Bibliographic record
Abstract
Beginning in the late 1950s, C. S. (Buzz) Holling conducted experiments to investigate how a predator's rate of prey capture is related to prey density, a relationship that had previously been dubbed the functional response (Solomon 1949). In the resulting series of seminal articles (Holling 1959a, b, 1965), Holling identified three general categories of functional response that he called Types 1, 2, and 3 (Fig. 1). Type 1 is the simplest: capture rate increases in direct proportion to prey density until it abruptly saturates. Type 2 is similar in that the rate of capture increases with increasing prey density, but in contrast to the linear increase of Type 1, Type 2 approaches saturation gradually. Type 3 is similar to Type 2 except at low prey density, where the rate of prey capture accelerates. Three types of functional responses. Holling's work struck a deep chord among ecologists. Over the 55 years since it was proposed, his classification of functional responses has been woven into the fabric of ecology, where it has acquired the aura of received knowledge. Now designated by roman numerals, Holling's functional responses appear in every introductory ecology text, usually with illustrative examples (e.g., filter feeders are Type I; insects and parasitoids, Type II; vertebrates, Type III), and his classification is commonly employed by theoretical ecologists when incorporating predation into models of population and community dynamics. Holling's classic papers have been cited nearly 4000 times, 222 times in 2012 alone. However, as with any well-established scientific dogma, it is useful to revisit its roots, and it was with great interest that I dug out my copies of Holling's work. Three messages emerged from this trip into ecological history: 1. Holling's categories serve as a reminder of the utility of mechanistic approaches in ecology. The complexity of ecological interactions can be overwhelming, at times leading ecologists to wonder whether they will ever be able to delineate general laws (e.g., Lawton 1999). In a field where contingency is king, many ecologists doubt the viability of a reductionist approach in which community dynamics can be explained by quantifying the physical environment and understanding the physiology and behavior of individuals. It is therefore worth remembering that Holling's classification of functional responses—so broadly accepted, taught, and used—was developed in a reductionist context. Holling's primary purpose in his articles was not to promote the classification of functional responses, but rather to outline the experimental and computational methods necessary to account for predation in terms of its basic components. For instance, the core value of his work on the Type II functional response lies in his demonstration that observed capture rates can be explained by taking into account the time required for a predator to handle its prey. Similarly, his work on the Type III response is notable because it develops the idea that predators increase their capture efficiency by learning as they hunt. By accounting for the basic functional components of predation, Holling was attempting to move beyond the phenomenological description of predation. By examining the mechanisms underlying his three types of functional response, he hoped to enhance the value of his classification. Whenever one sees Holling's categories put to use in ecology, it should serve as a reminder that predation is open to mechanistic explanation (e.g., Smout et al. 2010) and that a reductionist perspective can indeed be useful in ecology. 2. Despite its stature in ecology, the division of functional responses into three distinct categories has limited practical value. I reached this conclusion while tracing the lineage of the math behind Types I, II, and III. In much of the ecological literature, Eqs. 1, 2, and 4 are presented as the descriptors of Holling's categories of functional response, and the categories are treated as if they were discrete. Holling planted the seed of this tradition, supposing that Type II response was characteristic of invertebrates, whereas Type III was found only in vertebrates. However, as Real (1977) noted, Eq. 1 is just one particular case of Eq. 3 in which n = 1 and t = 0. Similarly, Equation 2 is the particular case of Eq. 3 where n = 1 and t> 0. Thus, Eq. 3 is a general model for the functional response, and Types I, II, and III are simply particular cases along a continuum. This mathematical continuity is borne out in nature; rather than being confined to Type II response, invertebrates have functional responses that span the gap between Types II and III (Hassell et al. 1977). In short, in the years since Holling first proposed them, the distinction between Types I, II, and III has become blurred. It is unfortunate that this continuity is seldom acknowledged. Classifying predation into Types I, II, and III undoubtedly has some heuristic value in introductory texts and can be useful in some aspects of research where categorization (even if arbitrary) is necessary. But it also gives the misleading impression of simplicity where none exists. When Holling's categories are used (certainly when used in introductory texts), they should be accompanied by a warning that predation can't be so easily pigeonholed. 3. Even classics disappear. I close with a note on the quirks of data retrieval. None of Holling's three classic papers on functional response is readily (or at least inexpensively) available on the Internet. Unless one is a member of the Entomological Society of Canada, the articles must be purchased from Cambridge Journals for $45 each. In an age where access to information is increasingly taken for granted, it is worrisome that students in the future will have difficulty obtaining these three blocks in ecology's foundation. I thank Marissa Baskett and Giulio DeLeo for stimulating discussions and historical insight.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".