Science for action at the local landscape scale

For landscape ecology to produce knowledge relevant to society, it must include considerations of human culture and behavior, extending beyond the natural sciences to synthesize with many other disciplines. Furthermore, it needs to be able to support landscape change processes which increasingly take the shape of deliberative and collaborative decision making by local stakeholder groups. Landscape ecology as described by Wu (Landscape Ecol 28:1–11, 2013) therefore needs three additional topics of investigation: (1) the local landscape as a boundary object that builds communication among disciplines and between science and local communities, (2) iterative and collaborative methods for generating transdisciplinary approaches to sustainable change, and (3) the effect of scientific knowledge and tools on local landscape policy and landscape change. Collectively, these topics could empower landscape ecology to be a science for action at the local scale.     

Lightning,precipitation and vegetation at landscape scale

Landscape Ecology - We investigated the question “Is there a relationship between seasonality in precipitation and vegetative cover in Pole Canyon, NM?” GIS and statistical methods were...     

Functional beetle diversity in managed grasslands: effects of region,landscape context and land use intensity

Current biodiversity conservation policies have so far had limited success because they are mainly targeted to the scale of individual fields with little concern on different responses of organism groups at larger spatial scales. We investigated the relative impacts of multi-scale factors, including local land use intensity, landscape context and region, on functional groups of beetles (Coleoptera). In 2008, beetles were suction-sampled from 95 managed grasslands in three regions, ranging from Southern to Northern Germany. The results showed that region was the most important factor affecting the abundance of herbivores and the abundance and species composition of predators and decomposers. Herbivores were not affected by landscape context and land use intensity. The species composition of the predator communities changed with land use intensity, but only in interaction with landscape context. Interestingly, decomposer abundance was negatively related to land use intensity in low-diversity landscapes, whereas in high-diversity landscapes the relation was positive, possibly due to enhanced spillover effects in complex landscapes. We conclude that (i) management at multiple scales, from local sites to landscapes and regions, is essential for managing biodiversity, (ii) beetle predators and decomposers are more affected than herbivores, supporting the hypothesis that higher trophic levels are more sensitive to environmental change, and (iii) sustaining biological control and decomposition services in managed grassland needs a diverse landscape, while effects of local land use intensity may depend on landscape context.     

Scale problems in reporting landscape pattern at the regional scale

Remotely sensed data for Southeastern United States (Standard Federal Region 4) are used to examine the scale problems involved in reporting landscape pattern for a large, heterogeneous region. Frequency distributions of landscape indices illustrate problems associated with the grain or resolution of the data. Grain should be 2 to 5 times smaller than the spatial features of interest. The analyses also reveal that the indices are sensitive to the calculation scale,i.e., the unit area or extent over which the index is computed. This “sample area” must be 2 to 5 times larger than landscape patches to avoid bias in calculating the indices. Research sponsored by the Office of Research and Development, U.S. Environmental Protection Agency under IAG DW89934440-6 and DW89936104-01 with the U.S. Department of Energy under contract DE-AC05-84OR21400 with Martin Marietta Energy Systems, Inc.     

Combining process-based models for future biomass assessment at landscape scale

We need an integrated assessment of the bioenergy production at landscape scale for at least three main reasons: (1) it is predictable that we will soon have landscapes dedicated to bioenergy productions; (2) a number of “win–win” solutions combining several dedicated energy crops have been suggested for a better use of local climate, soil mosaic and production systems and (3) “well-to-wheels” analyses for the entire bioenergy production chain urge us to optimize the life cycle of bioenergies at large scales. In this context, we argue that the new generation of landscape models allows in silico experiments to estimate bioenergy distributions (in space and time) that are helpful for this integrated assessment of the bioenergy production. The main objective of this paper was to develop a detailed modeling methodology for this purpose. We aimed at illustrating and discussing the use of mechanistic models and their possible association to simulate future distributions of fuel biomass. We applied two separated landscape models dedicated to human-driven agricultural and climate-driven forested neighboring patches. These models were combined in the same theoretical (i.e. virtual) landscape for present as well as future scenarios by associating realistic agricultural production scenarios and B2-IPCC climate scenarios depending on the bioenergy type (crop or forest) concerned in each landscape patch. We then estimated esthetical impacts of our simulations by using 3D visualizations and a quantitative “depth” index to rank them. Results first showed that the transport cost at landscape scale was not correlated to the total biomass production, mainly due to landscape configuration constraints. Secondly, averaged index values of the four simulations were conditioned by agricultural practices, while temporal trends were conditioned by gradual climate changes. Thirdly, the most realistic simulated landscape combining intensive agricultural practices and climate change with atmospheric CO₂ concentration increase corresponded to the lowest and unwanted bioenergy conversion inefficiency (the biomass production ratio over 100 years divided by the averaged transport cost) and to the most open landscape. Managing land use and land cover changes at landscape scale is probably one of the most powerful ways to mitigate negative (or magnify positive) effects of climate and human decisions on overall biomass productions.     

Butterflies in Swedish grasslands benefit from forest and respond to landscape composition at different spatial scales

Context

Loss and fragmentation of semi-natural grasslands has critically affected many butterfly species in Europe. Habitat area and isolation can have strong effects on the local biodiversity but species may also be strongly affected by the surrounding matrix.

Objectives

We explored how different land cover types in the landscape explained the occurrence of butterfly species in semi-natural grasslands.

Methods

Using data from 476 semi-natural grasslands in Sweden, we analysed the effect of matrix composition on species richness and occurrence. Additionally, we analysed at which spatial scales butterflies responded to matrix types (forests, semi-natural grasslands, arable land and water).

Results

Forest cover showed the strongest positive effect on species richness, followed by semi-natural grasslands. Forest also had a positive effect on red-listed species at local scales. Responses to matrix composition were highly species-specific. The majority of the 30 most common species showed strong positive responses to the amount of forest cover within 200–500 m. There was a smaller group of species showing a positive response to arable land cover within 500–2000 m. Thirteen species showed positive responses to the amount of semi-natural grasslands, generally at larger scales (10–30 km).

Conclusions

Our study showed that surrounding forest is beneficial for many grassland butterfly species and that forests might mitigate the negative effects of habitat loss caused by agricultural intensification. Also, semi-natural grasslands were an important factor for species richness at larger spatial scales, indicating that a landscape consisting mainly of supporting habitats (i.e. forests) are insufficient to sustain a rich butterfly fauna.

     

Impacts of selective logging on tree diversity across a rainforest landscape: the importance of spatial scale

Selective logging of tropical forests imposes spatial pattern on the landscape by creating a mosaic of patches affected by different intensities of disturbance. To understand the ecological impacts of selective logging it is therefore necessary to explore how patterns of tree species composition are affected by this patchy disturbance. This study examines the impacts of selective logging on species composition and spatial patterns of vegetation structure and tree diversity in Sabah, Borneo. We compare tree diversity between logged and unlogged forest at three scales: species richness within plots, species turnover among plots, and total species richness and composition of plots combined. Logging had no effect on tree diversity measured at the smallest scale. Logged forest had a greater rate of species turnover with distance, so at a large spatial scale it supported more tree species than the relatively homogeneous unlogged area. Tree species composition also differed significantly between the two types of forest, with more small dipterocarps and large pioneers in logged forest, and more large dipterocarps in unlogged forest. Our results emphasize the importance of sampling at a sufficiently large scale to represent patterns of biodiversity within tropical forest landscapes. Large areas of production forest in SE Asia are threatened with conversion to commercial crops; our findings show that selectively logged forest can retain considerable conservation value.     

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.

     

西藏东南地区不同海拔果树昆虫群落多样性研究

为了明确西藏地区果园昆虫种类组成及多样性,对该地区果园昆虫种类、数量进行了系统调查,分析探讨了西藏地区低、中、高3个不同海拔区域果园昆虫群落的组成、群落丰富度、多样性、均匀度和优势度等特征。结果表明,在不同海拔的昆虫种类组成具有明显差异。调查共采集到昆虫标本877个,隶属13目47科71种,其中,低海拔地区共51种,占比71.83%;中海拔地区17种,占比23.94%;高海拔地区11种,占比15.49%。低海拔地区物种丰富度最高,为7.7344,高海拔地区最低,为2.1762;昆虫群落物种多样性、群落均匀度、群落相似性也随海拔的升高而降低,而优势集中度则随海拔升高而增大。在果园生态系统中,不同海拔生产者(果树种类)垂直分布的不同,消费者(果树昆虫,包括害虫及天敌)的组成及多样性亦不同;西藏东南部地区果园昆虫在低海拔生境中群落较为丰富,多样性指数、均匀度最高;高海拔地区群落优势度最高。     

Landscape diversity and field border density enhance carabid diversity in adjacent grasslands and cereal fields

Landscape Ecology - Permanent grasslands have declined across Europe since the agricultural intensification. Grassland vicinity, landscape heterogeneity and vicinity of hedgerows are enhancing...     

The effects of landscape patterns on ecosystem services: meta-analyses of landscape services

Purpose

The recently introduced concept of ‘landscape services’—ecosystem services influenced by landscape patterns—may be particularly useful in landscape planning by potentially increasing stakeholder participation and financial funding. However, integrating this concept remains challenging. In order to bypass this barrier, we must gain a greater understanding of how landscape composition and configuration influence the services provided.

Methods

We conducted meta-analyses that considered published studies evaluating the effects of several landscape metrics on the following services: pollination, pest control, water quality, disease control, and aesthetic value. We report the cumulative mean effect size (E₊₊), where the signal of the values is related to positive or negative influences.

Results

Landscape complexity differentially influenced the provision of services. Particularly, the percentage of natural areas had an effect on natural enemies (E₊₊ =?0.35), pollination (E₊₊?=?0.41), and disease control (E₊₊?=?0.20), while the percentage of no-crop areas had an effect on water quality (E₊₊?=?0.42) and pest response (E₊₊?=?0.33). Furthermore, heterogeneity had an effect on aesthetic value (E₊₊?=?0.5) and water quality (E₊₊ =???0.40). Moreover, landscape aggregation was important to explaining pollination (E₊₊?=?0.29) and water quality (E₊₊?=?0.35).

Conclusions

The meta-analyses reinforce the importance of considering landscape structure in assessing ecosystem services for management purposes and decision-making. The magnitude of landscape effect varies according to the service being studied. Therefore, land managers must account for landscape composition and configuration in order to ensure the maintenance of services and adapt their approach to suit the focal service.

     

Deciduous trees increase bat diversity at stand and landscape scales in mosaic pine plantations

Context

In heterogeneous landscapes, habitat complementation is a key process underlying the distribution of mobile species able to exploit non-substitutable resources over large home ranges. For instance, insectivorous bats need to forage in a diversity of habitat patches offering varied compositions and structures within forest landscape mosaics to fulfill their life cycle requirements.

Objectives

We aimed at analyzing the effects of forest structure and composition measured at the stand and landscape scales on bat species richness, abundance and community composition in pine plantation forests of south-western France.

Methods

We sampled bat communities at different periods of the summer season using automatic ultrasound recorders along a tree composition gradient from pine monocultures to pure oak stands. We analyzed bat species activity (as a proxy for bat abundance) and species richness with linear mixed models. Distance-based constrained ordinations were used to partition the spatio-temporal variation in bat communities.

Results

Deciduous tree cover increased bat activity and modified community composition at both stand and landscape scales. Changes in bat communities were mostly driven by landscape-scale variables while bat activity responded more to stand-scale predictors.

Conclusions

The maintenance of deciduous trees at both stand and landscape scales is likely critical for bat communities living in fast-growing conifer plantations, by increasing the availability and diversity of prey and roosting sites. Our study suggests that bats respond to forest composition at both stand and landscape scales in mosaic plantation landscapes, mainly through a resource complementation process.

     

Trait-dependent responses of flower-visiting insects to distance to semi-natural grasslands and landscape heterogeneity

Protecting semi-natural grasslands may through spill-over benefit species richness and abundance of flower-visiting insects in linear habitats, such as uncultivated field boundaries, in agricultural landscapes. However, whether local diversity increases both with decreasing distance from potential source habitats and increasing landscape heterogeneity is poorly known due to a general lack of studies replicated at the landscape scale. We analysed if local assemblages of bumblebees, butterflies and hoverflies in linear uncultivated habitats increased with increasing distance to the nearest semi-natural grassland in 12 replicated landscapes along a gradient of landscape heterogeneity in Scania, Southern Sweden. Species richness and abundance of bumblebees and butterflies, but not hoverflies, decreased with increasing distance to semi-natural grasslands, but none of these groups were related to increasing landscape heterogeneity. Further analyses on trait-specific groups revealed significant decreases in the abundance of sedentary and grassland specialist butterflies with increasing distance to assumed source populations, whereas this was not the case concerning mobile species and grassland generalists. The abundance of all bumblebee trait groups decreased with increasing distance to semi-natural grasslands, but only some species (those nesting above ground, with long colony cycles and with small colony sizes) also increased with increasing landscape heterogeneity. We conclude that local species assemblages of flower-visiting insects in linear habitat elements were mainly affected by the occurrence of nearby semi-natural grasslands. In order to conserve diverse assemblages of flower-visiting insects, including the ecological services they provide, it is important to conserve semi-natural grasslands dispersed throughout agricultural landscapes.     

Partitioning spatial,environmental, and community drivers of ecosystem functioning

Landscape Ecology - Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in...     

Selection of scale for Everglades landscape models

This article addresses the problem of determining the optimal “Model Grain” or spatial resolution (scale) for landscape modeling in the Everglades. Selecting an appropriate scale for landscape modeling is a critical task that is necessary before using spatial data for model development. How the landscape is viewed in a simulation model is dependent on the scale (cell size) in which it is created. Given that different processes usually have different rates of fluctuations (frequencies), the question of selection of an appropriate modeling scale is a difficult one and most relevant to developing spatial ecosystem models. The question of choosing the appropriate scale for modeling is addressed using the landscape indices (e.g., cover fraction, diversity index, fractal dimension, and transition probabilities) recently developed for quantifying overall characteristics of spatial patterns. A vegetation map of an Everglades impoundment area developed from SPOT satellite data was used in the analyses. The data from this original 20 × 20 m data set was spatially aggregated to a 40 × 40 m resolution and incremented by 40 meters on up to 1000 × 1000 m (i.e., 40, 80, 120, 160 … 1000) scale. The primary focus was on the loss of information and the variation of spatial indices as a function of broadening “Model Grain” or scale. Cover fraction and diversity indices with broadening scale indicate important features, such as tree islands and brush mixture communities in the landscape, nearly disappear at or beyond the 700 m scale. The fractal analyses indicate that the area perimeter relationship changes quite rapidly after about 100 m scale. These results and others reported in the paper should be useful for setting appropriate objectives and expectations for Everglades landscape models built to varying spatial scales.     

Integrating landscape resistance and multi-scale predictor of habitat selection for amphibian distribution modelling at large scale

Context

Species distribution modelling is a common tool in conservation biology but two main criticisms remain: (1) the use of simplistic variables that do not account for species movements and/or connectivity and (2) poor consideration of multi-scale processes driving species distributions.

Objectives

We aimed to determine if including multi-scale and fine-scale movement processes in SDM predictors would improve accuracy of SDM for low-mobility amphibian species compared with species-level analysis.

Methods

We tested and compared different SDMs for nine amphibian species with four different sets of predictors: (1) simple distance-based predictors; (2) single-scale compositional predictors; (3) multi-scale compositional predictors with a priori selection of scale based on knowledge of species mobility and scale-of-effect; and (4) multi-scale compositional predictors calculated using a friction-based functional grain to account for resource accessibility with landscape resistance to movement.

Results

Using friction-based functional grain predictors produced slight to moderate improvements of SDM performance at large scale. The multi-scale approach, with a priori scale selection, led to ambiguous results depending on the species studied, in particular for generalist species.

Conclusion

We underline the potential of using a friction-based functional grain to improve SDM predictions for species-level analysis.

     

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.

     

Coupling ecosystem and landscape models to study the effects of plot number and location on prediction of forest landscape change

A fundamental but unsolved dilemma is that observation and prediction scales are often mismatched. Reconciling this mismatch largely depends on how to design samples on a heterogeneous landscape. In this study, we used a coupled modeling approach to investigate the effects of plot number and location on predicting tree species distribution at the landscape scale. We used an ecosystem process model (LINKAGES) to generate tree species response to the environment (a land type) at the plot scale. To explore realistic parameterization scenarios we used results from LINKAGES simulations on species establishment probabilities under the current and warming climate. This allowed us to design a series of plot number and location scenarios at the landscape scale. Species establishment probabilities for different land types were then used as input for the forest landscape model (LANDIS) that simulated tree species distribution at the landscape scale. To investigate the effects of plot number and location on forest landscape predictions, LANDIS considered effects of climate warming only for the land types in which experimental plots were placed; otherwise inputs for the current climate were used. We then statistically examined the relationships of response variables (species percent area) among these scenarios and the reference scenario in which plots were placed on all land types of the study area. Our results showed that for species highly or moderately sensitive to environmental heterogeneity, increasing plot numbers to cover as many land types as possible is the strategy to accurately predict species distribution at the landscape scale. In contrast, for species insensitive to environmental heterogeneity, plot location was more important than plot number. In this case, placing plots in land types with large area of species distribution is warranted. For some moderately sensitive species that experienced intense disturbance, results were different in different simulation periods. Results from this study may provide insights into sample design for forest landscape predictions.     

Present and historical landscape structure shapes current species richness in Central European grasslands

Landscape Ecology - Current diversity and species composition of ecological communities can often not exclusively be explained by present land use and landscape structure. Historical land use may...