Demographic effects of road mortality on mammalian populations: a systematic review
Bibliographic record
Abstract
In light of rapidly expanding road networks worldwide, there is increasing global awareness of the growing amount of mammalian roadkill. However, the ways in which road mortality affects the population dynamics of different species remains largely unclear. We aimed to categorise the demographic parameters in mammalian populations around the world that are directly or indirectly affected by road mortality, as well as identify the most effective study designs for quantifying population-level consequences of road mortality. We conducted a comprehensive systematic review to synthesise literature published between 2000 and 2021 and out of 11,238 unique studies returned, 83 studies were retained comprising 69 mammalian species and 150 populations. A bias towards research-intensive countries and larger mammals was apparent. Although searches were conducted in five languages, all studies meeting the inclusion criteria were in English. Relatively few studies (13.3%) provided relevant demographic context to roadkill figures, hampering understanding of the impacts on population persistence. We categorised five direct demographic parameters affected by road mortality: sex- and age-biased mortality, the percentage of a population killed on roads per year (values up to 50% were reported), the contribution of roadkill to total mortality rates (up to 80%), and roadkill during inter-patch or long-distance movements. Female-biased mortality may be more prevalent than previously recognised and is likely to be critical to population dynamics. Roadkill was the greatest source of mortality for 28% of studied populations and both additive and compensatory mechanisms to roadkill were found to occur, bringing varied challenges to conservation around roads. In addition, intra-specific population differences in demographic effects of road mortality were common. This highlights that the relative importance of road mortality is likely to be context specific as the road configuration and habitat quality surrounding a population can vary. Road ecology studies that collect data on key life parameters, such as age/stage/sex-specific survival and dispersal success, and that use a combination of methods are critical in understanding long-term impacts. Quantifying the demographic impacts of road mortality is an important yet complex consideration for proactive road management.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".