The transiogram as a graphic metric for characterizing the spatial patterns of landscapes

Context

Landscape metrics play an important role in measurement, analysis, and interpretation of spatial patterns of landscapes. There are a variety of different landscape metrics widely used in landscape ecology. However, existing landscape metrics are mostly non-graphic and single-value indices, which may not be sufficient to describe the complex spatial correlation and interclass relationships of various landscapes. As a transition probability diagram over the lag distance, the transiogram, which emerged in recent years, essentially provides a new graphic metric for measuring and visualizing the auto and cross correlations of landscape categories.

Objectives

To explore the capability of the transiogram for measuring spatial patterns of categorical landscape maps and compare it with existing landscape metrics.

Methods

Sixteen commonly-used landscape metrics and transiograms (including auto- and cross-transiograms) were estimated and compared for land cover/use classes in four areas with different landscapes.

Results

Results show that (1) these transiograms can provide visual information about the proportions, aggregation levels, interclass adjacencies, and intra-class/interclass correlation ranges of landscape classes; (2) sills and auto-correlation ranges of transiograms are correlated with the values of some landscape metrics; and (3) the peak height ratios of idealized transiograms can effectively represent the juxtaposition strength of neighboring class pairs.

Conclusions

The transiogram can be an effective graphic metric for characterizing the auto-correlation of single classes (through auto-transiograms) and the complex interclass relationships, such as interdependency and juxtaposition, between different landscape classes (through cross-transiograms).

     

Integrating landscape ecology into landscape practice in Central African Rainforests

Context

We describe how large landscape-scale conservation initiatives involving local communities, NGOs and resource managers have engaged with landscape scientists with the goal of achieving landscape sustainability. We focus on two landscapes where local people, practitioners and landscape ecologists have co-produced knowledge to design conservation interventions.

Objective

We seek to understand how landscape ecology can engage with practical landscape management to contribute to managing landscapes sustainably.

Methods

We focus on two large tropical landscapes: the Sangha Tri-National landscape (Cameroon, Republic of Congo and the Central African Republic) and the Batéké-Léfini Landscape (Gabon and Republic of Congo). We evaluate (1) a participatory method used in the Sangha Tri-National landscape that embeds interdisciplinary researchers and practitioners within a landscape to apply transdisciplinary learning to landscape conservation and (2) a participatory landscape zoning method where interdisciplinary teams of conservation practitioners analyse local land and resource use in the Batéké-Léfini landscape.

Results

We find that landscape ecology’s tradition of understanding the historical context of resource use can inform landscape conservation practice and natural resource mapping. We also find that the Sangha Group provides an example for landscape ecology on how to integrate local people and their knowledge to better understand and influence landscape processes.

Conclusions

Place-based engagement as well as the uptake of co-produced knowledge by policy makers are key in enabling sustainable landscapes. Success occurs when researchers, local communities and resource managers engage directly with landscape processes.

     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Sensitivity and effectiveness and of landscape metric scalograms in determining the characteristic scale of a hierarchically structured landscape

Landscape metric scalograms (the response curves of landscape metrics to changing grain size) have been used to illustrate the scale effects of metrics for real landscapes. However, whether they detect the characteristic scale of hierarchically structured landscapes remains uncertain. To address this question, the scalograms of 26 class-level metrics were systematically examined for a simple random landscape, seven hierarchical neutral landscapes, and the real landscape of the Xilin River Basin of Inner Mongolia, China. The results show that when the fraction of the focal patch type (P) is below a critical value (P _c), most metric scalograms are sensitive to change in single-scale and lower-level hierarchical structure and insensitive to change in higher-level hierarchical structure. The scalograms of only a few metrics measuring spatial aggregation and connectedness are sensitive to change in intermediate-level hierarchical structure. Most metric scalograms explicitly identify the characteristic scale of a single-scale landscape and fine or intermediate characteristic scales of a multi-scale landscape for both simulated and real landscapes. When P exceeds P _c, only some metrics detect scale and change in structure. The scalograms of total class area and Euclidean nearest-neighbor distance cannot detect scale or change in structure in either case. Landscape metric scalograms are useful for addressing scale issues, including illustrating the scale effects of spatial patterns, detecting multi-scale patterns, and developing possible scaling relations.

     

Surface metrics: an alternative to patch metrics for the quantification of landscape structure

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface metrology offers a variety of surface metrics for quantifying landscape gradients, yet these metrics are largely unknown and/or unused by landscape ecologists. In this paper, we describe a suite of surface metrics with potential for landscape ecological application. We assessed the redundancy among metrics and sought to find groups of similarly behaved metrics by examining metric performance across 264 sample landscapes in western Turkey. For comparative purposes and to evaluate the robustness of the observed patterns, we examined 16 different patch mosaic models and 18 different landscape gradient models of landscape structure. Surface metrics were highly redundant, but less so than patch metrics, and consistently aggregated into four cohesive clusters of similarly behaved metrics representing surface roughness, shape of the surface height distribution, and angular and radial surface texture. While the surface roughness metrics have strong analogs among the patch metrics, the other surface components are largely unique to landscape gradients. We contend that the surface properties we identified are nearly universal and have potential to offer new insights into landscape pattern–process relationships. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Spectral representation of neutral landscapes

Pattern in ecological landscapes is often the result of different processes operating at different scales. Neutral landscape models were introduced in landscape ecology to differentiate patterns that are the result of simple random processes from patterns that arise from more complex ecological processes. Recent studies have used increasingly complex neutral models that incorporate contagion and other constraints on random patterns, as well as using neutral landscapes as input to spatial simulation models. Here, I consider a common mathematical framework based on spectral transforms that represents all neutral landscape models in terms of sets of spectral basis functions. Fractal and multi-fractal models are considered, as well as models with multiple scaling regions and anisotropy. All of the models considered are shown to be variations on a basic theme: a scaling relation between frequency and amplitude of spectral components. Two example landscapes examined showed long-range correlations (distances up to 1000 km) consistent with fractal scaling.     

Human appropriated net primary productivity as a metric for land use planning: a case study in the US Great Lakes region

Context

Human appropriation of net primary productivity (HANPP) is employed as a measure of human pressures on biodiversity, though largely at global and national scales rather than landscape to regional scales where many conservation decisions take place. Though gaining in familiarity, HANPP is not widely utilized by conservation professionals.

Objectives

This study, encompassing the US side of the Great Lakes basin, examines how regional distributions of HANPP relate to landscape-based biodiversity proxy metrics used by conservation professionals. Our objectives were (1) to quantify the HANPP of managed lands at the county scale; and (2) to assess spatial patterns of HANPP in comparison to landscape diversity and local habitat connectedness to determine if the metric can provide useful information to conservation professionals.

Methods

We aggregated forest and cropland NPP data between 2005 and 2015 and coupled it with previously published potential vegetation maps to quantify the HANPP of each county in the study region. We mapped the outputs at 500 m resolution to analyze spatial relationships between HANPP and landscape metrics of biodiversity potential.

Results

Area-weighted HANPP across our study region averaged 45% of NPP, down to 4.9% in forest-dominated counties. Greater HANPP correlated with reduced landscape diversity (p?<?0.001, r²?=?0.28) and reduced local habitat connectedness (p?<?0.001, r²?=?0.36).

Conclusion

HANPP could be used as an additional tool for conservation professionals during regional-scale land use planning or conservation decision-making, particularly in mixed-use landscapes that both support important biodiversity and have high levels of primary production harvest.

     

Surface metrics for landscape ecology: a comparison of landscape models across ecoregions and scales

Context

The patch-mosaic model is lauded for its conceptual simplicity and ease with which conventional landscape metrics can be computed from categorical maps, yet many argue it is inconsistent with ecological theory. Gradient surface models (GSMs) are an alternative for representing landscapes, but adoption of surface metrics for analyzing spatial patterns in GSMs is hindered by several factors including a lack of meaningful interpretations.

Objectives

We investigate the performance and applicability of surface metrics across a range of ecoregions and scales to strengthen theoretical foundations for their adoption in landscape ecology.

Methods

We examine metric clustering across scales and ecoregions, test correlations with patch-based metrics, and provide ecological interpretations for a variety of surface metrics with respect to forest cover to support the basis for selecting surface metrics for ecological analyses.

Results

We identify several factors complicating the interpretation of surface metrics from a landscape perspective. First, not all surface metrics are appropriate for landscape analyses. Second, true analogs between surface metrics and patch-based, landscape metrics are rare. Researchers should focus instead on how surface measures can uniquely measure spatial patterns. Lastly, scale dependencies exist for surface metrics, but relationships between metrics do not appear to change considerably with scale.

Conclusions

Incorporating gradient surfaces into landscape ecological analyses is challenging, and many surface metrics may not have patch analogs or be ecologically relevant. For this reason, surface metrics should be considered in terms of the set of pattern elements they represent that can then be linked to landscape characteristics.

     

Habitat suitability and connectivity modeling reveal priority areas for Indiana bat (Myotis sodalis) conservation in a complex habitat mosaic

Context

Conservation for the Indiana bat (Myotis sodalis), a federally endangered species in the United States of America, is typically focused on local maternity sites; however, the species is a regional migrant, interacting with the environment at multiple spatial scales. Hierarchical levels of management may be necessary, but we have limited knowledge of landscape-level ecology, distribution, and connectivity of suitable areas in complex landscapes.

Objectives

We sought to (1) identify factors influencing M. sodalis maternity colony distribution in a mosaic landscape, (2) map suitable maternity habitat, and (3) quantify connectivity importance of patches to direct conservation action.

Methods

Using 3 decades of occurrence data, we tested a priori, hypothesis-driven habitat suitability models. We mapped suitable areas and quantified connectivity importance of habitat patches with probabilistic habitat availability metrics.

Results

Factors improving landscape-scale suitability included limited agriculture, more forest cover, forest edge, proximity to medium-sized water bodies, lower elevations, and limited urban development. Areas closer to hibernacula and rivers were suitable. Binary maps showed that 30% of the study area was suitable for M. sodalis and 29% was important for connectivity. Most suitable patches were important for intra-patch connectivity and far fewer contributed to inter-patch connectivity.

Conclusions

While simple models may be effective for small, homogenous landscapes, complex models are needed to explain habitat suitability in large, mixed landscapes. Suitability modeling identified factors that made sites attractive as maternity areas. Connectivity analysis improved our understanding of important areas for bats and prioritized areas to target for restoration.

     

The Eco-field Hypothesis: Toward a Cognitive Landscape

Cognition is recognized as an essential component of the living strategies of organisms and the use of cognitive approaches based on an organismic-centered-view is discussed as a strategy to aid the advancement of landscape ecology to a more independent scientific discipline. The incorporation of the theory of information, the theory of meaning and the Umwelt, and the biosemiotic models into the landscape ecology framework is described as the necessary step to create a common paradigmatic background and operational tools to develop basis for a cognitive landscape ecology. Three cognitive landscapes (neutrality-based landscape, individual-based landscape and observer-based landscape) have been described as the result of distinctive mechanisms to extract information from a cognitive matrix based on a growing literature of (bio)semiotic exchange. The eco-field hypothesis is presented as a new possibility to describe landscape processes according to an organismic-centered-view. The eco-field is defined as a spatial configuration carrier of a specific meaning perceived when a specific living function is activated. A species-specific cognitive landscape is composed of all the spatial configurations involved for all the living functions for a particular organism. Eco-field hypothesis offers a detailed vision of (habitat) environmental requirements and creates a novel conceptual bridge between niche, habitat, Umwelt and the methodological approaches of spatial ecology. Finally the eco-field hypothesis promises a new testing ground for experimental investigations in landscape ecology and in related disciplines including environmental psychology, cognitive ethology, cultural ecology, landscape aesthetics, design and planning.     

Aggregation-based method for computing absolute Boltzmann entropy of landscape gradient with full thermodynamic consistency

Context

The second law of thermodynamics is a central organizing principle of nature, whose core concept, Boltzmann entropy, is fundamentally important in landscape ecology research. However, the use of this entropy has remained at a conceptual level in landscape ecology for one and a half centuries. It was not until very recently that methods were developed for computing the Boltzmann entropy of landscape gradients and mosaics.

Objectives

The aim of this study was to examine the computational method (i.e., resampling-based method) for landscape gradients. The first objective was to validate whether the Boltzmann entropy computed using this method was thermodynamically consistent (i.e., consistent with statistical thermodynamics). The second objective was to propose a different method for computing thermodynamically consistent entropy.

Methods

A kinetic-theory-based approach was proposed for testing the thermodynamic consistency of entropy. This approach was applied to both relative and absolute Boltzmann entropies by the resampling-based method, revealing that the absolute Boltzmann entropy is only partly consistent. Hypothesis-driven experiments were designed to determine the cause.

Results

The cause was demonstrated to be the generalization technique for generating the macrostate of a landscape gradient, which is called resampling. A different computational method was developed on the basis of an alternative technique (i.e., aggregation).

Conclusions

Validation of its thermodynamic consistency is necessary even if a “thermodynamic” entropy is computed strictly according to the formula. The entropy computed using the aggregation-based method passed the validation and is recommended to be used in linking landscape ecological processes with statistical thermodynamics.

     

Changing patterns in the urbanized countryside of Western Europe

Urbanization refers to the complex interaction of different processes which transform landscapes formed by rural life styles into urban like ones. Urbanization causes profound changes in the ecological functioning of the landscape and gradually results in a changing spatial structure, i.e. forms new landscape patterns. The existing cities and urban network form the framework for this change, which is affecting increasingly larger areas in the countryside. Urbanization is mainly studied from social and economical viewpoints. Urban planners think about optimization of the land use and about aesthetics when reshaping the environment. Landscape ecology is lacking in urban planning because of different goals and concepts, but mostly because of missing significant information about these highly dynamical landscapes.     

Predicting the assembly of novel communities in urban ecosystems

Context

Ecological communities in urban ecosystems are assembled through ecological processes, such as species interactions, dispersal, and environmental filtering, but also through human factors that create and modify the landscape. These complex interactions make it difficult to untangle the relationships between social–ecological dynamics and urban biodiversity.

Objectives

As a result, there has been a call for research to address how human activities influence the processes by which ecological communities are structured in urban ecosystems. We address this research challenge using core concepts from landscape ecology to develop a framework that links social-ecological dynamics to ecological communities using the metacommunity perspective.

Methods

The metacommunity perspective is a useful framework to explore the assembly of novel communities because it distinguishes between the effects of local environmental heterogeneity and regional spatial processes in structuring ecological communities. Both are shaped by social–ecological dynamics in urban ecosystems.

Results

In this paper, we define social, environmental, and spatial processes that structure metacommunities, and ultimately biodiversity, in cities. We then address how our framework could be applied in urban ecosystem research to understand multi-scalar biodiversity patterns.

Conclusions

Our framework provides a theoretical and empirical foundation for transdisciplinary research to examine how social-ecological dynamics mediate the assembly of novel communities in urban ecosystems.

     

Characterizing connectivity relationships in freshwaters using patch-based graphs

Spatial graphs in landscape ecology and conservation have emerged recently as a powerful methodology to model patterns in the topology and connectivity of habitat patches (structural connectivity) and the movement of genes, individuals or populations among these patches (potential functional connectivity). Most spatial graph’s applications to date have been in the terrestrial realm, whereas the use of spatially explicit graph-based methods in the freshwater sciences has lagged far behind. Although at first patch-based spatial graphs were not considered suitable for representing the branching network of riverine landscapes, here we argue that the application of graphs can be a useful tool for quantifying habitat connectivity of freshwater ecosystems. In this review we provide an overview of the potential of patch-based spatial graphs in freshwater ecology and conservation, and present a conceptual framework for the topological analysis of stream networks (i.e., riverscape graphs) from a hierarchical patch-based context. By highlighting the potential application of graph theory in freshwater sciences we hope to illustrate the generality of spatial network analyses in landscape ecology and conservation.     

Influence of high-resolution data on the assessment of forest fragmentation

Context

Remote sensing has been a foundation of landscape ecology. The spatial resolution (pixel size) of remotely sensed land cover products has improved since the introduction of landscape ecology in the United States. Because patterns depend on spatial resolution, emerging improvements in the spatial resolution of land cover may lead to new insights about the scaling of landscape patterns.

Objective

We compared forest fragmentation measures derived from very high resolution (1 m²) data with the same measures derived from the commonly used (30 m?×??30 m; 900 m²) Landsat-based data.

Methods

We applied area-density scaling to binary (forest; non-forest) maps for both sources to derive source-specific estimates of dominant (density ≥?60%), interior (≥?90%), and intact (100%) forest.

Results

Switching from low- to high-resolution data produced statistical and geographic shifts in forest spatial patterns. Forest and non-forest features that were “invisible” at low resolution but identifiable at high resolution resulted in higher estimates of dominant and interior forest but lower estimates of intact forest from the high-resolution source. Overall, the high-resolution data detected more forest that was more contagiously distributed even at larger spatial scales.

Conclusion

We anticipate that improvements in the spatial resolution of remotely sensed land cover products will advance landscape ecology through re-interpretations of patterns and scaling, by fostering new landscape pattern measurements, and by testing new spatial pattern-ecological process hypotheses.

     

The Lorenz curve: a suitable framework to define satisfactory indices of landscape composition

Context

Patch diversity, evenness and dominance are important metrics of landscape composition. They have been traditionally measured using indices based on Shannon’s information entropy (H) and Simpson’s concentration statistic (λ).

Objectives

The main objectives of this study are: (1) to show that the Lorenz curve is an appropriate framework to understand and measure patch dominance, evenness and diversity; (2) to show that Lorenz-compatible indices have better mathematical behavior than H-based and λ-based indices.

Methods

Thirteen different hypothetical landscapes were created to assess landscape composition with the Lorenz curve and to compare the mathematical behavior of Lorenz-compatible indices with that of H-based and λ-based indices.

Results

The Lorenz curve is a suitable framework to understand and measure patch dominance, evenness and diversity due to four relevant equivalences: (1) patch dominance?=?the separation of the Lorenz curve from the 45-degree line of perfect patch evenness; (2) patch evenness?=?1 ? patch dominance; (3) patch diversity (eliminated by patch dominance)?=?patch richness?×?patch dominance; (4) patch diversity (preserved by patch evenness)?=?patch richness?×?patch evenness. Accordingly, patch diversity/patch richness?=?1???patch dominance and land-cover concentration?=?1/patch diversity.

Conclusions

Lorenz-compatible indices have better mathematical behavior than H-based and λ-based indices, exhibiting greater coherence and objectivity when measuring patch dominance, evenness and diversity.

     

Culture and changing landscape structure

Culture changes landscapes and culture is embodied by landscapes. Both aspects of this dynamic are encompassed by landscape ecology, but neither has been examined sufficiently to produce cultural theory within the field. This paper describes four broad cultural principles for landscape ecology, under which more precise principles might be organized. A central underlying premise is that culture and landscape interact in a feedback loop in which culture structures landscapes and landscapes inculcate culture. The following broad principles are proposed:

1. Human landscape perception, cognition, and values directly affect the landscape and are affected by the landscape.
2. Cultural conventions powerfully influence landscape pattern in both inhabited and apparently natural landscapes.
3. Cultural concepts of nature are different from scientific concepts of ecological function.
4. The appearance of landscapes communicates cultural values.

Both the study of landscapes at a human scale and experimentation with possible landscapes, landscape patterns invented to accommodate ecological function, are recommended as means of achieving more precise cultural principles.