A Review of Existing Studies Reporting the Negative Effects of Alcohol Access and Positive Effects of Alcohol Control Policies on Interpersonal Violence.

Alcohol consumption often leads to elevated rates of violence yet alcohol access policies continue to relax across the globe. Our review establishes the extent alcohol policy can moderate violent crime through alcohol availability restrictions. Results were informed from comprehensive selection of peer-reviewed journals from 1950 to October 2015. Our search identified 87 relevant studies on alcohol access and violence conducted across 12 countries. Seventeen studies included quasi-control design, and 23 conducted intervention analysis. Seventy-one (82%) reported a significant relationship between alcohol access and violent offenses. Alcohol outlet studies reported the greatest percentage of significant results (93%), with trading hours (63%), and alcohol price following (58%). Results from baseline studies indicated the effectiveness of increasing the price of commonly consumed alcohol, restricting the hours of alcohol trading, and limiting the number of alcohol outlets per region to prevent violent offenses. Unclear are the effects of tax reductions, restriction of on-premises re-entry, and different outlet types on violent crime. Further, the generalization of statistics over broad areas and the low number of control/intervention studies poses some concern for confounding or correlated effects on study results, and amount of information for local-level prevention of interpersonal violence. Future studies should focus on gathering longitudinal data, validating models, limiting crime data to peak drinking days and times, and wherever possible collecting the joint distribution between violent crime, intoxication, and place. A greater uptake of local-level analysis will benefit studies comparing the influence of multiple alcohol establishment types by relating the location of a crime to establishment proximity. Despite, some uncertainties particular studies showed that even modest policy changes, such as 1% increases in alcohol price, 1 h changes to closing times, and limiting establishment densities to <25 outlets per postal code substantively reduce violent crime.

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).

Exploring the ecological processes driving geographical patterns of breeding bird richness in British Columbia, Canada.

British Columbia (BC), Canada, has a diverse landscape that provides breeding habitat for > 300 avian species, and the recent development of the BC Breeding Bird Atlas data set presents key information for exploring the landscape conditions which lead to biological richness. We used the volunteer-collected raw breeding bird evidence data set to analyze the effects of sampling biases on spatial distribution of observed breeding bird species and implemented regression tree analysis (Random Forests) to examine the influence of productivity, ambient energy, and habitat heterogeneity on independently measured breeding bird richness. Results indicated that total breeding species richness is correlated with total survey effort (alpha < 0.001). By stratifying species richness by survey effort, we observed that ambient energy is the top-ranked environmental predictor of breeding bird richness across BC, which, when used in combination with a number of other environmental variables, explains -40% of the variation in richness. Using our modeled relationships, we predicted breeding bird species richness in the areas of BC not presently surveyed between three and six hours. The majority of the productive Boreal Plains, the southern portion of the Taiga Plains region, the lowlands of the Southern and Central Interior, along the Rocky Mountain Trench, and the coastal areas of the Georgia Depression are predicted to have the highest categories of breeding richness (35-57 unique species). Our results support ongoing species diversity gradient research, which identifies ambient energy as an important factor influencing species diversity distributions in the Northern Hemisphere. By linking breeding bird richness to environmental data derived from remotely sensed data and systematically collected climate data, we demonstrate the potential to monitor shifts in ambient energy as a surrogate for vertebrate habitat condition affecting population levels. By analyzing the influence of survey effort on species richness metrics, we also highlight the need to consider adding attributes to the raw breeding bird data set to describe observer experience, such as hours or seasons spent surveying, and provide survey dates to allow greater flexibility for removing survey bias. These additions can increase the utility of atlas data for species richness studies useful for conservation planning.