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).

     

Information theory as a consistent framework for quantification and classification of landscape patterns

Context

Quantitative grouping of similar landscape patterns is an important part of landscape ecology due to the relationship between a pattern and an underlying ecological process. One of the priorities in landscape ecology is a development of the theoretically consistent framework for quantifying, ordering and classifying landscape patterns.

Objective

To demonstrate that the information theory as applied to a bivariate random variable provides a consistent framework for quantifying, ordering, and classifying landscape patterns.

Methods

After presenting information theory in the context of landscapes, information-theoretical metrics were calculated for an exemplar set of landscapes embodying all feasible configurations of land cover patterns. Sequences and 2D parametrization of patterns in this set were performed to demonstrate the feasibility of information theory for the analysis of landscape patterns.

Results

Universal classification of landscape into pattern configuration types was achieved by transforming landscapes into a 2D space of weakly correlated information-theoretical metrics. An ordering of landscapes by any single metric cannot produce a sequence of continuously changing patterns. In real-life patterns, diversity induces complexity—increasingly diverse patterns are increasingly complex.

Conclusions

Information theory provides a consistent, theory-based framework for the analysis of landscape patterns. Information-theoretical parametrization of landscapes offers a method for their classification.

     

Riparian influences on stream fish assemblage structure in urbanizing streams

We assessed the influence of land cover at multiple spatial extents on fish assemblage integrity, and the degree to which riparian forests can mitigate the negative effects of catchment urbanization on stream fish assemblages. Riparian cover (urban, forest, and agriculture) was determined within 30 m buffers at longitudinal distances of 200 m, 1 km, and the entire network upstream of 59 non-nested fish sampling locations. Catchment and riparian land cover within the upstream network were highly correlated, so we were unable to distinguish between those variables. Most fish assemblage variables were related to % forest and % urban land cover, with the strongest relations at the largest spatial extent of land cover (catchment), followed by riparian land cover in the 1-km and 200-m reach, respectively. For fish variables related to urban land cover in the catchment, we asked whether the influence of riparian land cover on fish assemblages was dependent on the amount of urban development in the catchment. Several fish assemblage metrics (endemic richness, endemic:cosmopolitan abundance, insectivorous cyprinid richness and abundance, and fluvial specialist richness) were all best predicted by single variable models with % urban land cover. However, endemic:cosmopolitan richness, cosmopolitan abundance, and lentic tolerant abundance were related to % forest cover in the 1-km stream reach, but only in streams that had <15% catchment urban land cover. In these cases, catchment urbanization overwhelmed the potential mitigating effects of riparian forests on stream fishes. Together, these results suggest that catchment land cover is an important driver of fish assemblages in urbanizing catchments, and riparian forests are important but not sufficient for protecting stream ecosystems from the impacts of high levels of urbanization.     

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.

     

Spatial relationship between human population density, land use intensity and biodiversity in the Czech Republic

We test a hypothesis about the spatial coincidence of human population density and species richness, and analyze effects of land conversion and ecosystem use on species richness and landscape diversity in human dominated Central European country, the Czech Republic. We calculated fraction of aboveground net primary productivity appropriated by humans and compared it to the species richness of vertebrate, invertebrate and plant groups and to landscape diversity index in 560 mapping grid squares with grid size approximately 130?km². Spatial correlations and regressions were established between human population density, appropriation of net primary production, land cover and biodiversity. We found positive spatial coincidence between human population density and species richness. Although the amount of net primary production was not related to species richness in general, we found significant negative spatial relationship between ecosystem use intensity and landscape diversity. As the area of the Czech Republic exhibits relatively high land use intensities, spatial patterns of human impacts have important implications for land management and biodiversity conservation in a cultural landscape.     

Landscape influences on stream biotic integrity assessed at multiple spatial scales

The biological integrity of stream ecosystems depends critically on human activities that affect land use/cover along stream margins and possibly throughout the catchment. We evaluated stream condition using an Index of Biotic Integrity (IBI) and a habitat index (HI), and compared these measures to landscape and riparian conditions assessed at different spatial scales in a largely agricultural Midwestern watershed. Our goal was to determine whether land use/cover was an effective predictor of stream integrity, and if so, at what spatial scale. Twenty-three sites in first-through third-order headwater streams were surveyed by electrofishing and site IBIs were calculated based on ten metrics of the fish collection. Habitat features were characterized through field observation, and site HIs calculated from nine instream and bank metrics. Field surveys, aerial photograph interpretation, and geographic information system (GIS) analyses provided assessments of forested land and other vegetation covers at the local, reach, and regional (catchment) scales. The range of conditions among the 23 sites varied from poor to very good based on IBI and HI scores, and habitat and fish assemblage measures were highly correlated. Stream biotic integrity and habitat quality were negatively correlated with the extent of agriculture and positively correlated with extent of wetlands and forest. Correlations were strongest at the catchment scale (IBI with % area as agriculture, r²=0.50, HI with agriculture, r²=0.76), and tended to become weak and non-significant at local scales. Local riparian vegetation was a weak secondary predictor of stream integrity. In this watershed, regional land use is the primary determinant of stream conditions, able to overwhelm the ability of local site vegetation to support high-quality habitat and biotic communities.     

The relative influence of catchment and site variables on fish and macroinvertebrate richness in cerrado biome streams

Landscape and site-scale data analyses aid the interpretation of biological data and thereby help us develop more cost-effective natural resource management strategies. Our study focused on environmental influences on stream assemblages and we evaluated how three classes of environmental variables (geophysical landscape, land use and cover, and site habitat), influence fish and macroinvertebrate assemblage richness in the Brazilian Cerrado biome. We analyzed our data through use of multiple linear regression (MLR) models using the three classes of predictor variables alone and in combination. The four MLR models explained dissimilar amounts of benthic macroinvertebrate taxa richness (geophysical landscape R ² ≈ 35 %, land use and cover R ² ≈ 28 %, site habitat R ² ≈ 36 %, and combined R ² ≈ 51 %). For fish assemblages, geophysical landscape, land use and cover, site habitat, and combined models explained R ² ≈ 28 %, R ² ≈ 10 %, R ² ≈ 31 %, and R ² ≈ 47 % of the variability in fish species richness, respectively. We conclude that (1) environmental variables differed in the degree to which they explain assemblage richness, (2) the amounts of variance in assemblage richness explained by geophysical landscape and site habitat were similar, (3) the variables explained more variability in macroinvertebrate taxa richness than in fish species richness, and (4) all three classes of environmental variables studied were useful for explaining assemblage richness in Cerrado headwater streams. These results help us to understand the drivers of assemblage patterns at regional scales in tropical areas.     

Land cover and climate changes drive regionally heterogeneous increases in US insecticide use

Context

Global environmental change is expected to dramatically affect agricultural crop production through a myriad of pathways. One important and thus far poorly understood impact is the effect of land cover and climate change on agricultural insect pests and insecticides.

Objectives

Here we address the following three questions: (1) how do landscape complexity and weather influence present-day insecticide use, (2) how will changing landscape characteristics and changing climate influence future insecticide use, and how do these effects manifest for different climate and land cover projections? and (3) what are the most important drivers of changing insecticide use?

Methods

We use panel models applied to county-level agriculture, land cover, and weather data in the US to understand how landscape composition and configuration, weather, and farm characteristics impact present-day insecticide use. We then leverage forecasted changes in land cover and climate under different future scenarios to predict insecticide use in 2050.

Results

We find different future scenarios—through modifications in both landscape and climate conditions—increase the amount of area treated by ~ 4–20% relative to 2017, with regionally heterogeneous impacts. Of note, we report large farms are more influential than large crop patches and increased winter minimum temperature is more influential than increased summer maximum temperature. However, our results suggest the most important determinants of future insecticide use are crop composition and farm size, variables for which future forecasts are sparse.

Conclusions

Both landscape and climate change are expected to increase future insecticide use. Yet, crop composition and farm size are highly influential, data-poor variables. Better understanding of future crop composition and farm economics is necessary to effectively predict and mitigate increases in pesticide use.

     

Does catchment geodiversity foster stream biodiversity?

Context

One approach to maintain the resilience of biotic communities is to protect the variability of abiotic characteristics of Earth’s surface, i.e. geodiversity. In terrestrial environments, the relationship between geodiversity and biodiversity is well recognized. In streams, the abiotic properties of upstream catchments influence stream communities, but the relationships between catchment geodiversity and aquatic biodiversity have not been previously tested.

Objectives

The aim was to compare the effects of local environmental and catchment variables on stream biodiversity. We specifically explored the usefulness of catchment geodiversity in explaining the species richness on stream macroinvertebrate, diatom and bacterial communities.

Methods

We used 3 geodiversity variables, 2 land use variables and 4 local habitat variables to examine species richness variation across 88 stream sites in western Finland. We used boosted regression trees to explore the effects of geodiversity and other variables on biodiversity.

Results

We detected a clear effect of catchment geodiversity on species richness, although the traditional local habitat and land use variables were the strongest predictors. Especially soil-type richness appeared as an important factor for species richness. While variables related to stream size were the most important for macroinvertebrate richness and partly for bacterial richness, the importance of water chemistry and land use for diatom richness was notable.

Conclusions

In addition to traditional environmental variables, geodiversity may affect species richness variation in streams, for example through changes in water chemistry. Geodiversity information could be used as a proxy for predicting stream species richness and offers a supplementary tool for conservation efforts.

     

Improved methods for quantifying potential nutrient interception by riparian buffers

Efforts to quantify the effects of riparian buffers on watershed nutrient discharges have been confounded by a commonly used analysis, which estimates buffer potential as the percentage of forest or wetland within a fixed distance of streams. Effective landscape metrics must instead be developed based on a clear conceptual model and quantified at the appropriate spatial scale. We develop new metrics for riparian buffers in two stages of increasing functional specificity to ask: (1) Which riparian metrics are more distinct from measures of whole watershed land cover? (2) Do functional riparian metrics provide different information than fixed-distance metrics? (3) How do these patterns vary within and among different physiographic settings? Using publicly available geographic data, we studied 503 watersheds in four different physiographic provinces of the Chesapeake Bay Drainage. In addition to traditional fixed-distance measures, we calculated mean buffer width, gap frequency, and measures of variation in buffer width using both “unconstrained” metrics and “flow-path” metrics constrained by surface topography. There were distinct patterns of relationship between watershed and near-stream land cover in each physiographic province and strong correlations with watershed land cover confounded fixed-distance metrics. Flow-path metrics were more independent of watershed land cover than either fixed-distance or unconstrained measures, but both functional metrics provided greater detail, interpretability, and flexibility than the fixed-distance approach. Potential applications of the new metrics include exploring the potential for land cover patterns to influence water quality, accounting for buffers in statistical nutrient models, quantifying spatial patterns for process-based modeling, and targeting management actions such as buffer restoration.     

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.

     

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.

     

Ecosystem services as the products of land system dynamics: lessons from a longitudinal study of coupled human–environment systems

Context

We address understanding of whole-system and landscape-based approaches to the ecosystem services framework by considering the supply of provisioning services and the dynamics of agricultural land use in Scotland between 1940 and 2016.

Objectives

To characterise and understand the dynamics of change in provisioning services from agriculture in Scotland over the period 1940–2016. To identify ways in which funds of capitals and flows of inputs and output ecosystem goods are linked to land management practices and policies at a national scale.

Methods

Data describing agricultural land use, production, financial and energy inputs and outputs, and drivers of change in land use in Scotland are analysed with an accounting framework that links funds of natural, human, physical and financial capital, with flows of goods and services. Flow–fund ratios are used as benchmarks of system performance and dynamics.

Results

Scotland’s agriculture has modernised since 1940 and become more efficient in conversion of resources, with a consequent increase in delivery of provisioning goods and services. Although the energy ratio, and flow of goods per unit hectare and per unit labour have increased, the inputs necessary to maintain those flows of ecosystem goods are also increasing, even as their relative economic costs decrease. Increases in use of fertiliser suggests that production from the soil, as a natural capital fund, is not being conserved without a large, and increasing, input. Analysis of the complexity of the coupled agricultural land system also suggests that land management rather than biodiversity is a necessary subject for evaluation of provisioning services from agriculture. Understanding of ecosystem services based on accounts that integrate inputs, outputs and flows from funds of natural, human, social, financial and physical capitals, provides a process-based foundation for improved understanding of ecosystem services and human–environmental relationships.

Conclusions

Adopting an accounting approach for understanding the role of agricultural land use for supply of provisioning services, and particularly examining a long time-series of accounts, enables understanding of land changes and underlying drivers, as well as the contribution of cultural and other aspects of human systems coupled with environment systems. Accounting for ecosystem services using costs as well as benefits, and use of metrics beyond financial benefit, supports debate and evaluation of trade-offs between services and has direct relevance for decision- and policy-making.

     

Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel

The distributions of freshwater mussels are controlled by landscape factors operating at multiple spatial scales. Changes in land use/land cover (LULC) have been implicated in severe population declines and range contractions of freshwater mussels across North America. Despite widespread recognition of multiscale influences few studies have addressed these issues when developing distribution models. Furthermore, most studies have disregarded the role of landscape pattern in regulating aquatic species distributions, focusing only on landscape composition. In this study, the distribution of Rabbitsfoot (Quadrula cylindrica) in the upper Green River system (Ohio River drainage) is modeled with environmental variables from multiple scales: subcatchment, riparian buffer, and reach buffer. Four types of landscape environment metrics are used, including: LULC pattern, LULC composition, soil composition, and geology composition. The study shows that LULC pattern metrics are very useful in modeling the distribution of Rabbitsfoot. Together with LULC compositional metrics, pattern metrics permit a more detailed analysis of functional linkages between aquatic species distributions and landscape structure. Moreover, the inclusion of multiple spatial scales is necessary to accurately model the hierarchical processes in stream systems. Geomorphic features play important roles in regulating species distributions at intermediate and large scales while LULC variables appear more influential at proximal scales.     

Spatial patterns of plant invasiveness in a riparian corridor

Analysis of landscape-scale patterns of plant invasiveness can assist in interpreting spatial patterns of plant species richness. We investigated downstream variation in plant invasiveness in the riparian corridor of the free-flowing Vindel River in northern Sweden by introducing seeds of an alien species, Helianthus annuus, in 0.25 m² plots of natural vegetation from mountain headwaters to the coast and found a significant downstream pattern with middle reaches having the highest invasiveness. We related invasiveness to species richness, both on a reach scale (200-m long stretches of riverbank encompassing the experimental plots) and on the scale of experimental plots. We found no significant correlation between plant invasiveness and species richness, neither at the reach nor at the plot scale. The number of available soil substrates shows a significant positive quadratic relationship with location along the river and substrate fineness shows a near significant negative quadratic relationship with location along the river, with middle reaches having coarser substrates. Several studies have shown that plant species richness in riparian corridors often exhibits a quadratic pattern with highest species richness in the middle reaches of a river, similar to the pattern we found for invasiveness. Although species richness per se might not be a primary factor for invasibility, the same habitat conditions as those supporting plant species richness, can help in explaining large-scale patterns of plant invasion in riparian zones.     

Saproxylic species are linked to the amount and isolation of dead wood across spatial scales in a beech forest

Context

Dead wood is a key habitat for saproxylic species, which are often used as indicators of habitat quality in forests. Understanding how the amount and spatial distribution of dead wood in the landscape affects saproxylic communities is therefore important for maintaining high forest biodiversity.

Objectives

We investigated effects of the amount and isolation of dead wood on the alpha and beta diversity of four saproxylic species groups, with a focus on how the spatial scale influences results.

Methods

We inventoried saproxylic beetles, wood-inhabiting fungi, and epixylic bryophytes and lichens on 62 plots in the Sihlwald forest reserve in Switzerland. We used GLMs to relate plot-level species richness to dead wood amount and isolation on spatial scales of 20–200 m radius. Further, we used GDMs to determine how dead wood amount and isolation affected beta diversity.

Results

A larger amount of dead wood increased beetle richness on all spatial scales, while isolation had no effect. For fungi, bryophytes and lichens this was only true on small spatial scales. On larger scales of our study, dead wood amount had no effect, while greater isolation decreased species richness. Further, we found no strong consistent patterns explaining beta diversity.

Conclusions

Our multi-taxon study shows that habitat amount and isolation can strongly differ in the spatial scale on which they influence local species richness. To generally support the species richness of different saproxylic groups, dead wood must primarily be available in large amounts but should also be evenly distributed because negative effects of isolation already showed at scales under 100 m.

     

Landscape characteristics affecting streams in urbanizing regions of the Delaware River Basin (New Jersey,New York,and Pennsylvania,U.S.)

Widespread and increasing urbanization has resulted in the need to assess, monitor, and understand its effects on stream water quality. Identifying relations between stream ecological condition and urban intensity indicators such as impervious surface provides important, but insufficient information to effectively address planning and management needs in such areas. In this study we investigate those specific landscape metrics which are functionally linked to indicators of stream ecological condition, and in particular, identify those characteristics that exacerbate or mitigate changes in ecological condition over and above impervious surface. The approach used addresses challenges associated with redundancy of landscape metrics, and links landscape pattern and composition to an indicator of stream ecological condition across a broad area of the eastern United States. Macroinvertebrate samples were collected during 2000–2001 from forty-two sites in the Delaware River Basin, and landscape data of high spatial and thematic resolution were obtained from photointerpretation of 1999 imagery. An ordination-derived ‘biotic score’ was positively correlated with assemblage tolerance, and with urban-related chemical characteristics such as chloride concentration and an index of potential pesticide toxicity. Impervious surface explained 56% of the variation in biotic score, but the variation explained increased to as high as 83% with the incorporation of a second land use, cover, or configuration metric at catchment or riparian scales. These include land use class-specific cover metrics such as percent of urban land with tree cover, forest fragmentation metrics such as aggregation index, riparian metrics such as percent tree cover, and metrics related to urban aggregation. Study results indicate that these metrics will be important to monitor in urbanizing areas in addition to impervious surface.     

Interactions of local habitat type,landscape composition and flower availability moderate wild bee communities

Context

Landscape and local habitat traits moderate wild bee communities. However, whether landscape effects differ between local habitat types is largely unknown.

Objectives

We explored the way that wild bee communities in three distinct habitats are shaped by landscape composition and the availability of flowering plants by evaluating divergences in response patterns between habitats.

Methods

In a large-scale monitoring project across 20 research areas, wild bee data were collected on three habitats: near-natural grassland, established flower plantings and residual habitats (e.g. field margins). Additionally, landscape composition was mapped around the research areas.

Results

Our monitoring produced a dataset of 27,650 bees belonging to 324 species. Bee communities on all three habitats reacted similarly to local flower availability. Intensively managed grassland in the surrounding landscape had an overall negative effect on the studied habitats. Other landscape variables produced diverging response patterns that were particularly pronounced during early and late season. Bee communities in near-natural grassland showed a strong positive response to ruderal areas. Flower plantings and residual habitats such as field margins showed a pronounced positive response to extensively managed grassland and woodland edges. Response patterns regarding bee abundance were consistent with those found for species richness.

Conclusion

We advise the consideration of local habitat type and seasonality when assessing the effect of landscape context on bee communities. A reduction in the intensity of grassland management enhances bee diversity in a broad range of habitats. Moreover, wild bee communities are promoted by habitat types such as ruderal areas or woodland edges.

     

Functional rather than structural connectivity explains grassland plant diversity patterns following landscape scale habitat loss

Context

Functional connectivity is vital for plant species dispersal, but little is known about how habitat loss and the presence of green infrastructure interact to affect both functional and structural connectivity, and the impacts of each on species groups.

Objectives

We investigate how changes in the spatial configuration of species-rich grasslands and related green infrastructure such as road verges, hedgerows and forest borders in three European countries have influenced landscape connectivity, and the effects on grassland plant biodiversity.

Methods

We mapped past and present land use for 36 landscapes in Belgium, Germany and Sweden, to estimate connectivity based on simple habitat spatial configuration (structural connectivity) and accounting for effective dispersal and establishment (functional connectivity) around focal grasslands. We used the resulting measures of landscape change to interpret patterns in plant communities.

Results

Increased presence of landscape connecting elements could not compensate for large scale losses of grassland area resulting in substantial declines in structural and functional connectivity. Generalist species were negatively affected by connectivity, and responded most strongly to structural connectivity, while functional connectivity determined the occurrence of grassland specialists in focal grasslands. Restored patches had more generalist species, and a lower density of grassland specialist species than ancient patches.

Conclusions

Protecting both species rich grasslands and dispersal pathways within landscapes is essential for maintaining grassland biodiversity. Our results show that increases in green infrastructure have not been sufficient to offset loss of semi-natural habitat, and that landscape links must be functionally effective in order to contribute to grassland diversity.

     

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.