A computational framework to map species' distributions (realized density) using occurrence-only data and environmental predictors is presented and illustrated using a textbook example and two case studies: distribution of root vole (Microtes oeconomus) in the Netherlands, and distribution of white-tailed eagle nests (Haliaeetus albicilla) in Croatia. The framework combines strengths of point pattern analysis (kernel smoothing), Ecological Niche Factor Analysis (ENFA) and geostatistics (logistic regression-kriging), as implemented in the spatstat, adehabitat and gstat packages of the R environment for statistical computing. A procedure to generate pseudo-absences is proposed. It uses Habitat Suitability Index (HSI, derived through ENFA) and distance from observations as weight maps to allocate pseudo-absence points. This design ensures that the simulated pseudo-absence points fall further away from the occurrence points in both feature and geographical spaces. After the pseudoabsences have been produced, they are combined with occurrence locations and used to build regression-kriging prediction models. The output of prediction are either probability of species' occurrence or density measures. Addition of the pseudoabsence locations has proven effective -the adjusted R-square increased from 0.71 to 0.80 for root vole (562 records), and from 0.69 to 0.83 for white-tailed eagle (135 records) respectively; pseudo-absences improve spreading of the points in feature space and ensure consistent mapping over the whole area of interest. Results of cross validation (leave-one-out method) for these two species showed that the model explains 98% of the total variability for the root vole, and 94% of the total variability for the white-tailed eagle. The framework could be further extended to Generalized multivariate Linear Geostatistical Models and spatial prediction of multiple species. A copy of the R script and detailed instruction on how to run such analysis are available via contact author's website.

Following the call from the United Nations Convention on Biological Diversity BCities & Biodiversity Outlook^project to better preserve urban biodiversity, this paper presents stakeholder-specific statements for bird conservation in city environments. Based upon the current urban bird literature we focus upon habitat fragmentation, limited habitat availability, lack of the native vegetation and vegetation structure as the most important challenges facing bird conservation in cities. We follow with an overview of the stakeholders in cities, and identify six main Urban Ecosyst groups having the greatest potential to improve bird survival in cities: i) urban planners, urban designers and (landscape) architects, ii) urban developers and engineers, iii) homeowners and tenants, iv) companies and industries, v) landscaping and gardening firms, vi) education professionals. Given that motivation to act positively for urban birds is linked to stakeholder-specific advice, we present ten statements for bird-friendly cities that are guided by an action perspective and argument for each stakeholder group. We conclude with a discussion on how the use of stakeholder-specific arguments can enhance and rapidly advance urban bird conservation action.

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Collisions between aircraft and birds, so-called "bird strikes," can result in serious damage to aircraft and even in the loss of lives. Information about the distribution of birds in the air and on the ground can be used to reduce the risk of bird strikes and their impact on operations en route and in and around air fields. Although a wealth of bird distribution and density data is collected by numerous organizations, these data are not readily available nor interpretable by aviation. This paper presents two national efforts, one in the Netherlands and one in the United States, to develop bird avoidance nodels for aviation. These models integrate data and expert knowledge on bird distributions and migratory behavior to provide hazard maps in the form of GIS-enabled Web services. Both models are in operational use for flight planning and flight alteration and for airfield and airfield vicinity management. These models and their presentation on the Internet are examples of the type of service that would be very useful in other fields interested in species distribution and movement information, such as conservation, disease transmission and prevention, or assessment and mitigation of anthropogenic risks to nature. We expect that developments in cyber-technology, a transition toward an open source philosophy, and higher demand for accessible biological data will result in an increase in the number of biological information systems available on the Internet.

Melman, Th.C.P., A.G.M. Schotman, H.A.M. Meeuwsen, R.A. Smidt, B. Vanmeulebrouk en H. Sierdsema, 2016. Ex-ante-evaluatie ANLb-2016 Ex-ante evaluation ANLb2016 for learning management; a first look at size and spatial quality of managed units in the new agri-environmental system in the Netherlands.Outine: An ex ante evaluation was performed for the new system for agricultural nature and landscape in the Netherlands (ANLb-2016), in which managers (collectives of farmers) have more responsibility as before. Objects were size, location in suitable areas and spatial coherence of the managed plots. Special attention is paid to the quality as meadow bird habitat. A comparison is made with 2010. Attention is paid to four agricultural habitats: grassland, arable fields, dry and wet veining. The focus is put on meadow birds: much knowledge is available and the greater part of the managed area concerns this group. Results: the managed area declined from about 143,000 to 90,000 ha (of which approx 23.000ha concerns expiring contracts of which continuation is uncertain). Meadow bird management is about 62-64% in suitable area (58% in 2010); 65% of it is fairly concentrated, 35% more or less dispersed. With the so called heavy management, as far as situated within suitable area, is expected to result for about 50% into a reasonable to good quality habitat. Recommendation: To improve the management it is crucial to come to objectified insights, shared by all parties concerned: managers (collectives of farmers), scientists and policy-makers. Basic items for this moment are reconnition of suitable areas, lower limits for spatial coherence and habitat quality. Here, so called learning management (learning by doing, bench mark, sharing knowledge and experience) may be very important to come to ecological effects.Trefwoorden: Agrarisch natuurbeheer, leefgebiedtypen, ruimtelijke kwaliteit, ruimtelijke samenhang