved discussion of theory? In neither of these cases is the paper “bereft” of theory, but it is not clear from the methods how this difference was dealt with. As well, I think that ecological literature contains far more papers about applied topics, natural history, and system-specific reports than evolutionary biology. Applied literature is an important output of ecology, and as Scheiner states, builds undeniably on years of theoretical background. But on the other hand, a paper about the efficacy of existing reserves in protecting diversity using gap analysis is both important and may not have a clear role for a theoretical section (but will no doubt cite some theoretical and methodological studies). Does this make it somehow of less value to ecology than a paper explicitly testing theory? In addition, case reports and data *are* a necessary part of the theoretical process, since they provide the raw observations on which to build or refine theory. In many ways, Scheiner's editorial is a continuation of the ongoing tension between theory and empiricism that ecology has always faced.

The point I did agree strongly with is that ecology is prone to missing the step between theory development and data collection, i.e. theory testing. Far too few papers test existing theories before the theoreticians have moved on to some new theory. The balance between data collection, theory development, and theory testing is probably more important than the absolute number of papers devoted to one or the other.

Scheiner’s conclusion, though, is eloquent and easy to support, no matter how you feel about his other conclusions: “My challenge to you is to examine the ecological literature with a critical eye towards theory engagement, especially if you are a grant or manuscript reviewer. Be sure to be explicit about the theoretical underpinnings of your study in your next paper…Strengthening the ecological literature by engaging with theory depends on you.”

Thursday, October 10, 2013

Science shutdown

As the United States enters the 10th day of its government shutdown, the impacts on science and scientific researchers are becoming very apparent. Ignoring the political mess, the fact is that the shutdown is having devastating effects for science, ranging from small to very large scales.

Some of the largest obvious effects relate to the cessation of highly necessary services. For example, the majority of employees the Centers for Disease Control and Prevention were furloughed. Days later experts on foodborne illness were called back to work, because, surprise, they are essential in cases of E. coli outbreaks. Similarly, nearly all of the Environmental Protection Agency’s employees were furloughed, which means that air and water quality monitoring is furloughed too. According to one employee: "No one is going to be out inspecting water discharges, or wet lands. Nobody is going to be out inspecting waste water treatment plants, drinking water treatment plants, or landfills – nothing". Most of the employees whose work relates to climate science research and related environmental controls at the EPA, NASA, and the National Oceanic and Atmospheric Administration (NOAA) are also no longer at work.

Non-government scientists of every form are also being affected in multiple ways. The overwhelming issue is that the National Science Foundation (NSF) and National Institute of Health (NIH), have been all but closed. (For a great illustration, flip through the messages currently on US gov't science webpages, here). Technically, these furloughed employees are prohibited from replying to phone calls or answering emails from their work email. From one furlough letter: “Due to legal requirements, working in any way during a period of furlough is grounds for disciplinary action, up to and including termination of employment”. If your supervisor or collaborator is a federal scientist, this is a very direct impact of the furlough. But more generally and most importantly, these agencies (particularly the NSF for EEB academics) is the primary funding source for many scientists and institutes, and that means that until the shutdown is over, there will be no new payments or grants awarded.

(From, regarding new awards)
"Proposal Preparation & Submission
No new funding opportunities (program descriptions, announcements or solicitations) will be issued.
FastLane proposal preparation and submission will be unavailable."
(existing awards)
"Performance of Work
Awardees may continue performance under their NSF awards during the shutdown, to the extent funds are available, and the term of the grant or cooperative agreement has not expired. Any expenses must be allowable and in accordance with the Office of Management and Budget (OMB) cost circulars. During the shutdown, NSF cannot authorize costs exceeding available award amounts or obligate additional funds to cover such costs.
No payments will be made during the shutdown."

If your grant is up for review or you are applying for a new grant (it was DDIGs season), then you are out of luck for the moment (FastLane, necessary for submitting grants, is not available), and there undoubtedly will be delays in processing once the shutdown does end.

Even if you have money to spend, limitations may arise from the fact that permits for research activities can’t be filled, and National Parks, National Wildlife Reserves, National Forests are all closed, so planned field activities may be limited. For example, Long-term Ecological Reseach projects (LTERs), which by definition require continuity in sampling, some projects are now inaccessible. Researchers in charge of long-term studies of rodent populations in Sevilleta National Wildlife Refuge, New Mexico, found the gates locked and the combinations changed, making monitoring stations impossible to reach. If you were planning a field season in Antarctica, you are especially out of luck, since the field season has been cancelled altogether. If you planned to use the collections at a national museum (e.g. the Smithsonian), or use government websites and federally funded data repositories, you can’t. I’ve received several mass emails from researchers attempting to locate other sources of necessary data, since their government source is gone. Even if you aren’t a researcher in the US, you might notice the effect of the shutdown because the high profile open-access journal from the Public Library of Science, PLOS ONE, is also at a standstill. And if the keynote speaker at your conference is a US government employee, you’ll notice their absence, since they are not allowed to attend conferences

Given the global nature of science, these effects are not isolated to only just a single country in the world – scientists everywhere share US websites and institutions, museum collections, collaborate with US-located researchers, government or otherwise, do fieldwork in US national parks, or rely on the continuity of data from long-term research projects. The impacts of this shutdown are broad and deep, and the most important question is how long will it take for science and scientists to recover?

*If anyone has examples of how this shutdown is affecting their research, please leave a comment!