Great article by Scientific American about reading scientific papers!
After a long respite on this blog due to limited access to a computer while my laptop being fixed, I’m happy to make the belayed announcement that I’ll be joining the Population Biology graduate group as a first-year PhD student at UC Davis in Fall 2017!
My primary advisor will be Jennifer Gremer, a new plant ecologist in the Evolution and Ecology department. I’ve been working closely with her during my time as a Research Assistant in Johanna Schmitt’s lab, the position I currently hold, because she is co-leading a project that takes up the majority of my responsibilities as a tech.
I’m even thinking about doing some of my own PhD research on the project I’ve been working on for the past year – we are studying life history variation and local adaptation in the native California wildflower Streptanthus tortuosus in the context of its potential ability to adapt to climate change.
S. tortuosus is an ideal study organism for these questions because it displays a wide range of morphologies and adaptations across its range, which encompasses most of California and elevations from about 500-12,000 feet. It’s also classified as a biennial or perennial in many field guides, but we’ve seen it display an annual life history as well. In fact, we think we’ve found a trend in life history: increasing perenniality with increasing elevation. It also responds differently to vernalization treatments, flowers at different times, and grows at different rates in a common garden, providing some evidence for genetic differences in these traits.
I am especially interested in finding out whether this species is locally adapted to snowmelt timing on mountainsides. I have tentative plans to explore this question further this summer at Lassen Volcanic National Park, where I have observed plants displaying very different phenologies dependent on snowmelt timing across very short physical distances. These plants are bad at selfing, which means they rely on outcrossing by pollinators to reproduce, so I also want to study the landscape genetics of the species at Lassen – are there different “genetic cohorts” reproducing with each other every year because they consistently have open flowers at the same time as a consequence of when they emerge from the snow?
Hopefully, I can equip myself with the conceptual, statistical, and methodological tools to begin answering these questions during my first year of classwork as a PhD student. Whether or not this ends up being my dissertation project, I’m learning a lot about plants, genetics, and conducting long-term independent research in the meantime!
This paper comes from an open-access journal, Ecosphere! Woohoo! You can read the whole paper yourself for free here: Effects of climate change on phenologies and distributions of bumble bees and the plants they visit I encourage you to read both the scientific paper and my summary to get the most complete picture of the story – this paper is more comprehensible than most!
Shameless plug for native bees:
Honey bees get a lot of attention from the media because they help to pollinate the food we eat, but in terms of their conservation, agriculture is really the only reason we would focus on protecting honey bees. They are actually a non-native species from Europe, are not in any danger of dying out as a species, and in the wild, they often outcompete native bee species for floral resources, potentially causing harm to ecosystems overall. The following paper is about native or naturalized bumblebee species and describes one of the problems native bees are facing in nature due to climate change. Read on to learn more!
In this paper, the authors are focusing on bee and plant phenology, which is the timing of life events like birth, death, and peak activity, and in plants specifically, events like sprouting, budding, flowering, fruiting, and senescing (pre-programmed partial or complete death of plant parts, like when oak trees shed their leaves in the fall). Bees and plants interact with each other in a mutualistic relationship, meaning they help each other out with functions necessary to survival. This occurs primarily through pollination, whereby bees collect nectar and pollen to eat and feed their young, and the plants receive fertilization so they can produce successful offspring. But this mutualism can only occur when the bees and plants are operating on the same timeline – bees need to be buzzing around searching for food at the right time of the season, namely, when flowers are open on plants, for pollination to proceed. With changes in climate, bees and plants may need to shift their phenologies to coincide with optimal weather conditions – but a big question in ecology right now is, will they shift their phenologies in the same way so that they stay matched up with each other? This potential phenological mismatch between bees and plants, or asynchrony, is what Pyke and his colleagues explore in this paper.
- Organisms are expected to respond to changing climate by shifting geographical ranges and phenology toward remaining in their compatible climate zones
- Such changes may result in spatial or temporal mismatches between interacting species (asynchrony)
- This study examines mismatches arising from climate-induced shifts in plants and their pollinators
- Surveyed bumble bees and the plants they visit in 1974 and 2007 at the Rocky Mountain Biological Laboratory in Colorado (33 years)
- Tested hypotheses arising from observed climate change
The Rocky Mountain Biological Laboratory (RMBL) has been providing scientists with a natural outdoor laboratory since 1928. Many famous studies have been conducted there, and an author on the paper, David Inouye (below), has spent summers performing experiments on pollination ecology at RMBL since 1971.
RMBL is a great place to study shifts in phenology due to climate change, because changes in temperature occur very rapidly with changes in altitude on the slopes of mountains. In the 33-year intervening period between their two study years, for example, monthly spring and summer temperatures have increased 2 degrees C on average, which means that for plants and bees to experience the same temperature conditions they had in 1974, they must move 317 meters up the mountain by 2007.
- H1: Species distributions have shifted upwards by about 317 m to match the change in temperature with elevation
- H2: Phenologies have shifted earlier in the season, but not identically, resulting in asynchrony (mismatching)
- H3: Bumble bee abundance was lower in 2007 than in 1974 (due to asynchrony)
- Study encompassed an elevation range of 1000 m and spatial range of 16 km
- 47 study sites – dominated by grasses and herbaceous plants
- Surveyed every 8 days (1974) or 6 days (2007)
- Transects or “circle sites” (covering circular areas on roadsides)
- ID’d bumble bees observed and flowers visited
- 12 perennial plant species ID’d as important to bumble bees (represented 74.5% of visits)
- 8 bumblebee species (represented 97% of bumble bees observed)
Did bees shift up?
- H1A: Bees shifted up but not necessarily 317 m
Did plants shift up?
- H1B: Plant species did not show significant change in upwards distribution (expect one species)
Did bee phenology shift earlier?
- H2A: Phenological differences were partially consistent with hypotheses
- Workers shifted in peak recording rate ~17 days earlier in transect sites
Did flowering phenology shift earlier?
- H2B: Flowering phenology was significantly earlier in 2007 compared with 1974
Was there asynchrony (mismatching) between bees and plants?
- H2C: Found expected reduction in synchrony between bees & plants
- However, the authors assume that the bees and plants were synchronous in the first place in 1974
Was there lower bee abundance in 2007?
- H3: Found lower bee abundance in 2007 compared with 1974
Summary of results
- Shifts towards higher elevations for most bumble bee species, but not for most plant species
- Phenology shifted earlier for plants but not bees
- Bees and plants were mismatched in 2007
- Bee abundance was lower in 2007
We discussed this paper in a seminar on the phenological consequences of climate change that I’m auditing this quarter at UC Davis. Here are some of the points our discussion centered around:
- Only 2 years of data – are their conclusions justified?
- Why are upward shifts in bees inconsistent with the expectation (317 m)?
- Their surveys in 2007 ended before bumble bee workers declined, making it difficult to accurately estimate dates for peak recording rates – how might this affect their results?
- Can’t draw a causal link between reduced synchrony & reduced bee abundance, but how convinced are we that they’re related?
- Could not support the hypothesis that phenologies coincided seasonally in 1974 but not 2007 – do we think this reduces the power of their results?
- How can we better incorporate both spatial and temporal changes due to climate change when considering mismatch, especially for mutualisms occurring on steep environmental gradients?
Particularly if you read the paper in full, I encourage you to think carefully about these potential issues with the paper. It took me six years of reading scientific papers to feel comfortable with questioning methods, statistics, results, and claims that authors make, but learning to approach science with a healthy degree of skepticism is an important part of the your development as a critical thinker and the scientific process as a whole and. Always remember that correlation does not imply causation, and that each paper is only a small part of the bigger picture that science will eventually paint on particular issues as evidence builds over time. Certain parts will inevitably be wrong, and it’s our job as researchers to figure out which bits are wrong, and which bits are right, so we can eventually discover the mechanisms and processes that drive natural phenomena over the long term.
Regardless of the potential problems with the paper, I found it most interesting because while phenological mismatch is a hot topic to study in ecology right now, this is the first paper I’ve seen that studies several bumble bee species and several plant species at once, or the whole plant-pollinator community occurring in the study area. It is also the only paper I’ve come across that considers both the temporal and spatial components of mismatch: it’s easier to quantify phenology in ecological studies, so the temporal component has been overstudied in comparison to the spatial component, but both are equally important – think about it, if the bees and plants aren’t in the same physical location, it will be harder for pollination to proceed normally.
Why should you care?
Mismatch between all different kinds of interacting species around the world can have potentially devastating consequences for ecosystem functioning, and in turn, the provisioning of ecosystem services to humans. Nature consists of highly interconnected systems where organisms interact both directly and indirectly with each other in tandem: take the famous example of wolves having cascading effects on the ecosystems in Yellowstone National Park. When wolves were reintroduced, deer began avoiding parts of the park, which allowed plants to grow back. Willow and aspen trees sprang up, and with them came more berries and insects, attracting more bird species to the park. Beavers came back and created dams with wood from the trees, and the dams attracted otters, muskrats, and other reptiles. Wolves also killed coyotes, so the mice and rabbit population grew, attracting weasels, red foxes, badgers, and hawks. The wolves even indirectly changed the rivers — with increased plant growth now that deer were not munching everything in sight, the vegetation decreased erosion and stabilized river banks. Channels narrowed, more pools formed, and the rivers stayed more fixed in their course. In this ecosystem, everything is functioning properly and imposing balance on its individual components. But what if the timing was all off? What if the deer were giving birth before the plants started to grow in the spring time and the babies didn’t have enough food to survive? What if the berries didn’t grow on the trees at the same time as birds were foraging for food? What if the deer moved to a climate they preferred because the climate was warming, but the wolves didn’t move as quickly and the deer started to eat all the vegetation again because their populations weren’t being held in check by predators? These are the kinds of questions ecologists are asking about phenological mismatch due to climate change, and finding the answers will be of paramount importance in understanding how to conserve nature and protect intact ecosystems.
Pyke, G.H. et al. 2016. “Effects of climate change on phenologies and distributions of bumble bees and the plants they visit.” Ecosphere 7(3). (Published under a Creative Commons license).
Read the abstract of this paper yourself here: Conflicting selection on the timing of germination in a natural population of Arabidopsis thaliana
In this paper, the authors explore how seeds sprouting early versus sprouting late in the season can be good or bad for the plant’s overall fitness (its ability to survive and reproduce) depending on the effect that sprouting time has on the plant’s fitness at different stages in its life cycle.
To understand what they’re studying, it is important to know what “conflicting selection” is. First, plain old selection is the process by which more adapted individuals (i.e., those with better fitness) survive and pass on their genetic information to the next generation. Many many instances of natural selection over time cause evolution to occur.
Conflicting selection is a slightly more complicated version of regular selection. Jose Gomez (2004) describes a basic example in which producing bigger acorns can be advantageous for an oak plant to make because they contain more nutrients for the sprouting plant to use, but they can also be disadvantageous because animals that eat acorns, like squirrels, prefer to collect larger acorns. In cases like this, you might expect that because the smallest acorns die without enough nutrients and the largest acorns are eaten by squirrels, the only acorns left that actually survive long enough to make more oak trees are the medium-sized ones. That’s conflicting selection at work!
In Akiyama and Agren’s paper, the researchers study conflicting selection on the timing of germination, or sprouting, of a small flowering plant in the mustard family called Arabidopsis thaliana.
In order for plants to contribute genetic material to the next generation, they need to survive, and they need to reproduce. In this study, plants that sprouted early experienced lower survival as seedlings, but if they did survive to become adult plants, the adults had better survival and produced more offspring. On the other hand, plants that sprouted later experienced higher survival as seedlings, but out of the survivors, the adults had lower survival and produced fewer offspring than the plants that sprouted early.
In a situation like this where there are complicated pros and cons associated with sprouting early or late, which plants win the fitness game?
To find out, the authors measured overall fitness of the plants that sprouted at different times and found that the advantages of sprouting early outweighed the disadvantages: plants that sprouted earlier had higher overall fitness.
A word of caution from the authors: this study only took place over one year, which is not enough time to generalize these results as a consistently winning strategy for this population of plants. For example, during the year of this study, the fall and winter were fairly cool. This means that the plants that sprouted earlier may have had two advantages related to that year’s weather: 1) even though the early-sprouting seedlings were small and delicate in the fall, they may have survived drought conditions better than they usually would at that size because the fall was cooler than normal, and 2) because the early-sprouting plants had more time to grow big before winter came, they may have had an advantage over the smaller, later-sprouting plants because winter was cold and larger plants have a better chance of surviving the winter.
This is why it’s important to replicate studies – in this case, repeat it with different plants, in different places, over multiple years, etc. – before assuming all plants of the same species or even the same population employ the same early-sprouting strategy all the time. If the fall and winter had been warmer, the researchers may have found completely different results!
Why should you care?
This paper illustrates an important point about the complexity of nature – often, what’s really going on isn’t what seems initially obvious, or even what seems obvious after the second or third or fiftieth time an experiment has been done on it! Science is a slow process, and each paper like this one is a small brick added to a wall of knowledge that will always have gaps in it. Only with much rigorous science can we make the gaps smaller and smaller and the wall sturdier over time.
Akiyama, R. & Agren, J. 2013. Conflicting selection on the timing of germination in a natural population of Arabidopsis thaliana. Journal of Evolutionary Biology 27:193-199.
Gomez, Jose M. 2004. Bigger is not always better: Conflicting selective pressures on seed size in Quercus ilex. Evolution 58(1):71-80.
The latitudinal diversity gradient describes the phenomenon in which the diversity of species inhabiting biomes is higher near the equator and lower near the poles. Read on to learn more about existing hypotheses that attempt to explain why this gradient exists, and how scientists may benefit from considering more than one hypothesis at a time when approaching ecological questions of this scale and magnitude.
A standardized, multipronged approach to studying the Latitudinal Diversity Gradient
One of the most fundamental objectives of the field of ecology is to determine how species are assembled in space and time and why they are assembled in such ways, or in other words, whether and why there are patterns in species composition and diversity over varying spatial scales (Witman & Roy 2009). Globally relevant patterns are often difficult to study because of their inherently – indeed, literally – all-encompassing and therefore highly complex nature. However, global patterns can facilitate the elucidation of fundamental ecological processes because they promise generality.
One such pattern is the decline of biodiversity with low latitudes; a phenomenon termed the “latitudinal diversity gradient” (LDG) (Connolly 2009). This gradient, which has been observed with varying intensity throughout Earth’s history, is hypothesized to extend back through the Mesozoic and into the Paleozoic (Jablonski et al. 2006, Jansson et al. 2013, Crane & Lidgard 1989). First observed by Alexander von Humboldt during his travels to South America in the mid-18th century, the LDG has become one of the biggest unresolved challenges of biogeography and macroecology, for there remains much debate and controversy over which of the many hypotheses – or which combination of said hypotheses – best explains the LDG.
There has been a recent push in the endeavor to explain global patterns of diversity, partly due to the “increasingly urgent need to prioritize regions for conservation on a global scale” (Connolly 2009). As humans increasingly alter the Earth, conservationists grapple with the issue of how to conserve a high level of global diversity. Learning as much as possible about how and why the LDG arose could be key to informing conservation and management of biodiversity in the future.
Over the past several decades, a body of emerging evidence has suggested that many very different taxa exhibit similar species richness gradients; namely, the LDG (Connolly 2005). However, is the LDG a generalizable pattern of species diversity? Is the LDG even accurately designated as a gradient? Here, I explore these and similar questions, focusing not on whether the LDG exists, but whether scientists are utilizing the appropriate methodology and language to most effectively ascertain the truth about patterns of species richness observed in nature.
As I explore the above queries, I couch my analysis within a hypothetical situation in which the LDG is assumed to exist, and the goal of macroecology and other sciences regarding the LDG is to determine which combination of hypotheses explains the LDG best. Put aside the uncertainty and controversy over the existence of the LDG for the next fifteen minutes or so while you read. I argue that we enact environmental policy and move forward with conservation plans now, using the knowledge we already have about species diversity patterns, rather than delay action until we have more information and/or a confirmed scientific consensus over the existence and generality of the LDG, because global biodiversity is under threat now.
Caveats of studying the LDG
Studying global patterns across large temporal and spatial scales is a challenging and often daunting task. There are more interactions and variables to consider at large scales, at which the computing and processing abilities of computers, and indeed, our brains, is limited. In his 1989 Robert MacArthur Awards Lecture, Simon Levin stated, “the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology” (Levin 1989). It is this very problem with which scientists grapple when studying global patterns such as the LDG. However, as Levin alludes, solving the problem of scale when tackling a given scientific question can yield immensely valuable insights into the way our world works. The key to prediction and understanding, and the essence of science, lies in the elucidation of the mechanisms and processes that underlie and produce patterns (Levin 1989), and the concepts of scale and pattern are indelibly intertwined (Hutchinson 1953).
When we probe into a scientific inquiry, we observe the environment on a limited range of scales. This means that our perception of events and therefore our science provides us with only a “low-dimensional slice through a high-dimensional cake” (Levin 1989). When we scale up in study scope, “we must understand how information is transferred from fine scales to broad scales, and vice versa” (Levin 1989). Presently, ecologists do not fully understand why and how patterns of diversity exist on local or regional scales; therefore, we are necessarily limited by our lack of understanding at smaller scales when we attempt to scale up to study global patterns of diversity. Large-scale studies of global biodiversity also fall prey to the trade-offs between studying ecological patterns at small or at large scales. At small scales, we are able to pay closer attention to detail, but stochasticity plays a larger role and the patterns and interactions being studied are more unpredictable. At large scales, which display more regular statistical behavior, we trade off the loss of detail for the gain of predictability and generalizability (Levin 1989).
These considerations lead to another important question: is the LDG general? If the LDG holds true for the majority of Earth’s species, then yes. However, what is the magnitude at which a clade of organisms must follow the LDG in order for it to be considered displaying the LDG, or cited as evidence for the LDG’s existence? What proportion of Earth’s biodiversity must follow the LDG for it to be considered a global phenomenon? One of the main assumptions of the LDG is that Earth’s biodiversity is completely described. Scientists know this is certainly not the case. In fact, today, centuries after explorers and naturalists like Humboldt and Darwin first observed incredible biodiversity in the tropics, we do not even know within an order of magnitude the full extent of biodiversity on Earth: current estimates range from 3 to 30 million species (Gullan & Cranston 2010). Although our knowledge regarding global biodiversity is not complete, we can still study phenomena like the LDG using inference and the knowledge we currently have. This being said, scientists should also think carefully about caveats surrounding the LDG and studying global patterns, including the assumptions underlying the LDG and the incompleteness of our understanding of species diversity, distributions, and interactions at smaller scales.
In light of the tradeoff between studying science at large versus small scales, Levin reasons that there is no “correct” scale on which to describe populations or ecosystems; instead, when studying a particular scale, one should recognize that change is taking place on many scales simultaneously and consider that interactions occur across scalar boundaries (Steele 1978, Levin 1989, Wiens 1989). Consider this: organisms respond to their environment at an individual level, meaning that what we call a community or ecosystem is really just an “arbitrary subdivision of a continuous gradation of local species assemblages” (Whittaker 1975, Levin 1989). Globally, communities and ecosystems are not well-integrated units that move and evolve en masse; rather, they are assemblages of organisms responding individually to spatial and temporal variation. Thus, although a pattern like the LDG is observed globally, it arose through the individualistic ecological and evolutionary responses of much smaller constituents of the world’s biodiversity, rather than through evolution at the community or ecosystem level (Levin 1989). Many hypotheses seeking to elucidate the mechanisms underlying the LDG (see below for an overview of these hypotheses) refer to the evolution of entire clades of organisms; however, it is key to consider that the accuracy of analyses is reduced when considering evolutionary processes at higher taxonomic levels.
Once mechanisms underlying a pattern have been described and determined, the key to understanding the pattern lies in separating the mechanisms which theoretically could give rise to the observed pattern from the mechanisms which actually did give rise to the observed pattern. As Levin wisely points out, “there are many roads to Rome” (Levin 1989). Below I describe the various hypotheses explaining how the LDG arose. While each mechanism is supported by evidence that it contributed to the existence of the LDG, it is important to recognize that theory alone can only ever create a catalogue of possible mechanisms. Without performing experiments, or without support for highly risky predictions associated with one or more of the proposed hypotheses explaining the LDG, distinguishing among said hypotheses can be done only to a certain extent.
Because there are so many factors to consider when studying the LDG, there are also many different ways in which people can study it, with emphasis on varying factors depending on a person’s particular perceptions of the world, biases, and knowledge base. One of these factors is the concept of an appropriate resolution at which to study the LDG. For example, general circulation models were once performed in 10-degree grids, and current models allow for much higher resolution as the grids become smaller and smaller, similar to a picture including more and more pixels. This concept of resolution can also be applied to studying ecological concepts: as we scale up to include larger temporal and spatial scales, our resolution necessarily becomes coarser. The finer the resolution at which we study the world, the more accurate an interpretation of the world we are able to obtain. In many studies of the LDG, the world is parsed into latitudinal bands into which information on species diversity is separated. Presumably, the more finely one parses latitude while studying the LDG, the more accurately one interprets observed patterns of global species diversity, albeit in a necessarily asymptotic fashion. I explore this concept further below by performing a literature review to determine how finely studies of the LDG parse the globe into latitudinal bands. Ultimately, I ask: at what minimum resolution of observation is the LDG accurately termed a “gradient?”
One last caveat of studies of the LDG involves the dangers of correlation: most studies seeking to explain the LDG utilize simple correlations (Connolly 2009). Perhaps it has been repeated so often that it is now met with some impatience, but I will repeat it again because no matter how many times it is said, its relevance will not dwindle: “correlation does not imply causation.” Hypotheses pertaining to the LDG are intrinsically correlative. Furthermore, there is a cautionary tale amongst statisticians that when performing studies with a very large sample size n or very large number of observations i, the correlation in question (i.e. the relationship between latitude and species diversity) becomes increasingly likely to become significant as an artifact of that large amount of data. For example, the more people sampled from a given population, the more significant a correlation will become between people who have mustaches and people who smoke cigars, not because these two events are dependent upon each other in any way, but because the calculation of the significance level indirectly depends on the sample size. It is important to be cognizant of these and other caveats while studying the LDG because the elucidation of the mechanisms and processes underlying the LDG has the potential to shed much light on important scientific questions and inform global conservation and management of biodiversity in the future.
Hypotheses explaining the LDG
Exactly what proportion of Earth’s identified species display patterns matching the LDG? Although studies have been biased towards well-studied, larger-bodied organisms such as vertebrates and higher plants, and the majority of studies originated from the Americas, overall evidence suggests that most clades generally follow the LDG (Hillebrand 2004). Hillebrand (2004) performed a meta-analysis of nearly 600 observations of the LDG in the literature and found strong evidence for the existence of a generally applicable LDG. Notable exceptions include macroalgae (Kerswell 2006), fish parasites (Rohde 1998), seabirds (Proches 2001), and ichneumonid wasps (Janzen 1981). Major hypotheses regarding the LDG can be categorized into 1) spatial/area hypotheses 2) historical/evolutionary hypotheses, or 3) biotic hypotheses. Below, I provide a brief overview of these hypotheses. This overview is necessarily incomplete due to the sheer number of hypothesis in the literature endeavoring to explain the LDG, but I attempt to touch upon the major perspectives regarding the LDG, both currently and throughout history, and provide an accurate representation of all types of hypotheses and the level of support those hypotheses have received in the ecological community.
Spatial/area hypotheses include the mid-domain effect (MDE), the geographical area hypothesis (GAH), the species-energy hypothesis (SEH), the climate harshness hypothesis (CHH), and the climate stability hypothesis (CSH).
The mid-domain effect (MDE) was first described by Colwell and Hurtt (1994) and Willig and Lyons (1998), who used computer simulations to show that when species ranges are randomly placed in a domain (Earth) with boundaries at the poles, species ranges tend to overlap at the center of the domain, creating an MDE of low-latitude peak in species richness. Mid-domain models have been suggested to contribute to the LDG; however, these models do not include any ecological or environmental influences on species richness; therefore, they have been argued to be null models (Colwell et al. 2004, 2005). This means that if latitudinal gradients of species richness were determined by the MDE, the LDG would be indistinguishable from patterns produced by the random placement of observed species ranges (Colwell & Lees 2000). Some tests have found mid-domain models to have high predictive power, especially on large spatial scales (Jetz & Rahbek 2001, Dunn et al. 2007), while others claim it has low predictive power (Bokma & Monkkonen 2001, Kerr et al. 2006).
Connolly (2009) points out that the MDE assumes that the frequency distribution of range size displayed by a particular clade depends on the domain’s size and shape but not on characteristics of the clade. This approach, Connolly argues, ignores the fact that “rates of origination, colonization, or local extinction may differ among clades in the absence of geographical gradients of those rates,” meaning that “frequency distributions of ranges sizes may well differ among taxa, independent of any effects of environmental gradients” (2009).
Mid-domain models are the only ones that use latitude as a geometric constraint imposed on species’ ranges. All other models attempt to elucidate the relationship between latitude and one or more factor co-varying with latitude. Connolly believes this is a flaw in our approach to studying biogeographical patterns, because regression-based approaches can only assess a model’s predictive power, not its explanatory power (2009). Because analyses of species richness like those studying the LDG seek to explain how much a certain environmental factor has influenced species richness patterns over time and space, Connolly argues that the types of methodologies used to study macroecological patterns should be shifted from those better able to predict to those better able to explain (2009).
The geographical area hypothesis (GAH) suggests that the LDG arose through the ability of the tropics to contain more species because of their large contiguous geographic extent (Terborgh 1973). As the largest biome, the tropics can support species with larger range sizes, and larger range sizes impart lower extinction rates and increased speciation rates upon tropical species, leading to increased diversity in the tropics (Rosenzweig 2003). However, critics point out that successive biomes north of the tropics are similar in area, and should therefore contain similar levels of species richness according to the GAH, but they do not (Gaston & Blackburn 2000). Others argue that the terrestrial tropics are not the largest biome, and that it is erroneous to define the tropics as a single biome (Rohde 1997, Hawkins & Porter 2001). Additionally, area-dependent hypotheses such as the GAH are generally better able to predict species richness patterns for species with smaller ranges than those with larger ranges (Mora & Robertson 2005).
The species-energy hypothesis (SEH) (also called the “energy-richness hypothesis” or the “more individuals hypothesis”), posited in the mid-20th century by Hutchinson (1959) and later elaborated by Brown (1981) and Wright (1983), postulates that increased energy availability in the tropics boosts net primary productivity, allowing more individuals to exist, and therefore more species to evolve, in the tropics. Critics question the validity of the statement that increased productivity leads to increased numbers of individuals which in turn leads to increased numbers of species (Cardillo et al. 2005). Currie and colleagues (2004) tested the SEH and found that the relationship between productivity and the density of individuals at large spatial scales is weak. They further concluded that extant evidence is inconsistent with the mechanism proposed for the SEH.
The climate harshness hypothesis (CHH) states that the LDG exists because more species can physiologically tolerate the wetter, warmer environmental conditions of the tropics. Cardillo et al. (2005) and Currie et al. (2004) criticize this hypothesis by providing evidence that species are not present within every area whose climate they are able to tolerate.
The climate stability hypothesis (CSH) suggests that areas with stable environments like the tropics, which do not have as variable conditions as higher-latitude areas like temperate regions, allow species to specialize into narrow niches, decreasing resource overlap between species and therefore increasing speciation (Kaustuv et al. 1999, Lima-Ribeiro et al. 2009). Critics point out that climate stability does not always lead to higher species diversity, and that high species diversity exists in non-stable climates (Brown & Lomolino 1998).
Hypotheses invoking historical or evolutionary processes to explain the LDG include the historical perturbation hypothesis (HPH), the diversification rate hypothesis (DRH), the evolutionary time hypothesis (ETH), and the out of the tropics model (OTM).
The historical perturbation hypothesis argues that historical perturbations such as glaciation disproportionately affect global species richness levels, and that increased historical perturbations have dampened species richness levels at higher latitudes (Brown & Lomolino 1998, Gaston & Blackburn 2000). Further, the HPH suggests that temperate regions are not yet saturated with species due to moderate levels of disturbance over geologic time; therefore, diversity in temperate regions will continue to increase until it reaches an equilibrium number of species (Clarke & Crame 2003).
The diversification rate hypothesis proposes that higher ambient temperatures lead to shorter generation times, higher mutation rates, and faster physiological processes which contribute to higher diversification rates in the tropics (Rohde 1992, Currie et al. 2004, Cardillo et al. 2005). More research is needed to determine whether speciation rates are indeed higher in the tropics.
The ETH advocates that the long period of time under which the tropics have existed in a stable state has contributed to the generation and maintenance of the LDG, in combination with increased evolutionary rates in the tropics via mechanisms similar to those proposed by the DRH. This hypothesis accepts that other factors may contribute to the LDG, and assumes that the environment does not saturate as richness increases (it is a non-equilibrium hypothesis). Several studies have found evidence supporting this hypothesis (Allen et al. 2006, Wright et al. 2006, Jansson et al. 2013).
The OTM states that many taxa originate in the tropics and expand towards the poles while still remaining present in the tropics. Jablonski et al. (2006) found that a global analysis of marine bivalves supports this model and emphasizes a key implication of the OTM: if the tropics experience reduced biodiversity due to disturbance or human impacts, then after an ensuing time-lag, global diversity will also experience a similar reduction in biodiversity.
Proponents of biotic hypotheses argue that the increased intensity of biotic interactions like competition, predation, and parasitism at low latitudes caused the formation of the LDG (Pianka 1966). However, these hypotheses do not provide evidence that biotic interactions increase towards the equator, and additionally fail to explain why the biotic interactions cited as contributing to the LDG would increase towards the equator. Recent studies have found that changes in the intensity of biotic interactions with latitude are inconsistent (Lambers et al. 2002, Hillebrand 2004).
Reviews/multiple contributing mechanisms:
While some ecologists seek one primary mechanism driving the LDG, a growing number of ecologists argue that several mechanisms contribute to the LDG (Gaston & Blackburn 2000, Willig et al. 2003, Rahbek et al. 2007, Hawkins et al. 2003, Colwell & Lees 2000). Several recent studies (published in the past decade) have also performed reviews of the literature to determine whether one or more the above hypotheses are supported by data on observed species richness patterns.
For example, Currie and colleagues (2004) attempted to derive and test the predictions of the SEH, the CHH, the DRH, and biotic hypotheses. Their study yielded little support for the SEH, mixed results for the CHH, and neither support for nor evidence against the DRH and biotic hypotheses due to a lack of evidence available to test the predictions of these hypotheses. Currie et al. (2004) emphasize the need for more research on the LDG in general and express a hope for the ability of science to make more conclusive statements about the DRH and biotic hypotheses as the field of molecular-based evolutionary biology advances.
Jansson et al. (2013) performed a review of over 100 phylogenetic studies and mapped the latitudinal ranges of all taxa in order to test the relative importance of the OTM, a variation of the ETH called the tropical conservatism hypothesis (TCH), and the DRH. Like the OTM, the TCH argues that most clades originate in the tropics, but unlike the OTM, the TCH maintains that transitions of lineages from tropical to temperate latitudes are rare, resulting in increased species diversity in the tropics compared to higher latitudes (Jansson et al. 2013). Jansson and colleagues (2013) found that while most clades originated in the tropics and peaked in the zone of origin, transitions between latitudinal zones occurred frequently – at 16-22% of nodes – with the most common transitions occurring between tropical and temperate zones. Their results supported the ETH and the OTM, but contradicted the TCH and the DRH. Jansson et al. (2013) also suggest that the OTM is actually a special case of the ETH.
In Hillebrand’s review (2004), the LDG was found to be ubiquitous but varying in strength by scale, organism body mass, and trophic level. The LDG was weaker in freshwater habitats and also differed significantly between continents and habitat types. Fine and Ree (2006) found that a time-integrated area of biomes is positively correlated with species richness. They use this and other evidence to argue that area and time determine species richness.
While data evidencing the LDG is necessarily and sometimes woefully incomplete, there is enough evidence to support the statement that the LDG exists across geologic time, space, and the majority of the taxa we have documented to date. After performing a literature review of 25 studies of the past century supporting, contradicting, and/or comparing the major hypotheses regarding the LDG, I conclude that many of the competing hypotheses regarding the LDG can be reconciled because 1) the way the LDG is studied throughout the literature is inconsistent due to differences in assumptions underlying various hypotheses and methodologies, 2) apparent controversy over the hypotheses regarding the LDG may be an artifact of subjective biases and differences in worldviews between scientists, and 3) the LDG exists due to a combination of driving mechanisms of varying importance.
Across the 10 hypotheses and 25 papers I reviewed, there exists no standard definition for what is statistically, mathematically, or taxonomically considered an LDG. The hypotheses and studies define no standard minimum steepness at which the relationship between latitude and diversity must be observed, nor do they define a standard fit to a standard curve at which the relationship must be observed, for the relationship to “count” as a single observation of the LDG.
While some studies consider a “single” LDG, or the existence of a general latitudinal gradient of species richness incorporating the entirety of the Earth’s biodiversity, others speak of multiple latitudinal diversity gradients for given clades of organisms. Of those studies that consider multiple LDGs, the definition of an LDG is not constricted to a specific taxonomic level; rather, any observation of the decline of diversity with latitude in any taxonomic level from the lowest classification (species) to much higher-level classifications is counted simply as one instance of the LDG being observed. This is problematic because it skews the results of the study towards being more general for some groups of organisms and more specific for other groups of organisms.
Further, the studies and hypotheses I reviewed do not follow a standard minimum resolution at which the relationship between latitude and diversity can be deemed a “gradient:” in other words, the hypotheses and studies attempting to explain the LDG separate the globe into inconsistent numbers of latitudinal bands when performing analyses. For example, several hypotheses, although supported by studies that include much finer resolutions of species diversity gradients, make their arguments based on the difference between mechanisms operating in “the tropics” and “everything else,” such as the DRH and biotic hypotheses. Perhaps the most gradient-oriented hypothesis is the OTM, which, despite comparing the rates of diversification in the “tropics” to “everything else,” refers to a mechanism of range expansion underlying the LDG that is by definition truly gradating. Perhaps differences in resolution between studies of the LDG could be reconciled quantitatively through a type of data transformation that has not yet been described.
Clearly, the authors of these hypotheses and studies have varying assumptions about what defines an occurrence of the LDG and/or regarding what an LDG actually is. While scientists are still able to glean information about the LDG despite these differences, it is crucial that these differences are either eliminated or at least minimized by the creation of standard definitions surrounding the LDG, or that these differences are understood and/or better communicated by scientists so as to decrease any controversy that may arise as an artifact of these differences in assumptions rather than due to actual differences in interpretation of the data.
A related issue with studies of the LDG is that, without experimental evidence to back up a given hypothesis, as scientists offer differing ideas about various hypotheses, controversy could be a product of subjective differences in worldviews and theory dependency rather than evidence supplied by objective data, of which there is a serious lack. For example, Jansson et al. (2013) assume that migration is important, while Fine and Ree (2006) assume that it is not. Fine and Ree (2006) further suggest that the species-energy hypothesis is unlikely to be important. Ultimately, when grappling with complex patterns over large scales with little evidence at their disposal, scientists can make hand-waving claims and find nuggets of data backing up their work without receiving much criticism because in truth, there is a certain amount of guesswork and inference involved. When breaking down the different hypotheses regarding the LDG, one can ask, what is more fundamental: area, time, or energy? It is mere differences in worldviews that will sway scientists towards one or another. Even meta-analyses performing what are considered to be large-scale reviews on the LDG like those studying observations of LDGs numbering in the hundreds, the data included in these studies is patchy and incomplete, and I could even say, at risk of sounding hyperbolic, “a drop in the bucket” compared to the amount of data that would be needed to fully understand the mechanisms and processes driving the LDG.
Considering the complexity of the world and its interacting components, it seems likely that multiple mechanisms contributed to the origination and continued existence of the LDG. Even at regional scales, very rarely if never is a single mechanism responsible for an observed ecological pattern in nature – there are too many variables at play acting both singly and in tandem. At global scales, this should be even less likely. Many of the 10 hypotheses outlined above can coexist without contradicting each other. Each hypothesis can vary in importance with factors such as temporal and spatial scale, place, time, taxa, biome, and sets of environmental conditions.
Declining diversity towards the equator can be considered a general phenomenon, insofar as it is generally observed across clades and species that have been described by scientists thus far. Several caveats of the LDG include the issue of studying patterns at large spatial and temporal scales; the inherent incompleteness of the data used to study the LDG; and human biases, inconsistency, and lack of standardization when studying the LDG. There are many different hypotheses explaining the LDG, some of which can be reconciled. Here, we find an instance in which a lack of risky predictions for hypotheses explaining the LDG may actually be helpful in that this deficit can reveal what may be the truth: that no one hypothesis is more important than any other. The normal rules of ecological research may not apply when studying very large scales, and why should they? For example, the idea that many hypotheses interact with each other to explain the LDG at varying degrees flies in the face of the rule of parsimony, which when applied may otherwise erroneously force ecologists to choose one hypothesis to cling to and provide evidence for, or unhelpfully cause the scientific community to be inclined to determine one primary mechanism driving the LDG. Scientists must exercise creativity, open-mindedness, and fluid thinking in order to successfully study complex, large-scale patterns.
I argue that equal consideration should be given to each hypothesis and that the key to solving the mystery of the LDG will not be to determine which one hypothesis is correct above all others, but to determine how each hypothesis can vary in importance in relation to various intrinsic and extrinsic factors. The implications of the solution to this enigma are imperative to the conservation and maintenance of the most diversity possible in a rapidly changing, increasingly warming world. Understanding the processes underlying global patterns in species diversity will allow conservationists to conduct more effective triage as biodiversity dwindles. This is a rather grim yet practical outlook; for example, if the OTM explains a large proportion of the LDG, conservationists may consider prioritizing the tropics and building corridors to allow species to extend their ranges beyond the tropics. However, if the OTM explains less of the LDG than the GAH, conservationists may instead focus more time and energy on the protection and maintenance of large expanses of contiguous tropical habitats.
It is a great irony that the results of research lead scientists to conclude that more research should be done; alas, I too am forced to concur with this sentiment. There is an urgent need for more numerous and creative studies attempting to elucidate the causes, mechanisms, and processes underlying the LDG. In the meantime, I implore scientists to use the knowledge we already have – namely, that the LDG exists and that some combination of existing hypotheses likely tells us why – to create policy to protect the Earth’s biodiversity before it disappears.
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 The DRH is also a climate-related hypothesis, but I have included it here as a historical/evolutionary hypothesis because it more directly relates to evolutionary rates which are hypothesized to be caused by climate-related factors.
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Hi there! I am starting to get back into blog writing in the months leading up to starting grad school in the Fall of 2017 (don’t ask me where, I haven’t decided yet). One of the things I’d like to use this blog for is summarizing papers I’m reading. I hope it’ll give people a chance to access some science, even if it’s only a little bit at a time, without paying $20 for a pdf. Plus, it’ll give me some practice at translating science to a general audience. Here goes try number one!
Paper of the day: Dudley and Schmitt 1996, “Testing the adaptive plasticity hypothesis: Density-dependent selection on manipulated stem length in Impatiens capensis”
Untangling some mumbo-jumbo jargon for you first – if you decide to read the paper yourself (which I highly recommend, if you can access it for free!), you would need to understand at least these terms:
Plasticity: the ability of an organism to change its phenotype in response to changes in the environment. (i.e. human bodybuilders changing their muscle mass and distribution)
Phenotype: the set of observable characteristics of an individual resulting from the interaction of its genotype with the environment. (i.e. eye color, height)
Genotype: the genetic constitution of an individual organism. (i.e. all that DNA stuff that makes you uniquely you)
This paper tests the hypothesis that organisms adapt to the environment where they live, and therefore perform better than organisms that aren’t originally from that environment. Or in other words, “the phenotype evoked by each environment results in higher relative fitness than the alternative phenotype.” In biology, this is often referred to as the “home court advantage.” In this paper, the authors study the plant Impatiens capensis and how it responds to different environments.
In nature, Impatiens sometimes has to compete with fellow Impatiens plants or with other neighboring plant species for sunlight. How does a plant compete with other plants? Since plants can’t move, they have evolved many strategies to adapt to the environment where they’re stuck when they sprout from a seed. Many people have heard about the strategies that occur on a species-level, like cacti being able to draw on the water they hold in their bodies during dry spells in the desert. But, some species have populations spread across highly variable environments, and changes in the conditions plants face can occur from the top of a mountain to the bottom, or one football field-sized patch to the next, or at even smaller spatial scales, like one plant being next to a river and another stuck wedged between two rocks two feet away. To deal with this on an individual level, plants have evolved to be highly plastic – this means that each individual plant has the ability to adapt to its specific environment, and even if you put four genetically identical plants in different places, they could all end up looking and behaving totally differently.
That’s the basic premise of plasticity. BUT, the big question the authors ask in this paper is: is plasticity adaptive? In other words, is it a good strategy for that plant to adapt to its environment, or not? The overall goal of a species is to continue existing, so scientists determine adaptiveness by figuring out whether the adaptation contributes to that individual plant’s potential for future offspring (or “fitness”) – for example, by allowing the plant to grow bigger, make more flowers, and/or make more seeds that will grow to become the next generation of plants.
So, how does Impatiens compete with other plants for sunlight? It grows taller by elongating its stem and growing leaves higher than other plants. That way, it avoids being shaded by other plants. In this study, the authors manipulated the plants in two treatments by mimicking 1) an environment where the plants were shaded by other plants, and 2) an environment with full sunlight (not shaded by other plants). When plants were placed in the “shaded” treatment, they elongated their stems, and when they were placed in the full “sunlight” treatment, they did not elongate their stems.
Then, the scientists put the plants from each treatment, shaded or sunlight, into two different environments in nature: (1) plots where there were already lots of other plants present (high-density), and (2) plots where few other plants were present (low-density). In doing so, they were able to determine whether there was a home-court advantage, and they found that there was: plants with elongated stems performed better (or had higher “fitness”) in high-density plots than those without elongated stems. In other words, taller plants were more fit when there were other plants around for them to compete with, because they were able to reach the sunlight, whereas the shorter plants didn’t do as well because they were shaded by the other competing plants. On the other hand, plants withOUT elongated stems performed better than those WITH elongated stems in low-density plots. Why? The taller, more spindly plants tended to fall over if they were not physically held up by other plants crowding in on them (like in the high-density plots), so in the plots with only a few other plants, they were less fit than the short, squat plants that didn’t have any problem staying upright on their own.
The difference in fitness between the two environments (high or low density) that the tall vs. short plants displayed is an example of the “home court advantage.” The plants did better in the environment in which they adapted to live. But plasticity isn’t always adaptive! In a different study, some of the same researchers studied whether it was more adaptive for Impatiens to display this stem elongation type plasticity in sunny versus woodland habitats (Donohue et al. 2000). They did this because in a sunny environment, the plant can either experience sun when there are aren’t competitors, or shade when there are competitors – but in a forested area, the plants may experience shade from the tree canopy. As you can imagine, it’s not very useful for the plants to try to grow taller than the trees to reach the sun – so in this circumstance, their plastic response of elongating their stems was not as adaptive.
Why should you care about all this? It seems like it’s not important to the way people live their lives every day, but if we want to conserve and protect nature, we also have to understand all the nitty gritty messy complicated details that go along with nature. Understanding the fundamentals of plasticity itself could have enormous benefits to people when applied to medicine: imagine if you could trigger genes that activated increased production of melanin in your skin, getting a tan AND an effective sun blocker without having to expose yourself to harmful UV radiation at the same time? That’s a plastic response we could induce in humans if we knew how it all worked at a mechanistic level.
Thanks for reading! This was my first go at explaining a science paper to a relatively naive audience – my intended audience is anyone with high school-level biology or above. Send me a message or leave a comment if you have any constructive criticism!
Donohue, K., D. Messiqua, E. Hammond Pyle, M.S. Heschel, and J. Schmitt. 2000. Evidence of adaptive divergence in plasticity: density- and site-dependent selection on shade avoidance responses in Impatiens capensis. Evolution 54: 1956-1968.