Lutz Tischendorf

Can landscape indices predict ecological processes consistently

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 Morisitas 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.

How should we measure landscape 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.

Using patch isolation metrics to predict animal movement in binary landscapes

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.

Evaluation of patch isolation metrics in mosaic landscapes for specialist vs. generalist dispersers

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.

A transient, positive effect of habitat fragmentation on insect population densities

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.

Mechanisms Affecting Population Density in Fragmented Habitat

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.