Exploring subtle land use and land cover changes: a framework for future landscape studies

Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.     

Forest recovery since 1860 in a Mediterranean region: drivers and implications for land use and land cover spatial distribution

Context

Land use and land cover (LULC) change is a major part of environmental change. Understanding its long-term causes is a major issue in landscape ecology.

Objectives

Our aim was to characterise LULC transitions since 1860 and assess the respective and changing effects of biophysical and socioeconomic drivers on forest, arable land and pasture in 1860, 1958 and 2010, and of biophysical, socioeconomic and distance from pre-existing forest on forest recovery for the two time intervals.

Methods

We assessed LULC transitions by superimposing 1860, 1958 and 2010 LULCs using a regular grid of 1 × 1 km points, in a French Mediterranean landscape (195,413 ha). We tested the effects of drivers using logistic regressions, and quantified pure and joint effects by deviance partitioning.

Results

Over the whole period, the three main LULCs were spatially structured according to land accessibility and soil productivity. LULC was driven more by socioeconomic than biophysical drivers in 1860, but the pattern was reversed in 2010. A widespread forest recovery mainly occurred on steeper slopes, far from houses and close to pre-existing forest, due to traditional practice abandonment. Forest recovery was better explained by biophysical than by socioeconomic drivers and was more dependent on distance from pre-existing forest between 1958 and 2010.

Conclusions

Our results showed a shift in drivers of LULC and forest recovery over the last 150 years. Contrary to temperate regions, the set-aside of agricultural practices on difficult land has strengthened the link between biophysical drivers and LULC distribution over the last 150 years.

     

Linking greenhouse gas emissions to urban landscape structure: the relevance of spatial and thematic resolutions of land use/cover data

Context

Emissions of greenhouse gases in urban areas play an important role in climate change. Increasing attention has been given to urban landscape structure–emission relationships (SERs). However, it remains unknown if and to what extent SERs are dependent on observational scale.

Objective

To assess how changing observational scales (in terms of spatial and thematic resolutions) of urban landscape structure affect SERs.

Methods

We examined correlations between 16 landscape metrics and greenhouse gas emissions across 52 European cities, through (1) systematic manipulation of spatial and thematic resolutions of the urban land use/cover (ULUC) dataset, and (2) comparison between available standard ULUC datasets with different spatial resolutions.

Results

Our analyses showed that the observed SERs significantly depend on both thematic and spatial resolutions of the ULUC data. For the 16 landscape metrics, we found diverse spatial/thematic scaling relations exhibiting monotonic, hump-shaped or scale-invariant trends. For different landscape metrics, the SERs were strongest at different spatial scales, suggesting that there is no consistent scaling relation over those observational scales.

Conclusions

SERs are highly sensitive to spatial and thematic resolutions of landscape data. To avoid the problem of ‘ecological fallacy,’ important caveats should be taken for interpretations based on single landscape metrics. Particular consideration should be paid to metrics that are easily interpretable, predictable in scaling behaviors, and important for shaping SERs, such as PLAND, ED, and LPI. Systematic investigations on scaling behaviors of SERs over well-defined scale domains are encouraged in future studies linking greenhouse gas emissions and urban landscape structure.

     

Estimating landscape pattern metrics from a sample of land cover

Although landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units and then selecting a subset (sample) of these units introduces artificial patch edge and patch truncation effects that may lead to biased sample-based estimators of landscape pattern metrics. The bias and variance of sample-based estimators of status and change in landscape pattern metrics were evaluated for four 120-km × 120-km test regions with land cover provided by the 1992 and 2001 National Land-Cover Data of the United States. Bias was generally small for both the estimators of status and estimators of change in landscape pattern, but exceptions to this favorable result exist and it is advisable to assess bias for the specific metrics and region of interest in any given application. A 10-km × 10-km sample block generally yielded larger biases but smaller variances for the estimators relative to a 20-km × 20-km sample block. Stratified random sampling improved precision of the estimators relative to simple random sampling. The methodology developed to determine properties of sample-based estimators can be readily extended to evaluate other landscape pattern metrics, regions, and sample block sizes.     

Modeling landscape structure response across a gradient of land cover intensity

Landscape Ecology - Quantitative analyses in landscape ecology have traditionally been dominated by the patch-mosaic concept in which landscapes are modeled as a mosaic of discrete patches. This...     

The importance of landscape context for songbirds on migration: body mass gain is related to habitat cover

Landscape context influences many aspects of songbird ecology during the breeding season. The importance of landscape context at stopover sites for migrating songbirds, however, has received less attention. In particular, landscape context may affect the availability and quality of food for refueling during stopovers, which is critical for successful migration. We evaluated the influence of woody habitat cover in the surroundings of stopover sites at several spatial extents on the hourly changes of body mass in two species of European-African forest-dwelling songbird migrants (Willow Warbler, Phylloscopus trochilus, and the Eurasian Redstart, Phoenicurus phoenicurus). Data were sampled by standardized methods from a network of ringing stations throughout Europe during the falls of 1994–1996. In both species, hourly body mass gain calculated for first captures increased with woody habitat cover. We found a similar logarithmic relationship for both species, although for Willow Warblers mass gain was more strongly related to the habitat cover within 5 km, in contrast to 3 km for Redstarts. For Willow Warblers, where sufficient data are available for each year, the relationship is consistent over the years. The shape of the relationship suggests existence of a threshold of landscape suitability for refueling at stopover sites: in sites with less than 10% of woody habitat cover, birds tend to lose body mass or to gain mass at a lower rate. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Expert knowledge for translating land cover/use maps to General Habitat Categories (GHC)

Monitoring biodiversity at the level of habitats and landscape is becoming widespread in Europe and elsewhere as countries establish international and national habitat conservation policies and monitoring systems. Earth Observation (EO) data offers a potential solution to long-term biodiversity monitoring through direct mapping of habitats or by integrating Land Cover/Use (LC/LU) maps with contextual spatial information and in situ data. Therefore, it appears necessary to develop an automatic/semi-automatic translation framework of LC/LU classes to habitat classes, but also challenging due to discrepancies in domain definitions. In the context of the FP7 BIO_SOS (www.biosos.eu) project, the authors demonstrated the feasibility of the Food and Agricultural Organization Land Cover Classification System (LCCS) taxonomy to habitat class translation. They also developed a framework to automatically translate LCCS classes into the recently proposed General Habitat Categories classification system, able to provide an exhaustive typology of habitat types, ranging from natural ecosystems to urban areas around the globe. However discrepancies in terminology, plant height criteria and basic principles between the two mapping domains inducing a number of one-to-many and many-to-many relations were identified, revealing the need of additional ecological expert knowledge to resolve the ambiguities. This paper illustrates how class phenology, class topological arrangement in the landscape, class spectral signature from multi-temporal Very High spatial Resolution (VHR) satellite imagery and plant height measurements can be used to resolve such ambiguities. Concerning plant height, this paper also compares the mapping results obtained by using accurate values extracted from LIght Detection And Ranging (LIDAR) data and by exploiting EO data texture features (i.e. entropy) as a proxy of plant height information, when LIDAR data are not available. An application for two Natura 2000 coastal sites in Southern Italy is discussed.     

The impact of land use/land cover scale on modelling urban ecosystem services

Context

Urbanisation places increasing stress on ecosystem services; however existing methods and data for testing relationships between service delivery and urban landscapes remain imprecise and uncertain. Unknown impacts of scale are among several factors that complicate research. This study models ecosystem services in the urban area comprising the towns of Milton Keynes, Bedford and Luton which together represent a wide range of the urban forms present in the UK.

Objectives

The objectives of this study were to test (1) the sensitivity of ecosystem service model outputs to the spatial resolution of input data, and (2) whether any resultant scale dependency is constant across different ecosystem services and model approaches (e.g. stock- versus flow-based).

Methods

Carbon storage, sediment erosion, and pollination were modelled with the InVEST framework using input data representative of common coarse (25 m) and fine (5 m) spatial resolutions.

Results

Fine scale analysis generated higher estimates of total carbon storage (9.32 vs. 7.17 kg m^?2) and much lower potential sediment erosion estimates (6.4 vs. 18.1 Mg km^?2 year^?1) than analyses conducted at coarser resolutions; however coarse-scale analysis estimated more abundant pollination service provision.

Conclusions

Scale sensitivities depend on the type of service being modelled; stock estimates (e.g. carbon storage) are most sensitive to aggregation across scales, dynamic flow models (e.g. sediment erosion) are most sensitive to spatial resolution, and ecological process models involving both stocks and dynamics (e.g. pollination) are sensitive to both. Care must be taken to select model data appropriate to the scale of inquiry.

     

Linking land change model evaluation to model objective for the assessment of land cover change impacts on biodiversity

Landscape Ecology - Evaluation of land cover change (LCC) is commonly done at the pixel level; however, the model’s purpose may be relevant at a different grain size. Thus, the same...     

Influences of habitat and land cover on fish distributions along a tributary to Lake Ontario,New York

Influences of habitat and land cover on fish distributions were determined along a lentic–lotic gradient along a tributary to Lake Ontario, New York. Nonmetric multidimensional scaling, cluster analysis, and specific characterization methods were used to classify the fish species into five groups based on their similar patterns of distribution, species-specific habitat relationship, and relative abundance observed along the gradient. A stepwise regression approach was used to select the best habitat and land cover variables to explain variations in the distribution pattern of each fish group. Distribution patterns of the five fish groups were significantly explained by either a set of the selected habitat or land cover predictor variables or a combination of both. Of the 10 habitat variables, water depth, current velocity, aquatic plants, algae, woody debris, sand, and rock-bedrock were selected to explain the variations in distribution patterns of one or more fish groups. Of the 16 land cover types, evergreen wetlands, evergreen plantations, successional shrubs, shrub swamps, roads, and urban areas were selected to explain the variations in distribution patterns of at least one fish group.     

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services.     

Variations in landscape patterns and vegetation cover between 1957 and 1994 in a semiarid Mediterranean ecosystem

The aim of this study was to analyze the main processes that determine changes in landscape patterns and vegetation cover from 1957-1994 to develop a model for land cover dynamics. Land cover and landscape patterns were assessed and compared using aerial photographs taken in 1957, 1985, and 1994. Over this period, tall grass steppe and arid garrigues increased by 6% and 4%, respectively, while crop fields decreased by 15% and tall arid brush remained the same. Over the same period, tall grass steppes and arid garrigues became less fragmented.Changes in land use were triggered by socioeconomic forces, which were constrained by the underlying structure of the physical landscape. The best preserved vegetation (tall arid brushes) was concentrated at higher elevations, with a pronounced slope, not oriented towards the sea, and in volcanic substrate. Communities tended to be better preserved further away from towns and at lower house densities. Tall grass steppe was present on more gradual sea-oriented slope and in calcareous substrate, and increased at higher elevations, although not far from the town but away from high anthropogenic influence. Previous studies have revealed that traditional land uses of this landscape, particularly grazing, favoured the transition from tall arid brush to tall grass steppe. In this study, we analyzed to what extent the underlying structure of the physical landscape imposes limitations to the vulnerability to human activity of the main vegetation types. According to the data on the probability of vegetation transition over the 37-year period, the shift from tall arid brush to tall grass steppe appeared to be favoured by gradual slopes. Tall arid brush recovered from either arid garrigues or tall grass steppes at steeper slopes. Thus, steep terrain had a favourable effect on the formation of brushwood and more gradual terrain favoured tall grass steppe. The prevalent trends were confirmed by a projection of a transition matrix over 100 years.This revised version was published online in May 2005 with corrections to the Cover Date.     

An investigation of uncertainty in field habitat mapping and the implications for detecting land cover change

Land cover data for landscape ecological studies are frequently obtained by field survey. In the United Kingdom, temporally separated field surveys have been used to identify the locations and magnitudes of recent changes in land cover. However, such map data contain errors which may seriously hinder the identification of land cover change and the extent and locations of rare landscape features. This paper investigates the extent of the differences between two sets of maps derived from field surveys within the Northumberland National Park in 1991 and 1992. The method used in each survey was the Phase 1 approach of the Nature Conservancy Council of Great Britain. Differences between maps were greatest for the land cover types with the smallest areas. Overall spatial correspondence between maps was found to be only 44.4%. A maximum of 14.4% of the total area surveyed was found to have undergone genuine land cover change. The remaining discrepancies, equivalent to 41.2% of the total survey area, were attributed primarily to differences of land cover interpretation between surveyors (classification error). Differences in boundary locations (positional error) were also noted, but were found to be a relatively minor source of error. The implications for the detection of land cover change and habitat mapping are discussed.     

Predation risk across a dynamic landscape: effects of anthropogenic land use,natural landscape features,and prey distribution

Purpose

Human-mediated landscape changes alter habitat configuration, which strongly structures animal distributions and interspecific interactions. The effects of anthropogenic disturbance on predator–prey relationships are fundamental to ecology, yet less well understood. We determined where predation events occurred for fawn and adult female mule deer from 2008 to 2014 in critical winter range with extensive energy development. We investigated the relationship between predation sites, energy infrastructure, and natural landscape features across contiguous areas experiencing different degrees of energy extraction during periods of high and low intensity development.

Methods

We contrast spatial correlates of 286 mortality locations with random landscape locations and mule deer distribution estimated from 350,000 GPS locations. We estimated predation risk with resource selection functions and latent selection difference functions.

Results

Relative to the distribution of mule deer, predation risk was lower closer to pipelines and well pads, but higher closer to roads. Predation sites occurred more than expected relative to availability and deer distribution in deeper snow and non-forested habitats. Anthropogenic features had a greater influence on predation sites during the period of low activity than high activity, and natural landscape characteristics had weaker effects relative to anthropogenic features throughout the study. Though canids accounted for the majority of predation events, felids exhibited stronger landscape associations, driving the observed spatial patterns in predation risk to mule deer.

Conclusions

The emergence of varied interactions between predation and landscape features across contexts and years highlights the complexity of interspecific interactions in highly modified landscapes.

     

The role of land use and land cover change in climate change vulnerability assessments of biodiversity: a systematic review

Landscape Ecology - For many organisms, responses to climate change (CC) will be affected by land-use and land-cover changes (LULCC). However, the extent to which LULCC is concurrently...     

Predicting land use change: comparison of models based on landowner surveys and historical land cover trends

To make informed planning decisions, community leaders, elected officials, scientists, and natural resource managers must be able to evaluate potential effects of policies on land use change. Many land use change models use remotely-sensed images to make predictions based on historical trends. One alternative is a survey-based approach in which landowners’ stated intentions are modeled. The objectives of our research were to: (1) develop a survey-based landowner decision model (SBM) to simulate future land use changes, (2) compare projections from the SBM with those from a trend-based model (TBM), and (3) demonstrate how two alternative policy scenarios can be incorporated into the SBM and compared. We modeled relationships between land management decisions, collected from a mail survey of private landowners, and the landscape, using remotely-sensed imagery and ownership parcel data. We found that SBM projections were within the range of TBM projections and that the SBM was less affected by errors in image classification. Our analysis of alternative policies demonstrates the importance of understanding potential effects of targeted land use policies. While policies oriented toward increasing enrollment in the Conservation Reserve Program (CRP) resulted in a large (11–13%) increase in CRP lands, policies targeting increased forest thinning on private non-industrial lands increased low-density forest projections by only 1%. The SBM approach is particularly appropriate for landscapes including many landowners, because it reflects the decision-making of the landowners whose individual actions will result in collective landscape change.     

Empirical relationships between land use/cover and estuarine condition in the Northeastern United States

Land–water interactions were examined in three regions in the Virginian Biogeographic Province; the southern shore of Cape Cod, Massachusetts; the Hudson/Raritan region of New York; and the eastern shore of the Delmarva (Delaware/Maryland/Virginia) Peninsula. Cumulative distribution functions were used to evaluate similarity in environmental condition among estuaries. Spatial-setting variables (location in a river, coastal lagoon, or in open waters) were associated with variation for some measures of estuarine condition. Patterns of coastal urban and agriculture gradients were measured and their relationship with indicators of estuarine condition was modeled statistically. When estuaries were pooled, the highest variation explained by spatial-setting variables was found for dissolved oxygen (DO, R ² = 0.44) and salinity (R ² = 0.58), with DO decreasing in river locations and salinity decreasing with rainfall and sampling locations near rivers. The explanatory power for the other indicator variables was low and varied from 6% to 27%. Rainfall explained some of the variation (R ² = 0.23) in total suspended solids. Moderate (0.4 < | r | < 0.7) to strong (| r | ≥ 0.7) linear associations were found between total urban area and measures of estuarine condition. Within regions, total urban area was positively associated with Silver (r = 0.59), Cadmium (r = 0.65), and Mercury (r = 0.47) in Cape Cod, and inversely related to DO (r = −0.65) in the Hudson/Raritan region. No associations were found in the Delmarva Peninsula study area. Total area of agriculture showed a moderate association with Arsenic in Cape Cod, but no other associations were found in the other two regions. Our analyses show a measurable impact of urban land use on coastal ecosystem condition over large areas of the northeastern United States. This pattern was most evident when many different landscapes were considered simultaneously. The relationship between urban development and estuarine condition were weaker within the individual regions studied. The use of land use/cover models for predicting estuarine condition is a challenging task that warrants enhancements in the type, quantity, and quality of data to improve our ability to discern relationships between anthropogenic activities on land and the condition of coastal environments.