Mapping vegetation functional types in urban areas with WorldView-2 imagery: Integrating object-based classification with phenology

Mapping urban vegetation is a prerequisite to accurately understanding landscape patterns and ecological services provided by urban vegetation. However, the uncertainties in fine-scale vegetation biodiversity mapping still exist in capturing vegetation functional types efficiently at fine scale. To facilitate the application of fine-scale vegetation spatial configuration used for urban landscape planning and ecosystem service valuation, we present an approach integrating object-based classification with vegetation phenology for fine-scale vegetation functional type mapping in compact city of Beijing, China. The phenological information derived from two WorldView-2 imagery scenes, acquired on 14 September 2012 and 26 November 2012, was used to aid in the classification of tree functional types and grass. Then we further compared the approach to that of using only one WorldView imagery. We found WorldView-2 imagery can be successfully applied to map functional types of urban vegetation with its high spatial resolution and relatively high spectral resolution. The application of the vegetation phenology into classification greatly improved the overall accuracy of classification from 82.3% to 91.1%. In particular, the accuracies of vegetation types was improved by from 10% to 13.26%. The approach integrating vegetation phenology with high-resolution remote sensed images provides an efficient tool to incorporate multi-temporal data into fine-scale urban classification.     

Historical range of variability in eastern Cascades forests,Washington, USA

The historical range of variability (HRV) has been suggested as a coarse filter approach to maintain ecosystem sustainability and resiliency. The historical range of variability in forest age structure for the central eastern Cascade Range in Washington State, USA was developed from historical fire return intervals and the manner in which fire acted as both cyclic and stochastic processes. The proportions of seven forest structural stages calculated through these processes were applied to the area of each forest series within the central eastern Cascades landscape. Early successional forest stages were more common in high elevation forest than low elevation forest. The historical proportion of old growth and late successional forest varied from 38 to 63 percent of the forested landscape. These process-based estimates are consistent with those developed from forest structural information. HRV is a valuable planning tool for ecosystem conservation purposes, but must be applied to real landscapes with consideration of both temporal and spatial scale. This revised version was published online in July 2006 with corrections to the Cover Date.     

Linkages beyond borders: targeting spatial processes in fragmented urban landscapes

Management of ecosystems often focuses on specific species chosen for their habitat demand, public appeal, or levels of threat. We propose a complementary framework for choosing focal species, the mobile link concept, which allows managers to focus on spatial processes and deal with multi-scale ecological dynamics. Spatial processes are important for three reasons: maintenance, re-organization, and restoration of ecological values. We illustrate the framework with a case study of the Eurasian Jay, a mobile link species of importance for the oak forest regeneration in the Stockholm National Urban Park, Sweden, and its surroundings. The case study concludes with a conceptual model for how the framework can be applied in management. The model is based on a review of published data complemented with a seed predation experiment and mapping of Jay territories to reduce the risk of applying non-urban site-specific information in an urban setting. Our case study shows that the mobile link approach has several advantages: (1) Reducing the vulnerability of ecological functions to disturbances and fluctuations in resources allocated to management, (2) Reducing management costs by maintaining natural processes, and (3) Maintaining gene flow and genetic diversity at a landscape level. We argue that management that includes mobile link organisms is an important step towards the prevention of ecosystem degradation and biodiversity loss in increasingly fragmented landscapes. Identifying and managing mobile links is a way to align management with the ecologically relevant scales in any landscape.     

Modelling land cover transitions: A solution to the problem of spatial dependence in data

Raster-based spatial land cover transition models (LCTMs) are widely used in landscape ecology. However, many LCTMs do not account for spatial dependence of the input data, which may artificially fragment the output spatial configuration. We demonstrate the consequences of ignoring spatial dependence, thus assigning probabilities randomly in space, using a simple LCTM. We ran the model from four different initial conditions with distinct spatial configurations and results indicated that, after 20 simulation steps, all of them converged towards the spatial configuration of the random data set. From an ecological perspective this is a serious problem because ecological data often exhibit distinct spatial configuration related to ecological processes. As a solution, we propose an approach (region approach) that accounts for spatial dependence of LCTM input data. Underlying spatial dependence was used to apply spatial bias to probability assignment within the model. As a case study we applied a region approach to a Vegetation Transition Model (VTM); a semi-Markovian model that simulates forest succession. The VTM was applied to approximately 500,000 ha of boreal forest in Ontario, at 1 ha pixel resolution. When the stochastic transition algorithms were applied without accounting for spatial dependence, spatial configuration of the output data became progressively more fragmented. When the VTM was applied using the region approach to account for spatial dependence output fragmentation was reduced. Accounting for spatial dependence in transition models will create more reliable output for analyzing spatial patterns and relating those patterns to ecological processes.This revised version was published online in May 2005 with corrections to the Cover Date.     

Natural forest expansion into suburban countryside: Gained ground for a green infrastructure?

Understanding patterns of natural forest expansion in rural regions under the influence of urbanization processes is crucial for integrated spatial planning across the urban-to-rural gradient. As a matter of fact, forest expansion is the only natural process that may counteract the consumption of the ecosystem capital and ecosystems services of rural lands due to uncontrolled urban sprawl. The paper addresses this topic in the paradigmatic case study of the countryside of Rome (Italy), characterized by counter dynamics of forest expansion and suburbanization. Morphological Spatial Pattern Analysis (MSPA) is applied to classify the forest landscape structure twice (1974 and 2008) according to seven categories (core, islet, perforation, edge, loop, bridge, branch) with different potential functional role as elements of a green infrastructure. Main findings are: (i) forest cover increased from 11% to 16% between 1974 and 2008; forest land uptake exceeds 4% of total study area, but shows a slower pace than the growth of built-up areas (10%); (ii) forest expansion has been to a large extent achieved by “sprawling” of islets (1.6% of the study area) along the stream network; (iii) more compact forest expansion has taken place on 0.2% of the study area in the form of additions to existing core areas or creation of new ones and (iv) the establishment of a network of protected areas nearby Rome has played a key role for the conservation and further expansion of core areas; yet, local loss of 1974 core areas stocks in a few protected areas indicates need of further law enforcement to ensure effective protection of the natural capital from degradation processes or even land conversion into built-up areas.Results calls for future in-depth investigations on the quality of newly created or maintained forest resource stocks associated to different spatial pattern structures. Integrated spatial planning strategies are outlined for the conservation of ecosystem capital and ecosystems services provided by forests, as major components of Rome's green infrastructure.     

Elasticity and loop analyses: tools for understanding forest landscape response to climatic change in spatial dynamic models

Spatially explicit dynamic forest landscape models have been important tools to study large-scale forest landscape response under global climatic change. However, the quantification of relative importance of different transition pathways among different forest types to forest landscape dynamics stands as a significant challenge. In this study, we propose a novel approach of elasticity and loop analyses to identify important transition pathways contributing to forest landscape dynamics. The elasticity analysis calculates the elasticity to measure the importance of one-directional transitions (transition from one forest type directly to another forest type); while the loop analysis is employed to measure the importance of different circular transition pathways (transition from one forest type through other forest types back to itself). We apply the proposed approach to a spatially explicit dynamic model, LANDIS-II, in a study of forest landscape response to climatic change in the Boundary Waters Canoe Area (BWCA) incorporating the uncertainties in climatic change predictions. Our results not only corroborate the findings of the previous studies on the most likely future forest compositions under simulated climatic variability, but also, through the novel application of the elasticity and loop analyses concepts, provide a quantitative assessment of the specific mechanisms leading to particular forest compositions, some of which might remain undetected with conventional model evaluation methods. By quantifying the importance of specific processes (transitions among forest types) to forest composition dynamics, the proposed approach can be a valuable tool for a more quantitative understanding of the relationship between processes and landscape composition/patterns.     

Detection of relative differences in phenology of forest species using Landsat and MODIS

Landsat imagery is routinely used to characterize stand-level forest communities, but low temporal resolution makes pixel-wise characterization of phenology difficult. This limitation can be overcome by using multi-year imagery, but organizing Landsat scenes by calendar date ignores phenological gradients across the landscape as well as inter-annual differences in both scene- and pixel-wise phenology. We demonstrate how a spatially generalizable, phenologically-informed approach for re-ordering Landsat pixels can be used to characterize spatial variations in autumn senescence in several forest tree species. Using end-of-season estimates derived from MODIS phenology data, we determined the “days left in season” (DLiS) across Landsat images to produce a synthesized phenological trajectory of the normalized difference infrared index (NDII). We used ground-based species composition data in conjunction with the NDII trajectories to model autumn senescence by species. Absolute phenology differed by one and a half to 3 weeks between northern and southern Wisconsin, USA, but we show that the relative timing of phenology for individual species differs across regions by only 1–3 days when considering senescence with respect to the local end of the season. The progression of species senescence was consistent in lowland stands, starting with green and black ash, followed by silver maple, yellow birch, red maple, and tamarack. The image analyses suggest that senescence progressed more rapidly in southern than northern Wisconsin, starting earlier but taking about ten more days in the north. Our results support the use of MODIS phenological data with multi-year Landsat imagery to detect species with unique phenologies and identify how these vary across the landscape.     

Multi-scale predictive habitat suitability modeling based on hierarchically delineated patches: an example for yellow-billed cuckoos nesting in riparian forests,California, USA

The discipline of landscape ecology recognizes the importance of measuring habitat suitability variables at spatial scales relevant to specific organisms. This paper uses a novel multi-scale hierarchical patch delineation method, PatchMorph, to measure landscape patch characteristics at two distinct spatial scales and statistically relate them to the presence of state-listed endangered yellow-billed cuckoos (Coccyzus americanus occidentalis) nesting in forest patches along the Sacramento River, California, USA. The landscape patch characteristics calculated were: patch thickness, area of cottonwood forest, area of riparian scrub, area of other mixed riparian forest, and total patch area. A third, regional spatial variable, delineating the north and south portions of study area was also analyzed for the effect of regional processes. Using field surveys, the landscape characteristics were related to patch occupancy by yellow-billed cuckoos. The area of cottonwood forest measured at the finest spatial scale of patches was found to be the most important factor determining yellow-billed cuckoo presence in the forest patches, while no patch characteristics at the larger scale of habitat patches were important. The regional spatial variable was important in two of the three analysis techniques. Model validation using an independent data set of surveys (conducted 1987–1990) found 76–82% model accuracy for all the statistical techniques used. Our results show that the spatial scale at which habitat characteristics are measured influences the suitability of forest patches. This multi-scale patch and model selection approach to habitat suitability analysis can readily be generalized for use with other organisms and systems.     

Integrating stakeholders’ demands and scientific knowledge on ecosystem services in landscape planning

The conflict between conservation and timber production is shifting in regions such as Biscay (Basque Country, northern Spain) where planted forests are no longer profitable without public subsidies and environmentalist claim that public subsidies should be reoriented to the regeneration of natural forest. This paper develops an approach that integrates scientific knowledge and stakeholders’ demands to provide decision-making guidelines for the development of new landscape planning strategies while considering ecosystem services. First, a participatory process was conducted to develop a community vision for the region’s sustainable future considering the opportunities and constrains provided by the landscape and its ecosystems. In the participatory process forest management was considered an important driver for the region`s landscape development and forest multi-functionality was envisioned as a feasible attractive alternative. The participatory process identified a knowledge gap on the synergies and trade-offs between biodiversity and carbon storage and how these depend on different forest types. Second, to study the existing synergies and trade-offs between biodiversity and carbon storage and disentangle the identified knowledge gap, a GIS-based research was conducted based on spatially explicit indicators. Our spatial analysis results showed that natural forests’ contribution to biodiversity and carbon storage is higher than that of the plantations with exotic species in the region. The results from the spatial analysis converged with those from the participatory process in the suitability of promoting, where possible and appropriate, natural forest ecosystems restoration. This iterative learning and decision making process is already showing its effectiveness for decision making, with concrete examples of how the results obtained with the applied approach are being included in planning and decision-making processes.     

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.     

The value of vegetation cover for ecosystem services in the suburban context

Latin-American cities can be characterized by dynamic processes of urbanization that encroach upon the natural and semi-natural surrounding landscapes. Our study presents the effects of landscape development, transformed from semi-natural conditions into a mostly disperse suburban settlement. We explore the impact that this transformation has had on this context by three ecosystem services that regulate rainwater runoff, enhance microclimate conditions and help to improve air quality by monitoring vegetation cover. We have designed a spatio-temporal hierarchical analysis which employs remote sensing techniques to capture the structural changes of this landscape over long, medium and short term scales on two spatial levels. This methodological approach was tested in the Metropolitan Area of Santiago (MAS) as case study area. Despite of the increase in impervious surfaces due to urban processes, there has also been an increase in vegetation cover, which has led to an improvement in the provision of the above-mentioned ecosystem services. Hence, if diverse urbanization processes continue and they are coupled with an increase in vegetation cover, the provision of ecosystem services could also expand. This phenomenon can be observed in some areas, where public and private green spaces are created and maintained. Our data analyses give evidence that certain types of suburban areas which increase the share of vegetation cover can provide daily ecological benefits for urban neighborhoods, and beyond, for adjacent areas. Moreover, suburban development can successfully provide ecological benefits to citizens. Such processes can only be ecologically sustainable if the composition of vegetation is well-adapted to the regional climatic conditions.     

Scaling up ecosystem productivity from patch to landscape: a case study of Changbai Mountain Nature Reserve,China

Scaling up ecosystem processes from plots to landscapes is essential for understanding landscape structure and functioning as well as for assessing ecological impacts of land use and climate change. This study illustrates an upscaling approach to studying the spatiotemporal pattern of ecosystem processes in the Changbai Mountain Nature Reserve in northeastern China by integrating simulation modeling, GIS, remote sensing data, and field-based observations. The ecosystem model incorporated processes of energy transfer, plant physiology, carbon dynamics, and water cycling. Using a direct extrapolation scheme, the patch-level ecosystem model was scaled up to quantify the landscape-level pattern of primary productivity and the carbon source-sink relationship. The simulated net primary productivity (NPP) for the entire landscape, consisting of several ecosystem types, was 0.680 kg C m⁻² yr⁻¹. The most widely distributed ecosystem type in this region was the mixed broad-leaved and Korean pine (Pinus koraiensis) forest, which had the highest NPP (1.084 kg C m⁻² yr⁻¹). The total annual NPP for all ecosystem types combined was estimated to be 1.332 Mt C yr⁻¹. These results suggest that the Changbai Mountain landscape as a whole was a carbon sink, with a net carbon sequestration rate of about 0.884 Mt C yr⁻¹ for the study period. The simulated NPP agreed reasonably well with available field measurements at a number of locations within the study landscape. Our study provides new insight into the relationship between landscape pattern and ecosystem processes, and useful information for improving management practices in the Changbai Mountain Nature Reserve, which is one of the most important forested landscapes in China. Several research needs are discussed to further refine the modeling approach and reduce prediction uncertainties.     

Spatial and temporal analysis of landscape patterns

A variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landscape data that are stored in a GIS. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.     

An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems

Computer models are increasingly being used by forest ecologists and managers to simulate long-term forest landscape change. We review models of forest landscape change from an ecological rather than methodological perspective. We developed a classification based on the representation of three ecological criteria: spatial interactions, tree species community dynamics, and ecosystem processes. Spatial interactions are processes that spread across a landscape and depend upon spatial context and landscape configuration. Communities of tree species may change over time or can be defined a priori. Ecosystem process representation may range from no representation to a highly mechanistic, detailed representation. Our classification highlights the implicit assumptions of each model group and helps define the problem set for which each model group is most appropriate. We also provide a brief history of forest landscape simulation models, summarize the current trends in methods, and consider how forest landscape models may evolve and continue to contribute to forest ecology and management. Our classification and review can provide novice modelers with the ecological context for understanding or choosing an appropriate model for their specific hypotheses. In addition, our review clarifies the challenges and opportunities that confront practicing model users and model developers.     

Effects of bird and bat exclusion on coffee pest control at multiple spatial scales

Context

Despite the key role of biological control in agricultural landscapes, we still poorly understand how landscape structure modulates pest control at different spatial scales.

Objectives

Here we take an experimental approach to explore whether bird and bat exclusion affects pest control in sun coffee plantations, and whether this service is consistent at different spatial scales.

Methods

We experimentally excluded flying vertebrates from coffee plants in 32 sites in the Brazilian Atlantic Forest, encompassing a gradient of forest cover at landscape (2 km radius) and local (300 m) spatial scales, and quantified coffee leaf loss, as an indicator of herbivory, and fruit set.

Results

Leaf loss decreased with higher landscape forest cover, but this relation was significantly different between treatment and control plants depending on local forest cover. On the other hand, fruit set responded to the interaction between treatment and local forest cover but was not affected by landscape forest cover. More specifically, fruit set increased significantly with local forest cover in exclusion treatments and showed a non-significant decrease in open controls.

Conclusions

These results suggest that services provided by flying vertebrates are modulated by processes occurring at different spatial scales. We posit that in areas with high local forest cover flying vertebrates may establish negative interactions with predaceous arthropods (i.e. intraguild predation), but this would not be the case in areas with low local forest cover. We highlight the importance of employing a multi-scale analysis in systems where multiple species, which perceive the landscape differently, are providing ecosystem services.

     

Modeling the spatially dynamic distribution of humans in the Oregon (USA) Coast Range

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the socioeconomic and ecological processes under study are sensitive to a range of human habitation. In this paper, we characterize the spatial dynamic distribution of humans throughout the forest landscape of western Oregon (USA). We develop an empirical model describing the spatial distribution and rate of change in historic building densities as a function of a gravity index of development pressure, existing building densities, slope, elevation, and existing land use zoning. We use the empirical model to project changes in building densities that are applied to a 1995 base map of building density to describe future spatial distributions of buildings over time. The projected building density maps serve as inputs into a multidisciplinary landscape-level analysis of socioeconomic and ecological processes in Oregon's Coast Range Mountains. This revised version was published online in July 2006 with corrections to the Cover Date.     

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology in humid temperate forest as a function of topography. Moderate-resolution imaging spectro-radiometer (MODIS) vegetation indices are used to derive local patterns of topography-mediated vegetation phenology using a simple post-processing analysis and a non-linear model fitting. Elevation has the most explanatory power for all phenological variables with a strong linear relationship with mid-day of greenup period, following temperatures lapse rates. However, all other phenological variables show quadratic associations with elevation, reflecting an interaction between topoclimatic patterns of temperature and water availability. Radiation proxies also have significant explanatory power for all phenological variables. Though hillslope position cannot be adequately resolved at the MODIS spatial resolution (250 m) to discern impacts of local drainage conditions, extended periods of greenup/senescence are found to occur in wet years. These findings are strongly supported by previous field measurements at different topographic positions within the study area. The capability of detecting topography-mediated local phenology offers the potential to detect vegetation responses to climate change in mountainous terrain. In addition, the large, local variability of meteorological and edaphic conditions in steep terrain provides a unique opportunity to develop an understanding of canopy response to the interaction of climate and landscape conditions.     

Landscape regularity modelling for environmental challenges in agriculture

In agricultural landscapes, methods to identify and describe meaningful landscape patterns play an important role to understand the interaction between landscape organization and ecological processes. We propose an innovative stochastic modelling method of agricultural landscape organization where the temporal regularities in land-use are first identified through recognized Land-Use Successions before locating these successions in landscapes. These time–space regularities within landscapes are extracted using a new data mining method based on Hidden Markov Models. We applied this methodological proposal to the Niort Plain (West of France). We built a temporo-spatial analysis for this case study through spatially explicit analysis of Land-Use Succession dynamics. Implications and perspectives of such an approach, which links together the temporal and the spatial dimensions of the agricultural organization, are discussed by assessing the relationship between the agricultural landscape patterns defined using this approach and ecological data through an illustrative example of bird nests.