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How to predict community responses to perturbations in the face of imperfect knowledge and network complexity

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Helge Aufderheide, Lars Rudolf, Thilo Gross, Kevin D. Lafferty

Populations and Evolution · Submitted 15 Feb 2013

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Finally, in our assessment of model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators.

how it is stated · asserted 1.00 read the record →

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arXiv ID1302.3757 (version 5)
Pith IDI6VEQP2M, Pith's permanent record of this paper and its review
CitationHelge Aufderheide, Kevin D. Lafferty, Lars Rudolf, Thilo gross. "How to predict community responses to perturbations in the face of imperfect knowledge and network complexity." arXiv:1302.3757 (2013). https://pith.science/paper/I6VEQP2M
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,454 input tokens, $0.0002 reported.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.18 · human participants 0.02 · controlled comparison 0.03 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.33 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v5. Results and the main claim are underlined; .

It is a challenge to predict the response of a large, complex system to a perturbation. Recent attempts to predict the behaviour of food webs have revealed that the effort needed to understand a system grows quickly with its complexity, because increasingly precise information on the elements of the system is required. Here, we show that not all elements of the system need to be measured equally well. This suggests that a more efficient allocation of effort to understand a complex systems is possible. We develop an iterative technique for determining an efficient measurement strategy. Finally, in our assessment of model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators. Prioritizing the study of such species will make it easier to understand the response of complex food webs to perturbations.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 It is a challenge to predict the response of a large, complex system to a perturbation. background 1.00 0.04 0.02 asserted 1.00
s1 Recent attempts to predict the behaviour of food webs have revealed that the effort needed to understand a system grows quickly with its complexity, because increasingly precise information on the elements of the system is required. background 0.99 0.05 0.03 asserted 0.99
s2 Here, we show that not all elements of the system need to be measured equally well. result 0.71 0.67 0.39 asserted 1.00
s3 This suggests that a more efficient allocation of effort to understand a complex systems is possible. interpretation 0.99 0.21 0.21 hedged possibility 0.97
s4 We develop an iterative technique for determining an efficient measurement strategy. method 0.90 0.94 0.07 asserted 1.00
s5 Finally, in our assessment of model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators. result 1.00 0.94 0.70 asserted 1.00
s6 Prioritizing the study of such species will make it easier to understand the response of complex food webs to perturbations. interpretation 0.94 0.41 0.41 asserted 0.59

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.99.

What was examined, and what was not

sources read
  • arXiv listing abstract v5
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

It is a challenge to predict the response of a large, complex system to a perturbation. Recent attempts to predict the behaviour of food webs have revealed that the effort needed to understand a system grows quickly with its complexity, because increasingly precise information on the elements of the system is required. Here, we show that not all elements of the system need to be measured equally well. This suggests that a more efficient allocation of effort to understand a complex systems is possible. We develop an iterative technique for determining an efficient measurement strategy. Finally, in our assessment of model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators. Prioritizing the study of such species will make it easier to understand the response of complex food webs to perturbations.

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