Jochen A.G. Jaeger

Landscape division, splitting index, and effective mesh size : new measures of landscape fragmentation

Anthropogenic fragmentation of landscapes is known as a major reason for the loss of species in industrialized countries. Landscape fragmentation caused by roads, railway lines, extension of settlement areas, etc., further enhances the dispersion of pollutants and acoustic emissions and affects local climatic conditions, water balance, scenery, and land use. In this study, three new measures of fragmentation are introduced: degree of landscape division (D), splitting index (S), and effective mesh size (m). They characterize the anthropogenic penetration of landscapes from a geometric point of view and are calculated from the distribution function of the remaining patch sizes.First, D, S, and m are defined, their mathematical properties are discussed, and their reactions to the six fragmentation phases of perforation, incision, dissection, dissipation, shrinkage, and attrition are analysed. Then they are compared with five other known fragmentation indices with respect to nine suitability criteria such as intuitive interpretation, low sensivity to very small patches, monotonous reaction to different fragmentation phases, and detection of structural differences. Their ability to distinguish spatial patterns is illustrated by means of two series of model patterns. In particular, the effective mesh size (m), representing an intensive and area-proportionately additive measure, proves to be well suited for comparing the fragmentation of regions with differing total size.

The Rauischholzhausen Agenda for Road Ecology

Despite the documented negative effects of roads on wildlife, ecological research on road effects has had comparatively little influence on road planning decisions. We argue that road research would have a larger impact if researchers carefully considered the relevance of the research questions addressed and the inferential strength of the studies undertaken. At a workshop at the German castle of Rauischholzhausen we identified five particularly relevant questions, which we suggest provide the framework for a research agenda for road ecology: (1) Under what circumstances do roads affect population persistence? (2) What is the relative importance of road effects vs. other effects on population persistence? (3) Under what circumstances can road effects be mitigated? (4) What is the relative importance of the different mechanisms by which roads affect population persistence? (5) Under what circumstances do road networks affect population persistence at the landscape scale? We recommend experimental designs that maximize inferential strength, given existing constraints, and we provide hypothetical examples of such experiments for each of the five research questions. In general, manipulative experiments have higher inferential strength than do nonmanipulative experiments, and full before-after-control-impact designs are preferable to before-after or control-impact designs. Finally, we argue that both scientists and planners must be aware of the limits to inferential strength that exist for a given research question in a given situation. In particular, when the maximum inferential strength of any feasible design is low, decision makers must not demand stronger evidence before incorporating research results into the planning process, even though the level of uncertainty may be high.

DISPERSAL DISTANCE OF MAMMALS IS PROPORTIONAL TO HOME RANGE SIZE

We tested the prediction that home range area and dispersal distance in mammals are related when considered independently of body size. Regression of log- transformed data demonstrated that more variance in maximum dispersal distance could be explained by home range area (74%) than could be explained by body size (50%). The relationship between maximum dispersal distance and home range size was isometric (slope 5 1) when the square root of home range area (i.e., linear dimension of home range) was used. Thus, maximum dispersal distance was related to home range size by a single constant of 40. A linear relationship remained between these two variables after the effects of body size were removed (F 5 31.6, df 5 1, 32, P 5 3.2 3 10 26 , R 2 5 0.50). A similar isometric relationship with home range size was found for median dispersal distance (related by a multiple of 7). This isometric relationship between dispersal distance and home range size was tested using a second data source: maximum movements made by mammals after translocation, which also was linearly related to home range area (F 5 94.5, df 5 1, 23, P 5 1.3 3 10 29 , R 2 5 0.81). The slope and intercept of this relationship were not different from those of the relationship between maximum dispersal distance and home range area. We suggest that the vagility of mammals affected both home range size and dispersal distance (or movement after translocation) independently of body size, such that these movements could be predicted by home range area better than by body size alone. The resulting isometric relationship between dispersal distance and home range size has potential as a useful scaling rule for ecological practitioners.

Modification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem

Patch-based landscape metrics can be biased by the boundaries and the extent of a reporting unit if the boundaries fragment patches. We call this the “boundary problem”. The effective mesh size meff is a convenient method to quantify landscape fragmentation, that is based on the probability that two points chosen randomly in a region will be connected, e.g., not be separated by roads, railroads, or urban development. The cutting-out (CUT) procedure, used in the original computation of meff, suffers from the boundary problem because the boundaries of the reporting units are considered to be additional barriers. Therefore, meff will be underestimated, particularly if reporting units are embedded within the broader landscape. In this paper, we present a solution to overcome this limitation by a new method called “cross-boundary connections” (CBC) procedure. It attributes the connections between two points that are located in different reporting units to both reporting units. We systematically compare the CBC procedure to the CUT procedure and show that the boundary problem is intrinsic to the CUT procedure, while the CBC procedure is independent of the size and administrative boundaries of reporting units. In addition, we elucidate the superior performance of the new procedure in the case study of South Tyrol where meff is being used for sustainability reporting on the level of municipalities. The new CBC procedure eliminates the bias due to the boundaries and the size of reporting units in measuring landscape fragmentation through meff.

Reducing Moose–Vehicle Collisions through Salt Pool Removal and Displacement: an Agent-Based Modeling Approach

Between 1990 and 2002, more than 200 moose-vehicle collisions occurred each year in Quebec, including about 50/yr in the Laurentides Wildlife Reserve. One cause is the presence of roadside salt pools that attract moose near roads in the spring and summer. Using the computer simulation technique of agent-based modeling, this study investigated whether salt pool removal and displacement, i.e., a compensatory salt pool set up 100 to 1500 m away from the road shoulder, would reduce the number of moose–vehicle collisions. Moose road crossings were used as a proxy measure. A GPS (global positioning system) telemetry data set consisting of approximately 200,000 locations of 47 moose over 2 yr in the Laurentides Wildlife Reserve was used as an empirical basis for the model. Twelve moose were selected from this data set and programmed in the model to forage and travel in the study area. Five parameters with an additional application of stochasticity were used to determine moose movement between forest polygons. These included food quality; cover quality, i.e., protection from predators and thermal stress; proximity to salt pools; proximity to water; and slope. There was a significant reduction in road crossings when either all or two thirds of the roadside salt pools were removed, with and/or without salt pool displacement. With 100% salt pool removal, the reduction was greater (49%) without compensatory salt pools than with them (18%). When two thirds of the salt pools were removed, the reduction was the same with and without compensatory salt pools (16%). Although moose-vehicle collisions are not a significant mortality factor for the moose population in the Laurentides Wildlife Reserve, in areas with higher road densities, hunting pressure, and/or predator densities it could mean the difference between a stable and a declining population, and salt pool removal could be part of a good mitigation plan to halt population declines. This model can be used, with improvements such as spatial memory of salt pool locations and the addition of a road avoidance behavior, to assess the effectiveness of mitigation measures intended to reduce moose–vehicle collisions.

Assessing large-scale wildlife responses to human infrastructure development.

Significance Nature is increasingly threatened by rapid infrastructure expansion. For the first time, to our knowledge, we quantify the high pervasiveness of transportation infrastructure in all European countries. Unfortunately, spatial definition of the areas ecologically affected by infrastructure at large scales is complicated. Thus, we present a method for assessing the spatial extent of the impacts on birds and mammals at regional and national scales. As an illustration, its application to Spain shows that most of the country is affected, predicting moderate and severe declines for birds and mammals, respectively. The lack of areas that could be used as controls implies that scientists may no longer be able to measure the magnitude of road effects on wide-ranging mammals in most of Europe. Habitat loss and deterioration represent the main threats to wildlife species, and are closely linked to the expansion of roads and human settlements. Unfortunately, large-scale effects of these structures remain generally overlooked. Here, we analyzed the European transportation infrastructure network and found that 50% of the continent is within 1.5 km of transportation infrastructure. We present a method for assessing the impacts from infrastructure on wildlife, based on functional response curves describing density reductions in birds and mammals (e.g., road-effect zones), and apply it to Spain as a case study. The imprint of infrastructure extends over most of the country (55.5% in the case of birds and 97.9% for mammals), with moderate declines predicted for birds (22.6% of individuals) and severe declines predicted for mammals (46.6%). Despite certain limitations, we suggest the approach proposed is widely applicable to the evaluation of effects of planned infrastructure developments under multiple scenarios, and propose an internationally coordinated strategy to update and improve it in the future.

Experimental study designs to improve the evaluation of road mitigation measures for wildlife.

An experimental approach to road mitigation that maximizes inferential power is essential to ensure that mitigation is both ecologically-effective and cost-effective. Here, we set out the need for and standards of using an experimental approach to road mitigation, in order to improve knowledge of the influence of mitigation measures on wildlife populations. We point out two key areas that need to be considered when conducting mitigation experiments. First, researchers need to get involved at the earliest stage of the road or mitigation project to ensure the necessary planning and funds are available for conducting a high quality experiment. Second, experimentation will generate new knowledge about the parameters that influence mitigation effectiveness, which ultimately allows better prediction for future road mitigation projects. We identify seven key questions about mitigation structures (i.e., wildlife crossing structures and fencing) that remain largely or entirely unanswered at the population-level: (1) Does a given crossing structure work? What type and size of crossing structures should we use? (2) How many crossing structures should we build? (3) Is it more effective to install a small number of large-sized crossing structures or a large number of small-sized crossing structures? (4) How much barrier fencing is needed for a given length of road? (5) Do we need funnel fencing to lead animals to crossing structures, and how long does such fencing have to be? (6) How should we manage/manipulate the environment in the area around the crossing structures and fencing? (7) Where should we place crossing structures and barrier fencing? We provide experimental approaches to answering each of them using example Before-After-Control-Impact (BACI) study designs for two stages in the road/mitigation project where researchers may become involved: (1) at the beginning of a road/mitigation project, and (2) after the mitigation has been constructed; highlighting real case studies when available.

How effective is road mitigation at reducing road-kill? A meta-analysis.

Road traffic kills hundreds of millions of animals every year, posing a critical threat to the populations of many species. To address this problem there are more than forty types of road mitigation measures available that aim to reduce wildlife mortality on roads (road-kill). For road planners, deciding on what mitigation method to use has been problematic because there is little good information about the relative effectiveness of these measures in reducing road-kill, and the costs of these measures vary greatly. We conducted a meta-analysis using data from 50 studies that quantified the relationship between road-kill and a mitigation measure designed to reduce road-kill. Overall, mitigation measures reduce road-kill by 40% compared to controls. Fences, with or without crossing structures, reduce road-kill by 54%. We found no detectable effect on road-kill of crossing structures without fencing. We found that comparatively expensive mitigation measures reduce large mammal road-kill much more than inexpensive measures. For example, the combination of fencing and crossing structures led to an 83% reduction in road-kill of large mammals, compared to a 57% reduction for animal detection systems, and only a 1% for wildlife reflectors. We suggest that inexpensive measures such as reflectors should not be used until and unless their effectiveness is tested using a high-quality experimental approach. Our meta-analysis also highlights the fact that there are insufficient data to answer many of the most pressing questions that road planners ask about the effectiveness of road mitigation measures, such as whether other less common mitigation measures (e.g., measures to reduce traffic volume and/or speed) reduce road mortality, or to what extent the attributes of crossing structures and fences influence their effectiveness. To improve evaluations of mitigation effectiveness, studies should incorporate data collection before the mitigation is applied, and we recommend a minimum study duration of four years for Before-After, and a minimum of either four years or four sites for Before-After-Control-Impact designs.

Disentangling Woodland Caribou Movements in Response to Clearcuts and Roads across Temporal Scales

Although prey species typically respond to the most limiting factors at coarse spatiotemporal scales while addressing biological requirements at finer scales, such behaviour may become challenging for species inhabiting human altered landscapes. We investigated how woodland caribou, a threatened species inhabiting North-American boreal forests, modified their fine-scale movements when confronted with forest management features (i.e. clearcuts and roads). We used GPS telemetry data collected between 2004 and 2010 on 49 female caribou in a managed area in Québec, Canada. Movements were studied using a use – availability design contrasting observed steps (i.e. line connecting two consecutive locations) with random steps (i.e. proxy of immediate habitat availability). Although caribou mostly avoided disturbances, individuals nonetheless modulated their fine-scale response to disturbances on a daily and annual basis, potentially compromising between risk avoidance in periods of higher vulnerability (i.e. calving, early and late winter) during the day and foraging activities in periods of higher energy requirements (i.e. spring, summer and rut) during dusk/dawn and at night. The local context in which females moved was shown to influence their decision to cross clearcut edges and roads. Indeed, although females typically avoided crossing clearcut edges and roads at low densities, crossing rates were found to rapidly increase in greater disturbance densities. In some instance, however, females were less likely to cross edges and roads as densities increased. Females may then be trapped and forced to use disturbed habitats, known to be associated with higher predation risk. We believe that further increases in anthropogenic disturbances could exacerbate such behavioural responses and ultimately lead to population level consequences.

Analysis of uncertainty consideration in environmental assessment: an empirical study of Canadian EA practice

Identifying and communicating uncertainty is core to effective environmental assessment (EA). This study evaluates the extent to which uncertainties are considered and addressed in Canadian EA practice. We reviewed the environmental protection plans, follow-up programs, and panel reports (where applicable) of 12 EAs between 1995 and 2012. The types of uncertainties and levels of disclosure varied greatly. When uncertainties were acknowledged, practitioners adopted five different approaches to address them. However, uncertainties were never discussed or addressed in depth. We found a lack of suitable terminology and consistency in how uncertainties are disclosed, reflecting the need for explicit guidance, and we present recommendations for improvement. Canadian Environmental Impact Statements are not as transparent with respect to uncertainties as they should be, and uncertainties in EA need to be better considered and communicated.