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Basal cell carcinoma (BCC) is the most common malignant tumor among fair-skinned individuals, and its incidence had been steadily rising in the past decades. In order to maintain the highest quality of patient care possible, the German S2k guidelines were updated following a systematic literature search and with the participation of all professional societies and associations involved in the management of the disease. Part 2 addresses issues such as proper risk stratification, the various therapeutic approaches, and prevention as well as follow-up of patients with basal cell carcinoma.

Banks-Leite et al. (2021) claim that our suggestion of preserving ≥40% forest cover lacks evidence and can be problematic. We find these claims unfounded, and discuss why conservation planning urgently requires valuable, well-supported, and feasible general guidelines like the 40% criterion. Using region-specific thresholds worldwide is unfeasible and potentially harmful.

Agriculture and development transform forest ecosystems to human-modified landscapes. Decades of research in ecology have generated myriad concepts for the appropriate management of these landscapes. Yet, these concepts are often contradictory and apply at different spatial scales, making the design of biodiversity-friendly landscapes challenging. Here, we combine concepts with empirical support to design optimal landscape scenarios for forest-dwelling species. The supported concepts indicate that appropriately sized landscapes should contain ≥ 40% forest cover, although higher percentages are likely needed in the tropics. Forest cover should be configured with c. 10% in a very large forest patch, and the remaining 30% in many evenly dispersed smaller patches and semi-natural treed elements (e.g. vegetation corridors). Importantly, the patches should be embedded in a high-quality matrix. The proposed landscape scenarios represent an optimal compromise between delivery of goods and services to humans and preserving most forest wildlife, and can therefore guide forest preservation and restoration strategies.

Basal cell carcinoma is the most common malignant tumor among fair-skinned individuals, and its incidence has been rising steadily in the past decades. In order to maintain the highest quality of patient care possible, the German S2k guidelines were updated following a systematic literature search and with the participation of all professional societies and associations involved in the management of the disease. Part 1 highlights new developments in genetics in particular as well as aspects regarding epidemiology, diagnosis, and histology.

Agricultural landscape homogenization has detrimental effects on biodiversity and key ecosystem services. Increasing agricultural landscape heterogeneity by increasing seminatural cover can help to mitigate biodiversity loss. However, the amount of seminatural cover is generally low and difficult to increase in many intensively managed agricultural landscapes. We hypothesized that increasing the heterogeneity of the crop mosaic itself (hereafter “crop heterogeneity”) can also have positive effects on biodiversity. In 8 contrasting regions of Europe and North America, we selected 435 landscapes along independent gradients of crop diversity and mean field size. Within each landscape, we selected 3 sampling sites in 1, 2, or 3 crop types. We sampled 7 taxa (plants, bees, butterflies, hoverflies, carabids, spiders, and birds) and calculated a synthetic index of multitrophic diversity at the landscape level. Increasing crop heterogeneity was more beneficial for multitrophic diversity than increasing seminatural cover. For instance, the effect of decreasing mean field size from 5 to 2.8 ha was as strong as the effect of increasing seminatural cover from 0.5 to 11%. Decreasing mean field size benefited multitrophic diversity even in the absence of seminatural vegetation between fields. Increasing the number of crop types sampled had a positive effect on landscape-level multitrophic diversity. However, the effect of increasing crop diversity in the landscape surrounding fields sampled depended on the amount of seminatural cover. Our study provides large-scale, multitrophic, cross-regional evidence that increasing crop heterogeneity can be an effective way to increase biodiversity in agricultural landscapes without taking land out of agricultural production. This research was funded by the ERA-Net BiodivERsA, with the national funders French National Research Agency (ANR-11-EBID-0004), German Ministry of Research and Education, German Research Foundation and Spanish Ministry of Economy and Competitiveness, part of the 2011 BiodivERsA call for research proposals. The UK component of this research was funded by the UK Government Department of the Environment, Food and Rural Affairs (Defra), as Project WC1034. The Canadian component of this research was funded by a Natural Sciences and Engineering Research Council of Canada Strategic Project, the Canada Foundation for Innovation, Environment Canada, and Agriculture and Agri-Food Canada. N.G. was supported by the AgreenSkills+ Fellowship programme which has received funding from the EU’s Seventh Framework Programme under Grant Agreement FP7-609398 (AgreenSkills+ contract). A.G.-T. (Juan de la Cierva Fellow, JCI-2012-12089) was funded by Ministerio de Economía y Competitividad (Spain). C. Violle was supported by the European Research Council Starting Grant Project “Ecophysiological and biophysical constraints on domestication of crop plants” (Grant ERC-StG-2014-639706-CONSTRAINTS). A.R.’s position at the University of Alicante is funded by the “Vicerrectorado de Investigación y Transferencia de Conocimiento.”

In a review of landscape-scale empirical studies, Fahrig (2017a) found that ecological responses to habitat fragmentation per se (fragmentation independent of habitat amount) were usually non-significant (>70% of responses) and that 76% of significant relationships were positive, with species abundance, occurrence, richness, and other response variables increasing with habitat fragmentation per se. Fahrig concluded that to date there is no empirical evidence supporting the widespread assumption that a group of small habitat patches generally has lower ecological value than large patches of the same total area. Fletcher et al. (2018) dispute this conclusion, arguing that the literature to date indicates generally negative ecological effects of habitat fragmentation per se. They base their argument largely on extrapolation from patch-scale patterns and mechanisms (effects of patch size and isolation, and edge effects) to landscape-scale effects of habitat fragmentation. We argue that such extrapolation is unreliable because: (1) it ignores other mechanisms, especially those acting at landscape scales (e.g., increased habitat diversity, spreading of risk, landscape complementation) that can counteract effects of the documented patch-scale mechanisms; and (2) extrapolation of a small-scale mechanism to a large-scale pattern is not evidence of that pattern but, rather a prediction that must be tested at the larger scale. Such tests were the subject of Fahrig's review. We find no support for Fletcher et al.'s claim that biases in Fahrig's review would alter its conclusions. We encourage further landscape-scale empirical studies of effects of habitat fragmentation per se, and research aimed at uncovering the mechanisms that underlie positive fragmentation effects.

1. Human activities exert stress on and create disturbances to ecosystems, decreas- ing their diversity, resilience and ultimately the health of ecosystems and their vegetation. In environments with rapid changes in vegetation health (VH), pro- gress is needed when it comes to monitoring these changes and underlying causes. There are different approaches to monitoring VH such as in situ species ap- proaches and the remote-sensing approach. 2. Here we provide an overview of in situ species approaches, that is, the biological, the phylogenetic, and the morphological species concept, as well as an overview of the remote-sensing spectral trait/spectral trait variations concept to monitor the status of VH as well as processes of stress, disturbances, and resource limita- tions affecting VH. The approaches are compared with regard to their suitability for monitoring VH, and their advantages, disadvantages, potential, and require- ments for being linked are discussed. 3. No single approach is sufficient to monitor the complexity and multidimensional- ity of VH over the short to long term and on local to global scales. Rather, every approach has its pros and cons, making it all the more necessary to link approaches. In this paper, we present a framework and list crucial requirements for coupling approaches and integrating additional monitoring elements to form a multisource vegetation health monitoring network (MUSO-VH-MN). 4. When it comes to linking the different approaches, data, information, models or plat- forms in a MUSO-VH-MN, big data with its complexity and syntactic and semantic heterogeneity and the lack of standardized approaches and VH protocols pose the greatest challenge. Therefore, Data Science with the elements of (a) digitalization, (b) semantification, (c) ontologization, (d) standardization, (e) Open Science, as well as (f) open and easy analyzing tools for assessing VH are important requirements for moni- toring, linking, analyzing, and forecasting complex and multidimensional changes in VH.

Simple rules for landscape management seem elusive because different species and species groups are associated with different land cover types; a change in landscape structure that increases diversity of one group may reduce diversity of another. On the other hand, if simple landscape–biodiversity relationships do exist despite this complexity, they would have great practical benefit to conservation management. With these considerations in mind, we tested for consistent relationships between landscape heterogeneity and biodiversity in farmland (the cropped areas in agricultural landscapes), with a view to developing simple rules for landscape management that could increase biodiversity within farmland. Our measures of farmland heterogeneity were crop diversity and mean crop field size, where increases in crop diversity and/or decreases in mean field size represent increasing landscape heterogeneity. We sampled the abundance, and alpha, gamma and beta diversity of birds, plants, butterflies, syrphids, bees, carabids and spiders, in crop fields within each of 93 1 km × 1 km agricultural landscapes. The landscapes were selected to represent three gradients in landscape composition and heterogeneity: proportion of the landscape in crop, mean crop field size and Shannon crop type diversity of the farmland. We found that mean crop field size had the strongest overall effect on biodiversity measures in crop fields, and this effect was consistently negative. Based on our results we suggest that, if biodiversity conservation in crop fields is a priority, policies and guidelines aimed at reducing crop field sizes should be considered.

The rapid development in information and computer technology has facilitated an extreme increase in the collection and storage of digital data. However, the associated rapid increase in digital data volumes does not automatically correlate with new insights and advances in our understanding of those data. The relatively new technique of data mining offers a promising way to extract knowledge and patterns from large, multidimensional and complex data sets. This paper therefore aims to provide a comprehensive overview of existing data mining techniques and related tools and to illustrate the potential of data mining for different research areas by means of example applications. Despite a number of conventional data mining techniques and methods, these classical approaches are restricted to isolated or “silo” data sets and therefore remain primarily stand alone and specialized in nature. Highly complex and mostly interdisciplinary questions in environmental research cannot be answered sufficiently using isolated or area-based data mining approaches. To this end, the linked open data (LOD) approach will be presented as a new possibility in support of complex and inter-disciplinary data mining analysis. The merit of LOD will be explained using examples from medicine and environmental research. The advantages of LOD data mining will be weighed against classical data mining techniques. LOD offers unique and new possibilities for interdisciplinary data analysis, modeling and projection for multidimensional, complex landscapes and may facilitate new insights and answers to complex environmental questions. Our paper aims to encourage those research scientists which do not have extensive programming and data mining knowledge to take advantage of existing data mining tools, to embrace classical data mining and LOD approaches in support of gaining more insight and recognizing patterns in highly complex data sets.

For quantifying and modelling of landscape patterns, the patch matrix model (PMM) and the gradient model (GM) are fundamental concepts of landscape ecology. While the PMM model has been the backbone for our advances in landscape ecology, it may also hamper truly universal insights into process–pattern relationships. The PMM describes landscape structures as a mosaic of discretely delineated homogenous areas. This requires simplifications and assumptions which may even result in errors which propagate through subsequent analyses and may reduce our ability to understand effects of landscape structure on ecological processes. Alternative approaches to represent landscape structure should therefore be evaluated. The GM represents continuous surface characteristics without arbitrary vegetation or land-use classification and therefore does not require delineation of discrete areas with sharp boundaries. The GM therefore lends itself to be a more realistic representation of a particular surface characteristic. In the paper PMM and GM are compared regarding their prospects and limitations. Suggestions are made regarding the potential use and implementation of both approaches for process–pattern analysis. The ecological and anthropogenic process itself and its characteristics under investigation is decisive for: (i) the selection of discrete and/or continuous indicators, (ii) the type of the quantitative pattern analysis approach to be used (PMM/GM) and (iii) the data and the scale required in the analysis. Process characteristics and their effects on pattern characteristics in space and time are decisive for the applicability of the PMM or of the GM approach. A low hemeroby (high naturalness and low human pressure on landscapes) allows for high internal-heterogeneity in space and over time within patterns. Such landscapes can be captured with the GM approach. A high hemeroby reduces heterogeneity in space and time within patterns. For such landscapes we recommend the PMM model.

article i nfo Article history: Maps based on classified Earth observation (EO) imagery have been used to model biodiversity, but errors asso- ciatedwiththe classificationprocessitselfandthe resulting discretizationoflandcovermayultimatelylimitsuch efforts. Among other issues, discrete land cover maps can often be costly to produce and validate. Alternatively, the original continuous spectral information in EO imagery can be used. The primary objective of this study was to compare predictors based on continuous and discrete information derived from Landsat TM imagery for modelingbiodiversityinagriculturallandscapes.In46landscapesthroughoutEasternOntario,Canada,landscape metrics (mean field size, the percentage of landscape in agriculture, and crop diversity) derived from a discrete image classification, along with several measures of crop productivity based on the continuous Normalized Dif- ference Vegetation Index (NDVI), were used as predictors of field-based measures of species diversity for birds, butterflies, and plants. Using an Information-Theoretic approach for model-averaging and inference, we com- pared and interpreted the magnitude and direction of model-averaged coefficients, model evidence ratios, and overall fit of model-averaged predictions. Our findings indicate that when using Landsat TM imagery in agricul- tural environments, models using predictors derived from continuous information consistently outranked models based on discrete information derived from classified imagery.

Aim Species distribution models (SDMs) coupled with metapopulation dynamics models can integrate multiple threats and population-level processes that influence species distributions. However, multiple sources of uncertainties could lead to substantial differences in model outputs and jeopardize risk assessments. We evaluate uncertainties in coupled species distribution–metapopulation dynamics models and focus on two often underappreciated sources of uncertainty: the choice of general circulation model (GCM) and demographic parameter uncertainty of the metapopulation model. We rank the risks associated with potential climate changes and habitat loss on projected range margin dynamics of the Hooded Warbler (Setophaga citrina). Location Breeding range of the Hooded Warbler, North America. Methods Using SDMs, we quantified variability in projected future distributions using four GCMs and a consensus model at the biogeographic scale and assessed the propagation of uncertainty through to metapopulation viability projections. We applied a global sensitivity analysis to the coupled species distribution–metapopulation models to rank the influence of choice of GCM, parameter uncertainty and simulated effects of habitat loss on metapopulation viability, thereby addressing error propagation through the whole modelling process. Results The Hooded Warbler range was consistently projected to shift north: choice of GCMs influenced the magnitude of change, and variability was spatially structured. Variability in the choice of GCMs propagated through to metapopulation viability at the northern range boundary. Although viability measures were sensitive to the GCM used, measures of direct habitat loss were more influential. Despite the high ranking of vital rates in the global sensitivity analysis, direct habitat loss had a larger negative influence on extinction risk than potential future climate changes. Main conclusions This work underscores the importance of a global sensitivity analysis framework applied to coupled models to disentangle the relative influence of uncertainties on projections. The use of multiple GCMs enabled the exploration of a range of possible outcomes relative to the consensus GCM, helping to inform risk estimates. Ranking uncertainties informs the prioritization of management actions for species affected by dynamic anthropogenic threats over multiple spatial scales.

We examined the effects of matrix structure and movement responses of organisms on the relationships between 7 patch isolation metrics and patch immigration. Our analysis was based on simulating movement behaviour of two generic disperser types (specialist and generalist) across mosaic landscapes containing three landcover types: habitat, hospitable matrix and inhospitable matrix. Movement, mortality and boundary crossing probabilities of simulated individuals were linked to the landcover and boundary types in the landscapes. The results indicated that area-based isolation metrics generally predict patch immigration more reliably than distance-based isolation metrics. Relationships between patch isolation metrics and patch immigration varied between the two generic disperser types and were affected by matrix composition or matrix fragmentation. Patch immigration was always affected by matrix composition but not by matrix fragmentation. Our results do not encourage the generic use of patch isolation metrics as a substitute for patch immigration, in particular in metapopulation models where generic use may result in wrong projections of the survival probability of metapopulations. However, our examination of the factors affecting the predictive potential of patch isolation metrics should facilitate interpretation and comparison of existing patch isolation studies. Future patch isolation studies should include information about landscape structure and the dispersal distance and dispersal behaviour of the organism of interest.

Habitat isolation can affect the distribution and abundance of wildlife, but it is an ambiguous attribute to measure. Presumably, isolation is a characteristic of a habitat patch that reflects how spatially inaccessible it is to dispersing organisms. We identified four isolation metrics (nearest-neighbor distance, Voronoi polygons, proximity index, and habitat buffers) that were representative of the different families of metrics that are commonly used in the literature to measure patch isolation. Using simulated data, we evaluated the ability of each isolation metric to predict animal dispersal. We examined the simulated movement of organisms in two types of landscapes: an artificially-generated point-pattern landscapes where patch size and shape were consistent and only the arrangement of patches varied, and realistic landscapes derived from a geographic information system (GIS) of forest-vegetation maps where patch size, shape, and isolation were variable. We tested the performance of the four isolation metrics by examining the strength of the correlation between observed immigration rate in the simulations and each patch isolation metric. We also evaluated whether each isolation metric would perform consistently under varying conditions of patch size/shape, total amount of habitat in the landscape, and proximity of the patch to the landscape edge. The results indicate that a commonly-used distance-based metric, nearest-neighbor distance, did not adequately predict immigration rate when patch size and shape were variable. Area-informed isolation metrics, such as the amount of available habitat within a given radius of a patch, were most successful at predicting immigration. Overall, the use of area-informed metrics is advocated despite the limitation that these metrics require parameterization to reflect the movement capacity of the organism studied.

I am a co-author of the S2k-guideline on basal cell carcinoma (BCC), which is in its final stages of development. Supported by 40 years’ experience in tumor surgery on facial skin and by long-term analyses of more than 3800 operations for facial BCC, my views differ somewhat from those expressed in the article. Hedgehog signaling pathway inhibitors allow a new therapeutic principle in BCC. Because of their short time of use, however, many questions remain open. In the guideline indications are defined for so extensive and metastatic cases of BCC, which therefore can be neither treated by radiation nor by surgery. — A tumor board decides on their use. Competent surgeons and radiologists are a mandatory on such a board. Non-surgical local therapies (laser, cryotherapy, immunomodulators imiquimod, 5-fluorouracil, photodynamic therapy) are reserved for individual cases because of barely predictable oncological and esthetic results. Local recurrences or residual tumors occur in more than 10% of cases after such treatments. For the surgery that is potentially required subsequently, these cause problems regarding R0 resection because of multilocal and poorly localizable tumor residues. According to the guideline, the surgical approach with the highest possible degree of control of the resection margin (Microscopically controlled surgery- MCS) is the method of choice. Compared with conventional surgery, MCS lowers the recurrence rate in primary BCC by only 1% and thus does not significantly improve the prognosis. When treating tumor recurrences, MCS reduces the recurrence rate from 12% to 2.4%. According to my own analyses, surgical treatment for BCC by means of MCS using plastic-surgical or rare epithetic defect repairs on the face, will—in primary BCC—yield a probability for 20 tumor-free years of 98.2%; in the treatment of recurrences in a retrospective analysis of 74%; and in a prospective analysis, consistenly using our variant of MCS, of 98%. Untreated R1 results lower this probability of success drastically, to 52% (primary BCC) and 29% (BCC recurrence). This confirms the validity of the R1 finding for tumor clearance. It does not affect survival. Diverse methods for reconstructions of the defects in the repertoire of maxillofacial surgeons in association with MCS allow a high degree of oncological certainty even in extensive BCC in combination with good esthetic results, even in the problematic facial region.

P 0 Opinion is intended to facilitate communication between reader and author and reader and I reader. Comments, viewpoints or suggestions arising from published papers are welcome. N 1 s T Discussion and debate about important issues in ecology, e.g. theory or terminology, may I I also be included. Contributions should be as precise as possible and references should be P 0 kept to a minimum. A summary is not required. o N

The ecological interpretation of landscape patterns is one of the major objectives in landscape ecology. Both landscape patterns and ecological processes need to be quantified before statistical relationships between these variables can be examined. Landscape indices provide quantitative information about landscape pattern. Response variables or process rates quantify the outcome of ecological processes (e.g., dispersal success for landscape connectivity or Morisita's index for the spatial distribution of individuals). While the principal potential of this approach has been demonstrated in several studies, the robustness of the statistical relationships against variations in landscape structure or against variations of the ecological process itself has never been explicitly investigated. This paper investigates the consistency of correlations between a set of landscape indices (calculated with Fragstats) and three response variables from a simulated dispersal process across heterogeneous landscapes (cell immigration, dispersal success and search time) against variation in three experimental treatments (control variables): habitat amount, habitat fragmentation and dispersal behavior. I found strong correlations between some landscape indices and all three response variables. However, 68% of the statistical relationships were highly inconsistent and sometimes ambiguous for different landscape structures and for differences in dispersal behavior. Correlations between one landscape index and one response variable could range from highly positive to highly negative when derived from different spatial patterns. I furthermore compared correlation coefficients obtained from artificially generated (neutral) landscape models with those obtained from Landsat TM images. Both landscape representations produced equally strong and weak statistical relationships between landscape indices and response variables. This result supports the use of neutral landscape models in theoretical analyses of pattern-process relationships.

This paper examines the usage and measurement of “landscape connectivity” in 33 recent studies. Connectivity is defined as the degree to which a landscape facilitates or impedes movement of organisms among resource patches. However, connectivity is actually used in a variety of ways in the literature. This has led to confusion and lack of clarity related to (1) function vs structure, (2) patch isolation vs landscape connectivity and, (3) corridors vs connectivity. We suggest the term connectivity should be reserved for its original purpose. We highlight nine studies; these include modeling studies that actually measured connectivity in accordance with the definition, and empirical studies that measured key components of connectivity. We found that measurements of connectivity provide results that can be interpreted as recommending habitat fragmentation to enhance landscape connectivity. We discuss reasons for this misleading conclusion, and suggest a new way of quantifying connectivity, which avoids this problem. We also recommend a method for reducing sampling intensity in landscape-scale empirical studies of connectivity.

The methods for measuring landscape connectivity have never been compared or tested for their responses to habitat fragmentation. We simulated movement, mortality and boundary reactions across a wide range of landscape structures to analyze the response of landscape connectivity measures to habitat fragmentation. Landscape connectivity was measured as either dispersal success or search time, based on immigration into all habitat patches in the landscape. Both measures indicated higher connectivity in more fragmented landscapes, a potential for problematic conclusions for conservation plans. We introduce cell immigration as a new measure for landscape connectivity. Cell immigration is the rate of immigration into equal-sized habitat cells in the landscape. It includes both within- and between-patch movement, and shows a negative response to habitat fragmentation. This complies with intuition and existing theoretical work. This method for measuring connectivity is highly robust to reductions in sample size (i.e., number of habitat cells included in the estimate), and we hypothesize that it therefore should be amenable to use in empirical studies. The connectivity measures were weakly correlated to each other and are therefore generally not comparable. We also tested immigration into a single patch as an index of connectivity by comparing it to cell immigration over the landscape. This is essentially a comparison between patch-scale and landscape-scale measurement, and revealed some potential for patch immigration to predict connectivity at the landscape scale. However, this relationship depends on the size of the single patch, the dispersal characteristics of the species, and the amount of habitat in the landscape. We conclude that the response of connectivity measures to habitat fragmentation should be understood before deriving conclusions for conservation management.

A major problem in ecological modelling is finding the appropriate level of resolution when describing the processes and structures of ecological systems. When modelling basic ecological questions, as a rule the best approach is to ignore as much detail as possible in order to obtain general insights. However, for applied problems focusing in particular on ecological systems, there are no clear guidelines for identifying the most appropriate resolution in space, time and the detail of description. Spatially explicit modelling thus has to mainly rely on trial and error in scaling-up from modelling at the local scale to exploration of the model at the global scale. We demonstrate here a modelling strategy that takes the opposite approach: starting at the global scale, with a strategic model of minimum resolution, we proceed step by step to a model addressing applied questions. The strategic model is designed to reproduce a certain pattern observed in nature. As an example, we use the wave-like spreading pattern of rabies. The applied model addresses the question of whether rabies might persist in areas with a high proportion of foxes immunized by oral vaccination. As a consequence of our scaling-down strategy, the resolution of the applied model is not chosen a priori, but emerges from the step by step modelling strategy. During each step of model refinement, one module of the preceding model is described with a slightly increased resolution. This stepwise approach allows both a backward reference to the pattern reproduced by the strategic model and a cross-reference between the coarser and finer version of the module refined. The main potential of the scaling-down strategy is that it leads to efficient models in an efficient way, but since scaling-down is a complement to scaling-up approaches, it might also help to bridge the gap between theoretical and applied ecological modelling.

Understanding the response of organisms to heterogeneous, mosaic-like landscapes is of key importance for landscape ecology, especially for predicting the consequences of the impacts of landscape patterns on the spatial distribution of species. It is of current interest whether simulation models can carry out the necessary transformation between field data and larger spatial and temporal scales. We present a model which simulates the small scale movements of forest carabids, adjusted to a typical representative, Abax parallelepipedus, through hedgerows of different widths and lengths. The modelled individual's responses to the heterogeneous landscape differ because movement patterns, survival times and boundary reactions differ among the different patch types. We evaluate the transition probability through hedgerows as the proportion of the individuals attaining a patch at the end of a hedgerow. Our results predict maximum immigration distances of about 100 m into hedgerows for forest carabids during one season which corresponds with empirical findings based on trapping studies. This result is a promising example that the effect of landscape-dependent movements can be estimated using suitable simulation models and that transformation between the different scales inherent in the empirical methods, tracing and trapping is possible.

We conducted a factorial simulation experiment to analyze the relative importance of movement pattern, boundary-crossing probability, and mortality in habitat and matrix on population density, and its dependency on habitat fragmentation, as well as inter-patch distance. We also examined how the initial response of a species to a fragmentation event may affect our observations of population density in post-fragmentation experiments. We found that the boundary-crossing probability from habitat to matrix, which partly determines the emigration rate, is the most important determinant for population density within habitat patches. The probability of crossing a boundary from matrix to habitat had a weaker, but positive, effect on population density. Movement behavior in habitat had a stronger effect on population density than movement behavior in matrix. Habitat fragmentation and inter-patch distance may have a positive or negative effect on population density. The direction of both effects depends on two factors. First, when the boundary-crossing probability from habitat to matrix is high, population density may decline with increasing habitat fragmentation. Conversely, for species with a high matrix-to-habitat boundary-crossing probability, population density may increase with increasing habitat fragmentation. Second, the initial distribution of individuals across the landscape: we found that habitat fragmentation and inter-patch distance were positively correlated with population density when individuals were distributed across matrix and habitat at the beginning of our simulation experiments. The direction of these relationships changed to negative when individuals were initially distributed across habitat only. Our findings imply that the speed of the initial response of organisms to habitat fragmentation events may determine the direction of observed relationships between habitat fragmentation and population density. The time scale of post-fragmentation studies must, therefore, be adjusted to match the pace of post-fragmentation movement responses.

We conducted an experimental landscape study to test the hypotheses that: (1) habitat removal results in short-term increases in population density in the remaining habitat patches (the crowding effect); (2) following habitat removal, density is higher in landscapes with more, smaller patches and more habitat edge (i.e., a higher level of habitat fragmentation per se) than in less fragmented landscapes, for the same total amount of habitat on the landscapes; (3) this positive effect of fragmentation per se on density is larger in landscapes with smaller inter-patch distances; and (4) these last two effects should be reduced or disappear over time following habitat removal. Our results did not support the first hypothesis, but they provided some support for the other three hypotheses, for two of the four Coccinellid species studied. As in other empirical studies of fragmentation per se on population density, the effects of fragmentation per se were weak and positive (when they did occur). This is the first study to document a transient effect of fragmentation per se on population density, and to show that this effect depends on inter-patch distances. We suggest that fragmentation per se increased the rate of immigration to patches, resulting in higher population densities in more fragmented landscapes.

We used a simulation model to study the spatio-temporal dynamics of a potential rabies outbreak in an immunized fox population after the termination of a long-term, large-scale vaccination program with two campaigns per year one in spring and one in autumn. The ‘worst-case’ scenario of rabies resurgence occurs if rabies has persisted at a low prevalence despite control and has remained undetected by a customary surveillance program or if infected individuals invade to the control area. Even if the termination of a vaccination program entails such a risk of a subsequent new outbreak, prolonged vaccination of a wild host population is expensive and the declining cost-benefit ratio over time eventually makes it uneconomic. Based on the knowledge of the spatio-temporal dynamics of a potential new outbreak gained from our modelling study, we suggest “terminating but observing” to be an appropriate strategy. Simulating the decline of population immunity without revaccination, we found that a new outbreak of rabies should be detected by customary surveillance programs within two years after the termination of the control. The time until detection does not depend on whether vaccination was terminated within the fourth, fifth or sixth years of repeated biannual campaigns. But it is faster if the program was completed with an autumn campaign (because next-year dispersal then occurs after a noticeable decrease in population immunity). Finally, if a rabid fox is detected after terminating vaccination, we determine a rule for defining a circular hazard area based on the simulated spatial spread of rabies. The radius of this area should be increased with the time since the last vaccination campaign. The trade-off between the number of foxes potentially missed by the emergency treatment and the cost for the emergency measures in an enlarged hazard area was found.

The large-scale immunization of European fox populations against rabies is currently under the microscope for reducing the considerable expenditure without putting public health at risk. Empirical knowledge is inadequate to interpret the lasting sporadic incidences and, therefore, to verify the final success of the immunization campaigns. By using a proven simulation model we show that rabies can persist on a very low level in the form of spatio-temporal moving infection clusters within a highly immunized fox population. We found further: (i) the existence of a threshold after which the chance of eradicating the disease by vaccination increases clearly, and (ii) that at least six years of 70% mean immunization rate are required to guarantee a likely success.

Corridors are supposed to facilitate and conduct moving individuals between habitat remnants within an otherwise inhospitable landscape. Despite the scientific interest in corridors, their function as conduits is open to question. In this paper we present hypothetical answers to this question based on simulations of individual movements through corridors. Our generic modeling approach is individual-based and spatially explicit. The model is designed to simulate conceivable movements of small animals through line corridors with clear boundaries such as hedgerows. The parameters of the individual movements correspond with empirical data of tracking studies. We define the transition probability as the likelihood that moving individuals attain a distant target area within a certain period of time. We determine the transition probability based on distance frequency distributions. Our results show how the transition probability depends on the degree of movement autocorrelation, the returning angle at boundaries and the corridor width. In general, the transition probability is essentially determined by the degree of movement autocorrelation. The relative importance of both the returning angle at boundaries and the corridor width on the transition probability increases with higher degrees of movement autocorrelation. With increasing corridor width the transition probability increases asymptotically towards an upper level depending on movement velocity and time. Consequently, the corridor width has to be regarded as the main easily modified aspect for controlling transition probabilities. We use our findings to discuss the issue of an optimum corridor width. We take up the important effects of movement canalization within corridors and the way corridors influence both mortality en route and movement velocity. We compare the consequences of these effects on transition probabilities to situations without corridors in order to evaluate corridors in a more unbiased fashion.