Context

The positive correlation between landscape area of semi-natural habitat and wild pollinator richness and abundance in agroecosystems has been well studied. However, we lack a deep understanding of local scale floral resource and nest provisioning for wild bees necessary to optimize implementation of pollinator conservation practices.

Objectives

The primary objective of this study was to use a spatially interactive landscape pollination model (hereafter, the Lonsdorf model) to represent field scale spatial patterns of wild bee abundance and richness within a heterogeneous landscape in the mid-Atlantic USA.

Methods

We parameterized the Lonsdorf model with high resolution aerial imagery and insight from a previously published floristic study. To test the Lonsdorf model predictions, field studies were conducted to measure wild bee abundance and species richness in apple orchards as a function of distance from a forest edge.

Results

Field measurements indicated apple pollinator abundance and species richness significantly decreased with increasing distance from the forest edge. The Lonsdorf model pollination service score was highly sensitive to changes in resource provisioning in orchard and non-crop areas, and including resource rich forest and forest edge habitats in the model significantly improved pollination service estimates.

Conclusions

We demonstrated a novel application of the Lonsdorf model at a field scale to predict trends in pollination service provisioning as a factor of local habitat features. With sufficiently detailed inputs, the Lonsdorf model is a promising tool to quantify field scale pollination service deficits, guiding more cost effective habitat supplementation and other conservation efforts.

Context

An ecosystem service approach for land-use or conservation decisions normally uses economic or biophysical assessments for valuating nature’s services. In contrast, even though ecosystem services are required for human well-being, the actual use of services by differing stakeholder groups are rarely considered in typical ecosystem service assessments, especially the more intangible, cultural ecosystem services.

Objectives

The aim of this research was to quantify different uses for 15 cultural and provisioning ecosystem service indicators across seven stakeholder groups in a watershed proposed with large hydroelectric dam development.

Methods

We used a large-scale survey to quantify use and frequency of use for ecosystem services.

Results

We demonstrate that different stakeholder groups use ecosystem services differently, both in terms of specific ecosystem service indicators, as well as for frequency of ecosystem service use. Across all stakeholder groups, specific cultural ecosystem services were consistently more important to participants when compared to provisioning ecosystem services, especially aesthetic/scenic values.

Conclusions

This work is of global importance as it highlights the importance of considering cultural ecosystem services (e.g. aesthetic/scenic, sense-of-place values) along with multiple stakeholder groups to identify the trade-offs and synergies during decision-making processes for land-use or conservation initiatives.

Context

Policy decisions form a major driver of land use change, with important implications for socially and environmentally susceptible regions. It is well known that there can be major unintended consequences, especially where policies are not tailored to regionally specific contexts.

Objectives

In this paper we assess the implications of 60 years of agricultural policies on soil erosion prevention (SEP) by vegetation, an essential regulating ecosystem service in Mediterranean Europe.

Methods

To assess these implications we produced and analysed a time series of land cover/use and environmental conditions datasets (from 1951 to 2012) in relation to changing agricultural policies for a specific region in the southern Portugal. A set of indicators related to SEP allowed us to identify that land use intensification as increased soil erosion in the last 60 years.

Results

Particularly in the last 35 years, as a consequence of headage payments for cattle, the agricultural policy had a significant effect in the density and renewal of the tree cover, resulting in drastic effects for the provision of the SEP service. These are more significant after 1986, coinciding with the implementation of several Common Agricultural Policy instruments focused on increasing the modernization and productivity capacity of farm systems.

Conclusions

The results show some unintended effects of agricultural policy mechanisms on ecosystem service provision and highlight the need for context-based policies, tailored to the environmental constrains and potentials of each region.

Context

The variation in spatial distribution between ecosystem services can be high. Hence, there is a need to spatially identify important sites for conservation planning. The term ‘ecosystem service hotspot’ has often been used for this purpose, but definitions of this term are ambiguous.

Objectives

We review and classify methods to spatially delineate hotspots. We test how spatial configuration of hotspots for a set of ecosystem services differs depending on the applied method. We compare the outcomes to a heuristic site prioritisation approach (Marxan).

Methods

The four tested hotspot methods are top richest cells, spatial clustering, intensity, and richness. In a conservation scenario we set a target of conserving 10 % of the quantity of five regulating and cultural services for the forest area of Telemark county, Norway.

Results

Spatial configuration of selected areas as retrieved by the four hotspots and Marxan differed considerably. Pairwise comparisons were at the lower end of the scale of the Kappa statistic (0.11–0.27). The outcomes also differed considerably in mean target achievement, cost-effectiveness in terms of land-area needed per unit target achievement and compactness in terms of edge-to-area ratio.

Conclusions

An ecosystem service hotspot can refer to either areas containing high values of one service or areas with multiple services. Differences in spatial configuration among hotspot methods can lead to uncertainties for decision-making. This also has consequences for analysing the spatial co-occurrence of hotspots of multiple services and of services and biodiversity.

Context

During the past three decades, China’s agroecosystem has undergone dramatic alterations because of changes in climatic and management factors, which threatened agricultural sustainability.

Objectives

We investigated how climatic and management factors affected agricultural ecosystem services (AES).

Methods

We adopted the GIS-based Environmental Policy Integrated Climate (EPIC) model to simulate the five critical AES: food production, soil organic carbon (SOC), nitrate leaching, water erosion, and wind erosion from 1980 to 2010 and used a partial least square regression model to quantify the contributions of the drivers of the variation in the AES on the main grain-producing area (MGPA), climatic zone, and national scales.

Results

On the MGPA scale, SOC exhibited no obvious change and food production increased, whereas the negative environmental effects largely increased. The MGPA is important to ensure the safety of China’s food supply. At the climatic zone scale, food production and SOC increased, water erosion in the tropical-subtropical monsoonal zone and water and wind erosion in the temperate monsoonal zone decreased, whereas N leaching, water erosion, and wind erosion increased in other climate zones. At the national scale, food production, SOC, N leaching, and wind erosion increased, whereas water erosion decreased. The crop cultivated area played a major role in the effect on food production and SOC. The dominant factors for N leaching, water erosion, and wind erosion varied with crop type and study scales.

Conclusions

Adjustment of agricultural management measures is vital and possible to minimize the tradeoffs, increase the synergies among agro ecosystem services, and promote adaptation to the changing climate.

Context

Landscape metrics represent powerful tools for quantifying landscape structure, but uncertainties persist around their interpretation. Urban settings add unique considerations, containing habitat structures driven by the surrounding built-up environment. Understanding urban ecosystems, however, should focus on the habitats rather than the matrix.

Objectives

We coupled a multivariate approach with landscape metric analysis to overcome existing shortcomings in interpretation. We then explored relationships between landscape characteristics and modelled ecosystem service provision.

Methods

We used principal component analysis and cluster analysis to isolate the most effective measures of landscape variability and then grouped habitat patches according to their attributes, independent of the surrounding urban form. We compared results to the modelled provision of three ecosystem services. Seven classes resulting from cluster analysis were separated primarily on patch area, and secondarily by measures of shape complexity and inter-patch distance.

Results

When compared to modelled ecosystem services, larger patches up to 10 ha in size consistently stored more carbon per area and supported more pollinators, while exhibiting a greater risk of soil erosion. Smaller, isolated patches showed the opposite, and patches larger than 10 ha exhibited no additional areal benefit.

Conclusions

Multivariate landscape metric analysis offers greater confidence and consistency than analysing landscape metrics individually. Independent classification avoids the influence of the urban matrix surrounding habitats of interest, and allows patches to be grouped according to their own attributes. Such a grouping is useful as it may correlate more strongly with the characteristics of landscape structure that directly affect ecosystem function.

Context

In modern agricultural landscapes, fragmentation of partial habitats is a significant filter for multi-habitat users, reducing local taxonomic and functional diversity. There is compelling evidence that small species are more susceptible than large species. The impact of habitat fragmentation on intraspecific body-size distribution, however, is yet unexplored.

Objectives

We tested habitat fragmentation, a major driver of pollinator loss, for its impact on intraspecific body-size distributions of solitary wild-bee species. Subsequently, we tested individual body size for its impact on pollination services.

Methods

We sampled 1272 individuals of the four most common Andrena wild bee species in 22 newly established flowering fields (0.21–0.41 ha) in Hessen, Central Germany, over two consecutive years. Study sites were located in a ca. 80 ha landscape context of increasing habitat fragmentation. We analysed the pollen loads of the most abundant species.

Results

Body size within local populations of the two medium-sized bees increased with fragmentation, suggesting intraspecific selection for higher dispersal capacity. Pollen analysis carried out for the most common species revealed that larger individuals visited a significantly smaller plant spectrum. Habitat fragmentation may thus alter pollination services without necessarily affecting species richness or composition.

Conclusions

Systematic body-size variation at the population level thus explains the considerable variability between simple community measures and ecosystem functioning. Filtering processes at the individual level require increased understanding for targeting pollination services under current and future land-use change.

Context

Although there is a need to develop a spatially explicit methodological approach that addresses the social importance of cultural ecosystem services for regional planning, few studies have analysed the spatial distribution on the cultural ecosystem services based on social perceptions.

Objective

The main objective of this study was to identify cultural ecosystem service hot-spots, and factors that characterize such hot-spots and define the spatial associations between cultural ecosystem services in Southern Patagonia (Argentina).

Methods

The study was carried out in Southern Patagonia (243.9 thousand km²) located between 46° and 55° SL with the Andes mountains on the western fringe and the Atlantic Ocean on the eastern fringe of the study area. The study region has a range of different vegetation types (grasslands, shrub-lands, peat-lands and forests) though the cold arid steppe is the main vegetation type. We used geo-tagged digital images that local people and visitors posted in the Panoramio web platform to identify hot-spots of four cultural ecosystem services (aesthetic value, existence value, recreation and local identity) and relate these hot-spots with social and biophysical landscape features.

Results

Aesthetic value was the main cultural service tagged by people, followed by the existence value for biodiversity conservation, followed by local identity and then recreational activity. The spatial distribution of these cultural ecosystem services are associated with different social and biophysical characteristics, such as the presence of water bodies, vegetation types, marine and terrestrial fauna, protected areas, urbanization, accessibility and tourism offer. The most important factors are the presence of water in Santa Cruz and tourism offer in Tierra del Fuego.

Conclusions

Our results demonstrate that this methodology is useful for assessing cultural ecosystem services at the regional scale, especially in areas with low data availability and field accessibility, such as Southern Patagonia. We also identify new research challenges that can be addressed in cultural ecosystem services research through the use of this method.

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.

Context

Understanding how urban impervious surfaces (UIS) affect land surface temperatures (LST) on different scales in space and time is important for urban ecology and sustainability.

Objectives

We examined how spatial scales, seasonal and diurnal variations, and bioclimatic settings affected the UIS–LST relationship in mainland China.

Methods

We took a hierarchical approach explicitly considering three scales: the ecoregion, urban cluster, and urban core. The UIS–LST relationship was quantified with Pearson correlation using multiple remote sensing datasets.

Results

In general, UIS and LST were positively correlated in summer daytime/nighttime and winter nighttime, but negatively in winter daytime. The strength of correlation increased from broad to fine scales. The mean R² of winter nights at the urban core scale (0.262) was 4.03 times as high as that at the ecoregion scale (0.065). The relationship showed large seasonal and diurnal variations: generally stronger in summer than in winter and stronger in nighttime than in daytime. At the urban core scale, the mean R² of summer daytime (0.208) was 3.25 times as high as that of winter daytime (0.064), and the mean R² of winter nighttime (0.262) was 4.10 times as high as that of winter daytime (0.064). Vegetation and climate substantially modified the relationship during summer daytime on the ecoregion scale.

Conclusions

Our study provides new evidence that the UIS–LST relationship varies with spatial scales, diurnal/seasonal cycles, and bioclimatic context, with new insight into the cross-scale properties of the relationship. These findings have implications for mitigating urban heat island effects across scales in China and beyond.

Context

Dramatic land-use change has taken place in the tropical region of southwestern China. However, quantitative evaluation of changes in landscape sustainability and the provision of biodiversity ecosystem services (BESVs) of the region has seldom been attempted.

Objectives

This study was designed to: (1) assess bioenergy landscape dynamics based on graph theory; (2) predict bioenergy landscape sustainability in response to land-use changes, and (3) explore the effects of land-use changes on BESVs’ variation based on bioenergy modeling.

Methods

The PANDORA model, a bioenergy-based integrated evaluation of BESV related to landscape connectivity, was employed to analyze variations in landscape’s bioenergy and BESV in Jinghong County, southwestern China. In addition, we applied this model and several indices (change extent, change rate, and growth type) to evaluate responses of bioenergy and BESV to land-use changes.

Results

The bioenergy and bioenergy fluxes of the regional landscape have decreased since the 1970s, while the landscape has remained sustainable with a high level of bioenergy. The BESVs overall fluctuated from $8.41 m^?2 year^?1 in the 1970s to $8.54, 7.45, and 5.71 m^?2 year^?1 in 1990, 2000, and 2010, respectively. Further, both changes in the land-use area and patterns, including change extent, change rate, and change pattern, affected the variation in BESVs.

Conclusions

The PANDORA model can evaluate bioenergy dynamics, sustainability, and BESV variations on the landscape scale effectively. Further, the BESV is sensitive to changes in landscape composition and pattern, and thus, increasing natural vegetation and landscape connectivity could improve provisions to conserve the landscape’s biodiversity.

Context

Tropical forest regeneration is increasingly prominent as agro-pastoral lands are abandoned. Regeneration is characterised as favouring ‘marginal’ lands; however, observations of its drivers are often coarse or simple, leaving doubt as to spatial dynamics and causation.

Objectives

We quantified the spatial dynamics of forest regeneration relative to marginality and remnant forest cover in a 3000 km² pastoral region in northern tropical Australia.

Methods

Classification and regression trees related the extent and distribution of regeneration to soil agricultural potential, land-cover history, terrain slope, distance to primary forest, and primary forest fragment size, as defined by aerial photography.

Results

Secondary forest extent and distribution overwhelmingly reflect the proximity and size of primary forest fragments. Some 85 % of secondary forest area occurs <1 km of primary forest, and 86 % of secondary forest patches >50 ha are <400 m from primary forest and coincident with historic primary forest fragments. Where primary forest fragments are >8.5 ha, secondary forest area declines less rapidly with increasing distance from primary forest up to 1.5 km. Marginality inferred by soil potential and slope had no bearing on regeneration, except at the coarsest of spatial scales where regeneration is a proxy for primary forest cover.

Conclusion

Findings underline the need to conserve even modest rainforest patches as propagule reservoirs enabling regeneration. Marginality per se may have a limited role in regeneration. As most secondary forest was an extension of primary forest, its unique conservation value relative to that of primary forest may likewise merit reconsideration.

Context

Traditionally soils have not received much attention in urban planning. For this, tools are needed that can both be understood both by soil scientists and urban planners.

Purpose

The purpose of this paper is to enhance the role of soil knowledge in urban planning practice, through the following objectives: (1) identifying the role soil plays in recent urban plans; (2) analysing the ecosystem services and indicators used in soil science in an urban context; and (3) inferring the main challenges and opportunities to integrate soil into urban planning.

Methods

Seven urban plans and reports of world cities that include sustainability goals were analysed using text-mining and qualitative analysis, with a critical view on the inclusion of soil-related concepts. Secondly, the contribution of soil science to urban planning was assessed with an overview of case studies in the past decade that focus on soil-related ecosystem services in urban context.

Results

The results show an overall weak attention to soil and soil-related ecosystem services in the implementation and monitoring phases of urban plans. The majority of soil science case studies uses a haphazard approach to measure ecosystem service indicators which may not capture the ecosystem services appropriately and hence lack relevance for urban planning.

Conclusions

Even though the most urban plans assessed recognize soil as a key resource, most of them fail to integrate indicators to measure or monitor soil-related functions. There is a need to develop soil-related ecosystem services that can be easily integrated and understood by other fields.

Context

With global change, microclimates become important refuges for temperature-sensitive, range-restricted organisms. In African savannas, woody vegetation on Macrotermes mounds create widely-dispersed microclimates significantly cooler than the surrounding matrix, which buffer against elevated temperatures at the finer scale of mounds, allowing species to persist at the landscape scale. Termite colonies cultivate symbiotic fungi to digest lignin, but the fungi require temperatures between 29 and 32 °C, which termites strive to maintain. Mound-associated vegetation is a hot-spot for elephant herbivory, so removal of woody species cover by elephants could influence mound-associated microclimates, impacting temperature regulation by termites.

Objectives

We explored the interaction between two prominent ecosystem engineers (termites and elephants) to ascertain whether elephant removal of mound woody cover affects (1) external mound-associated microclimate and (2) internal mound temperature.

Methods

We surveyed 44 mounds from three sites in Kruger National Park, South Africa, during an El Niño/Southern Oscillation-induced drought and heatwave, recording whether sub-canopy, external, mound-surface and internal mound temperatures varied with vegetation removal by elephant.

Results

Elephant damage to mound-associated vegetation reduces the fine-scale microclimate effect provided by vegetation on Macrotermes mounds. Despite this, termites were able to regulate internal mound temperatures, whereas internal temperatures of abandoned mounds increased with elevated surface temperatures.

Conclusions

Termites can persist despite loss of mound-associated microclimates, but the loss likely increases energetic costs of mound thermoregulation. Since mound vegetation buffers against drought, loss of widely-dispersed, fine-scale microclimates could increase as megaherbivores remain constrained to protected areas, impacting climate-sensitive organisms and ecosystem function at a range of scales.

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.

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.

Context

Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods.

Objectives

We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California.

Methods

A forest AGB map of a 143 km² area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified.

Results

The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60–90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation.

Conclusions

A spatial scale of 60–90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions.

Context

The Mongolian Plateau, comprising Inner Mongolia, China (IM) and Mongolia (MG) is undergoing consistent warming and accelerated land cover/land use change. Extensive modifications of water-limited regions can alter ecosystem function and processes; hence, it is important to differentiate the impacts of human activities and precipitation dynamics on vegetation productivity.

Objectives

This study distinguished between human-induced and precipitation-driven changes in vegetation cover on the plateau across biome, vegetation type and administrative divisions.

Methods

Non-parametric trend tests were applied to the time series of vegetation indices (VI) derived from MODIS and AVHRR and precipitation from TRMM and MERRA reanalysis data. VI residuals adjusted for rainfall were obtained from the regression between growing season maximum VI and monthly accumulated rainfall (June–August) and were used to detect human-induced trends in vegetation productivity during 1981–2010. The total livestock and population density trends were identified and then used to explain the VI residual trends.

Results

The slope of precipitation-adjusted EVI and EVI2 residuals were negatively correlated to total livestock density (R² = 0.59 and 0.16, p < 0.05) in MG and positively correlated with total population density (R² = 0.31, p < 0.05) in IM. The slope of precipitation-adjusted EVI and EVI2 residuals were also negatively correlated with goat density (R² = 0.59 and 0.19, p < 0.05) and sheep density in MG (R² = 0.59 and 0.13, p < 0.05) but not in IM.

Conclusions

Some administrative subdivisions in IM and MG showed decreasing trends in VI residuals. These trends could be attributed to increasing livestock or population density and changes in livestock herd composition. Other subdivisions showed increasing trends residuals, suggesting that the vegetation cover increase could be attributed to conservation efforts.

Context

We address the issue of adapting landscapes for improved insect biodiversity conservation in a changing climate by assessing the importance of additive (main) and synergistic (interaction) effects of land cover and land use with climate.

Objectives

We test the hypotheses that ant richness (species and genus), abundance and diversity would vary according to land cover and land use intensity but that these effects would vary according to climate.

Methods

We used a 1000 m elevation gradient in eastern Australia (as a proxy for a climate gradient) and sampled ant biodiversity along this gradient from sites with variable land cover and land use.

Results

Main effects revealed: higher ant richness (species and genus) and diversity with greater native woody plant canopy cover; and lower species richness with higher cultivation and grazing intensity, bare ground and exotic plant groundcover. Interaction effects revealed: both the positive effects of native plant canopy cover on ant species richness and abundance, and the negative effects of exotic plant groundcover on species richness were greatest at sites with warmer and drier climates.

Conclusions

Impacts of climate change on insect biodiversity may be mitigated to some degree through landscape adaptation by increasing woody native vegetation cover and by reducing land use intensity, the cover of exotic vegetation and of bare ground. Evidence of synergistic effects suggests that landscape adaptation may be most effective in areas which are currently warmer and drier, or are projected to become so as a result of climate change.

Context

Arid rangelands have been severely degraded over the past century. Multi-temporal remote sensing techniques are ideally suited to detect significant changes in ecosystem state; however, considerable uncertainty exists regarding the effects of changing image resolution on their ability to detect ecologically meaningful change from satellite time-series.

Objectives

(1) Assess the effects of image resolution in detecting landscape spatial heterogeneity. (2) Compare and evaluate the efficacy of coarse (MODIS) and moderate (Landsat) resolution satellite time-series for detecting ecosystem change.

Methods

Using long-term (~12 year) vegetation monitoring data from grassland and shrubland sites in southern New Mexico, USA, we evaluated the effects of changing image support using MODIS (250-m) and Landsat (30-m) time-series in modeling and detecting significant changes in vegetation using time-series decomposition techniques.

Results

Within our study ecosystem, landscape-scale (>20-m) spatial heterogeneity was low, resulting in a similar ability to detect vegetation changes across both satellite sensors and levels of spatial image support. While both Landsat and MODIS imagery were effective in modeling temporal dynamics in vegetation structure and composition, MODIS was more strongly correlated to biomass due to its cleaner (i.e., fewer artifacts/data gaps) 16-day temporal signal.

Conclusions

The optimization of spatial/temporal scale is critical in ensuring adequate detection of change. While the results presented in this study are likely specific to arid shrub-grassland ecosystems, the approach presented here is generally applicable. Future analysis is needed in other ecosystems to assess how scaling relationships will change under different vegetation communities that range in their degree of landscape heterogeneity.