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.

     

Effect of spatial image support in detecting long-term vegetation change from satellite time-series

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.

     

An Introduction and Practical Guide to Use of the Soil-Vegetation Inventory Method (SVIM) Data

Long-term vegetation dynamics across public rangelands in the western United States are not well understood because of the lack of large-scale, readily available historic datasets. The Bureau of Land Management’s Soil-Vegetation Inventory Method (SVIM) program was implemented between 1977 and 1983 across 14 western states, but the data have not been easily accessible. We introduce the SVIM vegetation cover dataset in a georeferenced, digital format; summarize how the data were collected; and discuss potential limitations and biases. We demonstrate how SVIM data can be compared with contemporary monitoring datasets to quantify changes in vegetation associated with wildfire and the abundance of exotic invasive species. Specifically, we compare SVIM vegetation cover data with cover data collected by BLM’s Assessment, Inventory, and Monitoring (AIM) program (2011–2016) in a focal area in the northern Great Basin. We address issues associated with analyzing and interpreting data from these distinct programs, including differences in survey methods and potential biases introduced by spatial and temporal variation in sampling. We compared SVIM and AIM survey methods at 44 plots and found that percent cover estimates had high correspondence for all measured functional groups. Comparisons between historic SVIM data and recent AIM data documented significant declines in the occupancy and cover of native shrubs and native perennial forbs, and a significant increase in exotic annual forbs. Wildfire was a driver of change for some functional groups, with greater change occurring in AIM plots that burned between the two time periods compared with those that did not. Our results are consistent with previous studies showing that many native shrub-dominated plant communities in the Great Basin have been replaced by exotic annuals. Our study demonstrates that SVIM data will be an important resource for researchers interested in quantifying vegetation change through time across public rangelands in the western United States.     

THE PATH OF CARBON IN PHOTOSYNTHESIS. XXVII. SUGAR-CONJUGATED PLANT GROWTH REGULATORS ENHANCE GENERAL PRODUCTIVITY

We have found that applications of sugar-conjugated plant growth regulators (SPGRs) by exposures of roots or shoots to millimolar (mM) SPGRs are key to their uptake and transport for enhancement of vegetative productivity of the entire plant as compared to control populations. Initial surveys utilizing foliar applications of identically nutrient-supplemented 0.3 mM cytokinin glycosides, N⁶-benzyladenine glycosides, kinetin glycosides; and a 0.3 mM auxin glycoside, indoxyl-β-D-glucopyranoside (IG) resulted in significant shoot enhancements over controls. Foliar application of 0.3 mM kinetin glucoside resulted in significant root increase above the control. Foliar application of 3 mM to 6 mM IG resulted in enhanced root and shoot growths over controls. Similarly, increases of root and shoot yields over controls were observed as a result of foliar application of 3 mM indoxyl-β-D-glucuronide. Foliar application of 1 mM trans-zeatin-β-D-glucoside was particularly effective, resulting in significant enhancement of root and shoot growth with no phytotoxicity.     

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