Detecting biodiversity refugia using remotely sensed data

Context

Habitats characterized by improved soil moisture availability can function as microrefugia (hereafter referred to as “refugia”) for the persistence of rare plant species in dry environments. Such areas are dominated by Mediterranean woody vegetation (shrubland and woodland). An analysis of these refugia elucidates their spatial distribution at the landscape scale.

Objectives

Explore whether potential refugia, detected using the upper quantile of the normalized difference vegetation index (NDVI), are related, in space and time, with the survivability of rare species in dry environments.

Methods

We used upper NDVI quantile (25%) values to predict potential refugia in nine selected areas in northern parts of Israel from 1992 to 2011. Next, we developed an index based on the ratio of density (number of observations per area) of rare species in non-refugia versus refugia patches, per site (density of rare species index, DRSI). Finally, we examined the temporal stability of the DRSI using ANOVA and Augmented Dickey–Fuller (ADF) tests.

Results

Refugia classifications and DRSI values for all areas were stable over time (1992–2011). The DRSI values were significantly lower than 1; that is, the density of rare species in the predicted refugia areas was higher than in non-refugia areas.

Conclusions

We assumed that patches of dense woody vegetation, determined by the upper 25% quantile of the NDVI, could be used to identify potential biodiversity refugia in dry environments. This assumption was validated by the DRSI results; it confirms that the local conditions in refugia support rare species.

     

Rangeland biodiversity assessment using fine scale on-ground survey,time series of remotely sensed ground cover and climate data: an Australian savanna case study

Savanna rangelands are undergoing rapid environmental change and the need to monitor and manage landscape health is becoming increasingly an imperative of government agencies and research organizations. Remotely sensed ecological indicators of disturbance offer a potential approach, particularly in the context of issues of scale required to assess and monitor extensive rangeland areas. The objective of this research is to analyse the potential of spatially explicit ecological indicators of disturbance to explain the spatial variability in species diversity and abundance (including introduced flora species) in rangelands. For two mapped rangeland ecosystem types in northern Australia, regression analysis was used to explore the relationships between species diversity and abundance, and remotely sensed ground cover time series statistics, foliage projective cover, and a precipitation deficit index. It was assumed that the ecosystem types used had been mapped to represent uniform vegetation units and consequently predictors of environmental heterogeneity were not used in the regression analysis. It was found that the predictor variables performed well in explaining the variation in species diversity and abundance for the more open, homogenous and less topographically complex basalt ecosystem type and less effectively for the more structurally complex, more wooded and less disturbed metamorphic ecosystem type. The results indicate that, for mapped ecosystem types with low heterogeneity and topographic complexity, ground cover temporal mean and variance are potentially useful indicators of disturbance to species diversity and abundance, provided the local spatial variability in the climate signal is accounted for.     

Stability of ecosystem functioning and diversity of grasslands at the landscape scale

Diversity often increases ecosystem functioning and enhances stability, but this relationship has been evaluated at the community scale and considering, for the most part, only species richness. Here, we explored the relationship between landscape diversity and either the coefficient of variation or the interannual standard deviation of greenness in Pampean grasslands and Patagonian meadows, and tried to elucidate the mechanisms responsible for the resulting patterns. The coefficient of variation decreased with increasing landscape richness in Pampas but remained constant in Patagonia, while the interannual standard deviation of greenness decreased in both regions. The diversity–variability relationship in Pampean grasslands was largely accounted for by the mechanism of statistical averaging, while in Patagonian meadows, it was accounted for by a combination of statistical averaging, mean–variance rescaling and positive covariation of landscape units. There were no cases of negative covariance among landscape units. This is the first demonstration that landscape diversity increases stability of ecosystem functioning.     

Functional and structural landscape indicators of intensification,resilience and resistance in agroecosystems in southern Argentina based on remotely sensed data

There is increasing interest in developing criteria to evaluate the environmental implications of intensive agricultural land use. This implies discriminating between nature and man-made effects upon structural and functional attributes of agroecosystems. Adequate indicators of these combined effects should be cost efficient yet compatible with the core of ecological theory on biodiversity, spatial organization and ecosystem stability. We developed resistance-resilience metrics of plant growth to evaluate the intensity of agricultural use in a temperate irrigated basin in southern Argentina. The metrics are based on an analysis of the components of a temporal series of vegetation indices computed at a low resolution from available globally remote sensed reflectance imagery. We related the developed metrics to the properties of the soils and plant canopies observed at field scale and high-resolution imagery of the basin. Soil depth, soil erosion status and land fragmentation account for large fractions of the variance of the distribution of functional groups of the plant canopies and are also correlated with smaller scale attributes of land vegetation cover. Resistance-resilience indicators constitute a cost-efficient and adequate approach to evaluate the degree of intensification of land agricultural use.     

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.     

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.     

Sensitivity of ecosystem goods and services projections of a forest landscape model to initialization data

Projections of indicators of forest ecosystem goods and services (EGS) based on process-based landscape models are critical for adapting forest management to climate change. However, the scarcity of fine-grained, spatially explicit forest data means that initializing these models is both a challenge and a source of uncertainty. To test how different initialization approaches influence the simulation of forest dynamics and EGS indicators we initialized the forest landscape model LandClim with fine resolution empirical data, coarse empirical data, and simulation-derived data, and evaluated the results at three spatial scales (stand, management area and landscape). Simulations were performed for a spruce (Picea abies) dominated landscape in the Black Forest, Germany, under current climate and a climate change scenario. We found that long-term (>150 years) projections are robust to initialization uncertainty. In contrast, shorter-term projections are sensitive to initialization uncertainty, with sensitivity increasing when EGS are assessed at smaller spatial scales, and when the EGS indicators depend on the spatial distribution of individual species. EGS dynamics are strongly influenced by interactions between the density, species composition, and age structure of initialized forests and simulated forest management. If EGS dynamics are strongly influenced by climate change, such as when climate change induces mortality in drought-sensitive species, some of the initialization uncertainty can be masked. We advocate for initializing landscape models with fine-grained data in applications that focus on spatial management problems in heterogeneous landscapes, and stress that the scale of analysis must be in accordance with the accuracy that is warranted by the initialization data.     

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.

     

Quantifying habitat specificity to assess the contribution of a patch to species richness at a landscape scale

Assessing and predicting the species richness of a complex landscape remains a problem because there is no simple scaling function of species richness in a heterogeneous environment. Furthermore, the potential value of an area for biodiversity conservation may depend on which, rather than how many, species the area contains. This paper shows how we can objectively evaluate the contribution of an area, e.g., a habitat patch, to larger-scale plant species richness, e.g., a landscape composed of patches of several habitat types, and how we can test hypotheses that attempt to explain this contribution. We quantified the concept of habitat specificity to assess the proportion of each observed plant population that is concentrated within a given spatial element. A case study of a biodiversity-monitoring program in the Swiss Canton of Aargau showed that the relative contribution of the three main types of land use to the overall species richness differed strongly between higher taxa (vascular plants and molluscs). However, the type of data, i.e., presence-absence or abundance, was not important. Resampling of the plant data suggested that stratification provided an unbiased estimate of relative specificity, whereas unstratified sampling caused bias even for large samples. In a second case study of vascular plants in an agricultural landscape in central Switzerland, we tested whether the type, size or shape of a landscape element can predict its contribution to the species richness of the landscape. Habitat types that were less frequently disturbed contributed more per m² to landscape species richness than more frequently disturbed ones. Contrary to expectation, patch size was negatively correlated to specificity per m² for arable fields, whereas patch shape appeared to be unrelated to the specificity per m² both for arable fields and for meadows. The specificity approach provides a solution to the problem of scaling species richness and is ideally suited for testing hypotheses on the effect of landscape structure on landscape species richness. Specificity scores can easily be combined with measures of other aspects of rarity to assess the contribution of a spatial element to conservation goals formulated at regional, national or global level.     

Bush cover and range condition assessments in relation to landscape and grazing in southern Ethiopia

Progressive growth of bush cover in dry savannahs is responsible for declines in range conditions. In southern Ethiopia, the Booran pastoralists assisted our understanding of spatial patterns of bush cover and range conditions in 54 landscape patch types grouped into six landscape units within an area of 30000 km². The size of landscape patches sampled was 625 m². We assessed the relationships between bush cover, grass cover and bare soil and grazing pressure and soil erosion and changes in range condition. Externally, political conflicts and internally, break down of land use, and official bans on the use of fire promoted bush cover and the decline in range conditions. Bush cover was negatively correlated with grass cover, and positively correlated with bare soil. Grass cover was negatively correlated with bare soil and grazing pressure in most landscape patch types. Grazing pressure was not significantly correlated with bush cover or bare soil, while soil erosion was directly related to bare soil. Soil erosion was absent in 64% of the landscape patch types, and seemingly not a threat to the rangelands. The relationship between bush cover, grass cover, bare soil and soil erosion is complex and related to climate, landscape geology, and patterns of land use. Main threats to range conditions are bush climax, loss of grass cover and unpalatable forbs. Currently, >70% of the landscape patch types are in poor to fair range conditions. Decline in range conditions, unless reversed, will jeopardise the pastoral production system in southern Ethiopia.     

Establishment of a comprehensive indicator system for the assessment of biodiversity and ecosystem services

Context

Common indicators are needed to monitor biodiversity loss and the implications for the sustainable provision of ecosystem services (ES). A plethora of different sets of indicators may hinder the identification of major endpoints for large-scale assessments of biodiversity and ecosystem services (BES).

Objectives

We aim to describe the main challenges of indicators for BES assessment and provide suggestions for establishing a comprehensive indicator system.

Methods

An extensive literature review was conducted in this study. We review the main challenges of indicators for BES assessment and propose corresponding improvements from our perspectives of theory and practical applications.

Results

The main theoretical challenges of existing indicators include inconsistent definitions and classifications of ES, misunderstanding of linkages among biodiversity, ecosystem structure, functions and services, and practical problems relate to such issues as indicator representativeness, data availability, and uncertainty. Our suggested improvements include clarifying the main terms, concepts and classification of indicators, establishing a robust conceptual framework with clear interactions among different components and indicators, selecting indicators based on ecosystem properties, streaming existing data into one platform, and strengthening validation of proxies. The steps for constructing a comprehensive indicator system for BES assessment are summarized.

Conclusions

Clear definitions of key terms are indispensable to classify indicators and construct a conceptual framework. Improved understanding of the relations among indicators of biodiversity, ecosystem functions, and ES across multiple scales can guide the development of the indicator system. The integrated indicator system is an important tool for BES assessment to support decision making for sustainable development.

     

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.     

Variation in parasitoid attraction to herbivore-infested plants and alternative host plant cover mediate tritrophic interactions at the landscape scale

Landscape Ecology - Tritrophic interactions may be affected by local factors and the broader landscape context. At small spatial scales, carnivorous enemies of herbivorous insects use...     

Integrating land cover structure and functioning to predict biodiversity patterns: a hierarchical modelling framework designed for ecosystem management

Context

Land-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.

Objectives

An innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.

Methods

Founded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.

Results

The dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.

Conclusions

We outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.

     

Concepts and methods for landscape multifunctionality and a unifying framework based on ecosystem services

The potential of landscapes to supply multiple benefits to society beyond commodities production has received increasing research and policy attention. Linking the concept of multifunctionality with the ecosystem services (ES) approach offers a promising avenue for producing scientific evidence to inform landscape planning, e.g., about the relative utility of land-sharing and land-sparing. However, the value for decision-making of ES-based multifunctionality assessments has been constrained by a significant conceptual and methodological dispersion. To contribute towards a cohesive framework for landscape multifunctionality, we analyse case studies of joint ES supply regarding ten criteria designed to ultimately answer four aspects: (i) the multifunctionality of what (e.g., landscapes), (ii) the type of multifunctionality (e.g., based on ES synergies), (iii) the procedure of multifunctionality assessments, and (iv) the purpose of multifunctionality. We constructed a typology of methodological approaches based on scores for criteria describing the evaluation method and the level of stakeholder participation in assessments of joint ES supply. Surveyed studies and underlying types of methodological approaches (spatial, socio-spatial, functional, spatio-functional) differed in most criteria. We illustrate the influence of methodological divergence on planning recommendations by comparing two studies employing contrasting approaches (spatial and functional) to assess the joint supply of wildlife habitat and agricultural production in the Argentine Chaco. We distinguish between a pattern-based and process-based multifunctionality, where the latter can only be detected through approaches considering the ecological processes (e.g., ES complementarities) supporting the supply of multiple ES (functional and spatio-functional). Finally, we propose an integrated approach for assessing a socially-relevant process-based multifunctionality.     

Informing landscape planning and design for sustaining ecosystem services from existing spatial patterns and knowledge

Over the last decade we have seen an increased emphasis in environmental management and policies aimed at maintaining and restoring multiple ecosystem services at landscape scales. This emphasis has resulted from the recognition that management of specific environmental targets and ecosystem services requires an understanding of landscape processes and the spatial scales that maintain those targets and services. Moreover, we have become increasingly aware of the influence of broad-scale drivers such as climate change on landscape processes and the ecosystem services they support. Studies and assessments on the relative success of environmental policies and landscape designs in maintaining landscape processes and ecosystem services is mostly lacking. This likely reflects the relatively high cost of maintaining a commitment to implement and maintain monitoring programs that document responses of landscape processes and ecosystem services to different landscape policies and designs. However, we argue that there is considerable variation in natural and human-caused landscape pattern at local to continental scales and that this variation may facilitate analyses of how environmental targets and ecosystem services have responded to such patterns. Moreover, wall-to-wall spatial data on land cover and land use at national scales may permit characterization and mapping of different landscape pattern gradients. We discuss four broad and interrelated focus areas that should enhance our understanding of how landscape pattern influences ecosystem services: (1) characterizing and mapping landscape pattern gradients; (2) quantifying relationships between landscape patterns and environmental targets and ecosystem services, (3) evaluating landscape patterns with regards to multiple ecosystem services, and (4) applying adaptive management concepts to improve the effectiveness of specific landscape designs in sustaining ecosystem services. We discuss opportunities as well as challenges in each of these four areas. We believe that this agenda could lead to spatially explicit solutions in managing a range of environmental targets and ecosystem services. Spatially explicit options are critical in managing and protecting landscapes, especially given that communities and organizations are often limited in their capacity to make changes at landscape scales. The issues and potential solutions discussed in this paper expand upon the call by Nassauer and Opdam (Landscape Ecol 23:633–644, 2008) to include design as a fundamental element in landscape ecology research by evaluating natural and human-caused (planned or designed) landscape patterns and their influence on ecosystem services. It also expands upon the idea of “learning by doing” to include “learning from what has already been done.”     

An agent-based approach to modeling impacts of agricultural policy on land use, biodiversity and ecosystem services

We present extensions to the agent-based agricultural policy simulator (AgriPoliS) model that make it possible to simulate the consequences of agricultural policy reform on farmers?? land use decisions and concomitant impacts on landscape mosaic, biodiversity and ecosystem services in a real agricultural region. An observed population of farms is modelled as a multi-agent system where individual farm-agent behaviour and their interactions??principally competition for land??are defined through an optimization framework with land use and landscape impacts resulting as emergent properties of the system. The model is calibrated to real data on the farms and the landscape to be studied. We illustrate the utility of the model by evaluating the potential impacts of three alternative frameworks for the European Union Common Agricultural Policy (CAP) on landscape values in two marginal agricultural regions. Mosaic value was found to be sensitive to the choice of policy scheme in one of the landscapes, whereas significant trade-offs were shown to occur in terms of species richness by habitat and species composition at the landscape scale in both regions. The relationship between food production and other ecosystem services was found to be multifaceted. Thus illustrating the difficulty of achieving landscape goals in a particular region with simple or general land management rules (such as the current rules attached to CAPs direct payments). Given the scarcity of funding for conservation, the level and conditions for allocating direct payments are, potentially, of great importance for preserving landscape values in marginal agricultural regions (subject to levels of other support).