34As the second largest cause of biodiversity loss worldwide, there is an urgent need to study the dynamics of 35 biological invasions and identify factors limiting the distribution of invasive alien species. In the present study 36 we analyze national-scale hunting bag data from Germany to predict the dispersal of raccoons in the largest non-37 native population of the species. Our focus is (1) to document changes in the distribution and abundance of 38 raccoons, (2) to identify the species-environment relationship and predict which areas will be suitable for future 39 colonization and (3) to apply a dispersal model to predict how fast the raccoon will spread to these areas. The 49 Introduction 50Worldwide, Invasive Alien Species (IAS) are associated with significant damage to the economy and public 51 health, and are considered to be one of the major threats to native biodiversity (Mack et al. 2000; Pimentel et al. 54monitoring programs help to determine the distribution of non-native species, which is necessary in order to 55 assess the impact of non-native species in terms of disease risks, economic damage and negative effects on 56 native species and the environment, and plan management actions to reduce these impacts (Engeman et al. 2006; 57 Sterner and Smith 2006; Yokomizo et al. 2009). Monitoring programs for terrestrial mammals are usually based 58 on the collation of ad-hoc records (Roy et al. 2014a), systematic surveys of abundance (such as road-kill surveys, 59tracking plots, spotlighting, pellet counts along fixed routes), or more cost intensive and logistically complicated 60 methods such as radio-tracking, mark-recapture, camera trapping, aerial surveys and DNA genotyping 61 (Woodroffe et al. 1990; Bartel et al. 2012; Engeman et al. 2013). Hunting bag data are routinely collected for 62 3 game species, and these offer an additional monitoring strategy as they can be used as a general index of long 63 term trends, population and distribution change and a proxy of abundance across time (Cattadori et al. 2003; 64 Kitson 2004; Carlsson et al. 2010). 65These abundance or presence/absence data are used in species distribution models (SDMs) to identify 66 suitable or unsuitable areas for a species based on a set of environmental covariates, and these SDMs can be used 67 to predict where a non-native species will spread to. Generally SDMs assume that the species being modelled is 68 at equilibrium with the environment (Guisan and Thuiller 2005), which means unoccupied areas are considered 69 as unsuitable for the species. However non-native species are often spreading from a few release sites and are 70therefore not at equilibrium with their environment, so absences may be due to dispersal limitation as well as 71 unsuitable environmental conditions (Václavík and Meentemeyer 2012). One approach to address this is to 72 model the dispersal process, and then weight the species distribution model by the predicted probability of 73 different areas being dispersed to (Sullivan et al. 2012 ...

The German Wildlife Information System, founded in 2001, is a long-term monitoring program documenting occurrence, number, and development of game populations throughout Germany. Population numbers are recorded by standardized counting methods in so-called reference areas. The population densities of the European hare are calculated by spotlight strip censuses in the reference areas each spring and autumn all across Germany. From 2002 to 2005, the censuses were carried out by local hunters in 510 to 676 reference areas each year. During these years, the calculated spring densities increased significantly from 11.0 (2002) to 14.5 hares/km 2 (2005) nationwide. The overall increase in spring densities was primarily caused by the population rise from spring 2003 to 2004, which correlates with the high net growth rate in 2003. In 2005, the number of counted hares varied between less than 1 and more than 107 hares/km 2 in spring and between 0 and more than 170 hares/km 2 in autumn. Because of differing landscapes in Germany, three regions were differentiated. In spring 2005, the average population densities (median) in East Germany (5.4 hares/km 2 ) and Southwest Germany (14.6 hares/km 2 ) were significantly lower than in Northwest Germany (23.9 hares/km 2 ). These regional differences had been similarly distinct in former years.

Monitoring the populations of badgers and red foxes may help us to manage these predator species as a matter of wildlife conservation and regulation. To fit the needs of a monitoring programme, the most practicable method has to be selected. Hunting bag statistics deliver large but inaccurate data amounts with low effort. Indirect and also often direct counts might deliver only presenceabsence data with high effort. Direct counts with high accuracy are very costly. Den mapping by volunteer local hunters can deliver reliable data on density and additional biological variables while being feasible and cost effective. Within reference areas all over Germany, fox and badger dens and litters were recorded, and spring and summer densities estimated as well as potential annual population increases were calculated for 2003-2007. Habitat preferences for breeding dens were also analysed. Additionally, in 2006, the distribution of badgers was surveyed by a nationwide questionnaire. Fox and badger are distributed all over Germany with some small gaps and regionally differing densities. During the monitoring period, fox and badger densities and reproduction stayed stable, at a high level corresponding to hunting bags. However, densities varied between geographical regions, with lower densities in the sparsely wooded lowland regions. A preference for forest and habitats offering shelter was clear for breeding setts and dens. Badgers especially preferred setts of natural origin.