Michael D. Jennions

ORCID: 0000-0001-9221-2788
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About
Contact & Profiles
Research Areas
  • Animal Behavior and Reproduction
  • Plant and animal studies
  • Evolutionary Psychology and Human Behavior
  • Insect and Arachnid Ecology and Behavior
  • Fish Ecology and Management Studies
  • Crustacean biology and ecology
  • Amphibian and Reptile Biology
  • Marine and fisheries research
  • Species Distribution and Climate Change
  • Ecology and Vegetation Dynamics Studies
  • Evolutionary Game Theory and Cooperation
  • Meta-analysis and systematic reviews
  • Evolution and Genetic Dynamics
  • Genetic diversity and population structure
  • Reproductive biology and impacts on aquatic species
  • Wildlife Ecology and Conservation
  • Coral and Marine Ecosystems Studies
  • Demographic Trends and Gender Preferences
  • Avian ecology and behavior
  • Morphological variations and asymmetry
  • Animal Vocal Communication and Behavior
  • Aquatic Invertebrate Ecology and Behavior
  • Parasite Biology and Host Interactions
  • Physiological and biochemical adaptations
  • Data Analysis with R

Australian National University
2016-2025

Stellenbosch University
2024-2025

Institute for Advanced Study
2016-2021

Google (United States)
2013-2018

Iowa State University
2009

RELX Group (Netherlands)
2006

University of the Ryukyus University Hospital
2006

Smithsonian Tropical Research Institute
1993-2003

University of the Ryukyus
2003

Smithsonian Institution
1997-2002

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as "p-hacking," occurs when researchers collect or select data statistical analyses until nonsignificant become significant. Here, we use text-mining demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for performing a meta-analysis show that, while probably common, its effect seems be weak relative...

10.1371/journal.pbio.1002106 article EN cc-by PLoS Biology 2015-03-13

Sexual reproduction is associated with the evolution of anisogamy and sperm-producing males egg-laying females. The ensuing competition for mates has led to sexual selection coevolution sexes. Mathematical models are extensively used test plausibility different complicated scenarios traits. Unfortunately, diversity now itself equally bewildering. Here we clarify some current debate by reviewing evolutionary explanations relationship between anisogamy, potential reproductive rates, parental...

10.1146/annurev.ecolsys.37.091305.110259 article EN Annual Review of Ecology Evolution and Systematics 2006-07-21

10.1016/s0169-5347(01)02235-2 article EN Trends in Ecology & Evolution 2001-10-01

10.1016/j.tree.2004.03.035 article EN Trends in Ecology & Evolution 2004-04-20

10.1016/j.tree.2006.01.005 article EN Trends in Ecology & Evolution 2006-02-04

Since the early 1990s, ecologists and evolutionary biologists have aggregated primary research using meta-analytic methods to understand ecological phenomena. Meta-analyses can resolve long-standing disputes, dispel spurious claims, generate new questions. At their worst, however, meta-analysis publications are wolves in sheep's clothing: subjective with biased conclusions, hidden under coats of objective authority. Conclusions be rendered unreliable by inappropriate statistical methods,...

10.1111/brv.12721 article EN cc-by-nc Biological reviews/Biological reviews of the Cambridge Philosophical Society 2021-05-07

Observer bias and other "experimenter effects" occur when researchers' expectations influence study outcome. These biases are strongest researchers expect a particular result, measuring subjective variables, have an incentive to produce data that confirm predictions. To minimize bias, it is good practice work "blind," meaning experimenters unaware of the identity or treatment group their subjects while conducting research. Here, using text mining literature review, we find evidence blind...

10.1371/journal.pbio.1002190 article EN cc-by PLoS Biology 2015-07-08

Abstract Publication bias threatens the validity of quantitative evidence from meta‐analyses as it results in some findings being overrepresented meta‐analytic datasets because they are published more frequently or sooner (e.g. ‘positive’ results). Unfortunately, methods to test for presence publication bias, assess its impact on results, unsuitable with high heterogeneity and non‐independence, is common ecology evolutionary biology. We first review both classic emerging tests funnel plots,...

10.1111/2041-210x.13724 article EN Methods in Ecology and Evolution 2021-10-09

Fewer women than men pursue careers in science, technology, engineering and mathematics (STEM), despite girls outperforming boys at school the relevant subjects. According to 'variability hypothesis', this over-representation of males is driven by gender differences variance; greater male variability leads numbers who exceed performance threshold. Here, we use recent meta-analytic advances compare academic grades from over 1.6 million students. In line with previous studies find strong...

10.1038/s41467-018-06292-0 article EN cc-by Nature Communications 2018-09-11

10.1016/s0169-5347(03)00009-0 article EN Trends in Ecology & Evolution 2003-03-01

10.1016/0169-5347(94)90202-x article EN Trends in Ecology & Evolution 1994-03-01
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