Daijiang Li


McGill, Brian J. “The what, how and why of doing macroecology.” Global Ecology and Biogeography 28.1 (2019): 6-17. link to paper

Shade, A., Dunn, R. R., Blowes, S. A., Keil, P., Bohannan, B. J., Herrmann, M., … & Chase, J. (2018). Macroecology to unite all life, large and small. Trends in Ecology & Evolution. link to paper

How do we scale small scale processes to global scales?

The goal of the field of macroecology is to explain variation in species abundance, distribution, and diversity, particularly over large geographic scales. It’s useful to talk about at this stage in the semester because we’ve focused a lot on relatively local processes (e.g., competition in a single area). Many macroecological relationships do not have a clear mechanism, often ignore species differences, and almost exclusively do not consider many ecological processes we’ve discussed (e.g., competition, predation). Much of this relates to classic ecological theory on the importance of spatial scale. One idea is that some processes such as competition and predation are important largely important at very local (smaller) scales. As we “zoom out” to more coarser scales, the role of environment becomes more pronounced in determining species diversity and abundance. This is often referred to as the Eltonian noise hypothesis.

The transmutation problem Sometimes spatial scale can determine whether a pattern is observed at all. That is, a series of relationships at more local scales that can be either positive or negative can result in a clear pattern at larger spatial scales. McGill 2019 goes into a lot of detail about transmutations, which explore how different hierarchical scales may be entirely different.

A simple example is in the scaling between a local to macro scale comparison of the relationship between precipitation and productivity. This is the idea that areas that receive more precipitation, on average, have higher productivity (more green biomass, essentially). But this is a bit site-specific, right? We can imagine that productivity could go up with precipitation if plants require more water, but the opposite relationship could be observed as nutrients are washed away from the soil and plants are exposed to too much water. While the local context would suggest no clear relationship, plotting a series of these local relationships yields a general macroecological relationship between precipitation and productivity.

Macroecological relationships allow scientists to undercover generalized laws about how biodiversity is distributed. That is, at some spatial scale, the influence of many small scale ecological processes will become relatively unimportant, and global (or macro) scale patterns will emerge. We’ll go over some examples of macroecological laws here, and be sure to read to the McGill paper for more information on the historical and conceptual history of macroecology.

The dimensionality of macroecology The scope of macroecology is perhaps best depicted in terms of spatial, temporal, and taxonomic scales of study. How many of these do you think would need to be incorporated to qualify as “macroecology”?

Figure taken from McGill (2019)

Figure taken from McGill (2019)

Latitudinal scaling

Latitude is a major driver of variation in species diversity and range dynamics. Latitudinal variation represents large climatic variation, but could also relate to solar radiation, historical biogeographic processes, land area, etc.

Latitudinal diversity gradient Species richness (alpha diversity) tends to be highest near the equator, and declines toward the poles. This pattern has been studied for many different groups of organisms (including parasites!) and is pretty consistent. As with many macroecological patterns though, it is difficult to attribute mechanism to the pattern. Latitude is not really an ecologically driver, but temperature, precipitation, land area, and geological history are all associated with latitude in some form.

species-energy hypothesis: the amount of energy sets limits to the species richness an area can achieve (relate this back to food web structure). So more primary productivity in lower latitudes through increased light availability leads to more species in the food web.

climatic stability hypothesis: Fluctuating environments tend to cause species extinctions. Environmental conditions tend to fluctuate more at higher latitudes.

The mid-domain effect The inherent constraints on latitude and shifting species ranges causes species richness to peak at middle latitudes. That is, assuming the random placement of a species with some fixed latitudinal range, there will still be more species near the equator.

The mid-domain effect doesn’t mean that we shouldn’t look for latitudinal diversity relationships, but we should recognize that they could be the result of randomness. Teasing the randomness from the pattern sometimes requires the use of a null model. In the case of the mid-domain effect, a null model would correspond to shuffling species ranges around and measuring the strength and variation in the resulting latitudinal diversity relationship. We also talked about null models a bit when we discussed ecological networks (specifically the importance of a single node to a property of the entire network).

What is the theory of island biogeography?

As discussed above with respect to patch occupancy in metapopulations, the theory of island biogeography attempts to explain the colonization and extinction of species (and subsequently the species richness of islands) as a function of island area and distance from the mainland. These two things influence the number of species that can colonize and persist on a given island, as distance from a mainland source is proportional to species dispersal and colonization probability and island area controls the population size attainable by a given species, and thus influences extinction rate. That is, the theory is based on the relationship between distance from the mainland (colonization rate) and island area (extinction rate) in determining the number of species that an island contains. This is fundamentally related to a metapopulation, as the structure of the landscape is the same. That is, a metapopulation consists of habitat patches connected by dispersal but within an inhospitable landscape. The theory of island biogeography assumes the same, originally developed to explain the number of species on isolated islands.

This assumes that all islands are reachable by every species in the community with a non-zero probability, and is spatially-implicit (i.e., the actual locations of habitat patches are not considered).

Species-area relationships

One clear extension, and honestly the original purpose of island biogeography theory, is the study of species-area relationships. The idea here is that increasing geographic area results in a greater number of unique species able to occupy the patch.

Species-area relationships exist in two different forms, depending on how the data are structured. The most related to island biogeography theory is the “island” species-area relationship, where a set of discontiguous habitats are studied, and the area of each patch is related to species richness in that patch. The second – called the “mainland” species-area relationship – considers a contiguous habitat where patches are nested within another.

\[ S = cA^{z} \]

where \(S\) is the number of species, \(A\) is patch area, \(z\) describes the shape of the relationships, and \(c\) is a constant. \(c\) actually describes the number of species we would expect to find in one unit of sampling area (whatever the unit is in the study).