Forecasting global biodiversity threats associated with human population growth

Population growth Birth rateDeath rate Growth rateDensity (/1000) 8.8 (/1000) (/1000) 8.7 (/1000) (/1000) 9.7 (/1000)

Introduction Background Possible threats to ecosystems are human density and population growth However population growth rate is not a good estimator of exact threat Biodiversity still shown to relate to human population size Past studies Density of humans related to threatened bird species (Kerr & Currie 1995) and threatened plant species (Thompson & Jones 1999) Current study Based in relationship between human density and threats to biodiversity a statistical model was built to predict future threats The model included population data and ecological characteristics of various nations

Methods Data utilized Total number of mammal and bird species data as reported by nation according to UNEP-WCMC Animals of the World Database IUCN Red List of 2000 on critically endangered, endangered and vulnerable species Mean annual temperature per nation Mean annual precipitation per nation Human census data for 2000, 2020 and 2050 from U.S. Census Bureau Tested 114 of 230 nations review –small and island nations excluded –some nation’s data incomplete

Methods Analysis Chose potential variables that would be significantly correlated with a number of threatened species To account for nation size all frequency variables were divided by geographic area in 10 6 km 2 Variables log-transformed to normalize distributions Subset of predictor variables chose for multiple regression analysis

Results Table 1. Linear regression correlates of the number of threatened mammal and bird species per unit area (log 10) Human population density significantly correlated with threatened species per unit area { r 2 = P < 0.001} Greatest correlation with species richness Mean precipitation correlated, but temperature did not

Results Linear regression model showed human population and species richness good combined predictors Fig. 1. Predicted vs. actual values of log- transformed density of threatened species per nation for the year 2000 based on the multiple regression model: log threatened species per 106 km2= × log species richness × human population density.

Results Growing populations show increased threat to species, while declining populations show slight decrease in threat Median increase = 1.6 by 2020 and 3.0 by 2050 Largest increase threat due to high species diversity and growth rate of 3.19% is in Congo with 26 additional threatened species by 2050 United States has possible increase of 10 threatened species by 2050 although growth rate is 0.91% Although 100 of 114 nations show increase of threat by 2020, 10 of those show decrease in threat by 2050

Results Fig. 2: Forecast changes in number of mammal and bird species threatened for each of the 114 nations in 2050.

Discussion Model demonstrates that 87.9% of differences in number of threatened species can be accounted for by human population density and species richness The other 12.1% not explained by density could be due to endemic species Climate change and economic from growth could also affect biodiversity Model can be used to project threat of extinction based on population growth Model needs to be expanded: Brazil’s threatened species were underestimated showing that population density within a country cannot always account for threat alone without including demands of other countries Ultimately shows that if model can be projected to other taxa then there is a serious threat to biodiversity worldwide