Data and code from: Impact evaluation shows that hunting without quotas has contrasting effects on deer harvest across management levels
Data files
Apr 14, 2026 version files 127.16 KB
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3.hunting_data_Schleswig-Holstein.csv
23.36 KB
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4.hunting_data_state_forest.csv
92.08 KB
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model_and_prediction_SH_state_forest.R
2.90 KB
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model_and_prediction_SH_whole_state.R
3.12 KB
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README.md
5.70 KB
Abstract
Hunting is widely used to manage deer populations and their impacts on ecosystems. Various management strategies can be used to ensure that the hunting bag is of adequate size and composition to actually control population growth, including the abolishment of hunting quotas. However, the actual impacts of hunting without quotas on deer harvest are rarely assessed.
Here we evaluated the impact of hunting without quotas on roe deer (Capreolus capreolus) in Schleswig-Holstein, Germany, by comparing the hunting bag seven years before and after the abolishment of hunting quotas in the federal state and state forests. We used linear mixed models and a counterfactual approach to separate the impact of hunting without quotas from confounding factors that also influence roe deer harvest.
We found no significant change in annual harvest densities (i.e., the number of harvested roe deer per 100 ha) overall, but a significant increase in harvest densities in state forests. This increase was most pronounced in forest districts where the forest manager changed during the study.
Hunting without quotas altered the harvest sex ratio from a female-dominated to a male-dominated one in both the state forests and the entire state. Despite this decrease in relative number of females harvested, hunting without quotas still led to an increase in the absolute number of harvested females in the state forests, while fewer females were harvested across the entire state.
Synthesis and applications: Hunting without quotas increased the total and female harvest density in state forests, but actually decreased female harvest across the state. Thus, such hunting could result in source-sink dynamics that make actual reductions of roe deer densities in state forests challenging. Our study illustrates the usefulness of counterfactual approaches to objectively evaluate the effectiveness of hunting regulations as a wildlife management tool. Such approaches could be applied more routinely in the future and may be extended to evaluate the impact of hunting regimes on actual deer densities and their effects on (forest) vegetation.
Authors: Maya Hasenfuß, Johannes Signer, Niko Balkenhol
File overview
Data files (data/)
| File | Description |
|---|---|
3.hunting_data_Schleswig-Holstein.csv |
Annual roe deer harvest data for the entire federal state of Schleswig-Holstein |
4.hunting_data_state_forest.csv |
Annual roe deer harvest data for individual state forest districts, including sex- and age-class-specific harvest densities |
Both files use ; as the column separator and , as the decimal separator.
Column descriptions
3.hunting_data_Schleswig-Holstein.csv
| Column | Description |
|---|---|
hunting year |
Year of harvest |
district |
Pseudonyms (letter codes) for the actual districts to ensure anonymity |
number of hunted roe deer |
Total roe deer harvested |
roe deer density |
Harvested roe deer per 100 ha |
hunting quotas |
Whether hunting quotas were in effect (yes/no) |
NAO |
North Atlantic Oscillation winter index (current hunting year) |
NAO_2 |
North Atlantic Oscillation winter index (two years prior the respective hunting year) |
PC1–PC5 |
Principal components of environmental covariates |
COVID |
Whether the year was affected by COVID-19 restrictions (yes/no) |
hunting concept |
Changes in roe deer hunting season were included as three hunting concepts (A, B, C). For more information, see "S1: Factors potentially affecting deer harvest" within the supporting information |
4.hunting_data_state_forest.csv
Contains all columns listed above, with the addition of change of forest manager (between PC5 and COVID), plus the following sex- and age-class columns:
| Column | Description |
|---|---|
Female.density |
Harvested females per 100 ha |
Male.density |
Harvested males per 100 ha |
Juvenile.density |
Harvested juveniles per 100 ha |
Adult.density |
Harvested adults per 100 ha |
prop.female |
Proportion of females in the harvest |
prop.male |
Proportion of males in the harvest |
prop.juvenile |
Proportion of juveniles in the harvest |
prop.adult |
Proportion of adults in the harvest |
Code files (src/)
| File | Description |
|---|---|
model_and_prediction_SH_whole_state.R |
Fits linear mixed models (LMMs) and generates a prediction for roe deer harvest density across the entire state of Schleswig-Holstein, compares model structures via AIC and likelihood ratio tests. |
model_and_prediction_SH_state_forest.R |
Same modelling and prediction workflow as above, applied to the state forest dataset. |
Software requirements
- R version (4.5.1 or higher)
- Required packages:
glmmTMB,DHARMa,performance,broom.mixed,tidyverse
