Unpacking Pandora’s box: Understanding and categorising ecosystem disservices for environmental management and human wellbeing
- Authors: Shackleton, Charlie M , Ruwanza, Sheunesu , Sinasson Sanni, Gisele , Bennett, S , De Lacy, Peter , Modipa, Rebone D , Mtati, Nosiseko , Sachikonye, Mwazvita T B , Thondhlana, Gladman
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/182113 , vital:43801 , xlink:href="https://doi.org/10.1007/s10021-015-9952-z"
- Description: Research into the benefits that ecosystems contribute to human wellbeing has multiplied over the last few years following from the seminal contributions of the international Millennium Ecosystem Assessment. In comparison, the fact that some ecosystem goods and services undermine or harm human wellbeing has been seriously overlooked. These negative impacts have become known as ecosystem disservices. The neglect of ecosystem disservices is problematic because investments into the management or reduction of ecosystem disservices may yield better outcomes for human wellbeing, or at a lower investment, than management of ecosystem services. Additionally, management to optimise specific ecosystem services may simultaneously exacerbate associated disservices. We posit that one reason for the neglect of ecosystem disservices from the discourse and policy debates around ecosystems and human wellbeing is because there is no widely accepted definition or typology of ecosystem disservices. Here, we briefly examine current understandings of the term ecosystem disservices and offer a definition and a working typology to help generate debate, policy and management options around ecosystem disservices. We differentiate ecosystem disservices from natural hazards and social hazards, consider some of their inherent properties and then classify them into six categories. A variety of examples are used to illustrate the different types of, and management strategies to, ecosystem disservices.
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- Date Issued: 2016
An assessment of chlorophyll-a concentration spatio-temporal variation using Landsat satellite data, in a small tropical reservoir
- Authors: Dalu, Tatenda , Dube, Timothy , Froneman, P William , Sachikonye, Mwazvita T B , Clegg, Bruce W , Nhiwatiwa, Tamuka
- Date: 2015
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/68042 , vital:29189 , https://doi.org/10.1080/10106049.2015.1027292
- Description: Publisher version , Traditional approaches to monitoring aquatic systems are often limited by the need for data collection which often is time-consuming, expensive and non-continuous. The aim of the study was to map the spatio-temporal chlorophyll-a concentration changes in Malilangwe Reservoir, Zimbabwe as an indicator of phytoplankton biomass and trophic state when the reservoir was full (year 2000) and at its lowest capacity (year 2011), using readily available Landsat multispectral images. Medium-spatial resolution (30 m) Landsat multispectral Thematic Mapper TM 5 and ETM+ images for May to December 1999–2000 and 2010–2011 were used to derive chlorophyll-a concentrations. In situ measured chlorophyll-a and total suspended solids (TSS) concentrations for 2011 were employed to validate the Landsat chlorophyll-a and TSS estimates. The study results indicate that Landsat-derived chlorophyll-a and TSS estimates were comparable with field measurements. There was a considerable wet vs. dry season differences in total chlorophyll-a concentration, Secchi disc depth, TSS and turbidity within the reservoir. Using Permutational multivariate analyses of variance (PERMANOVA) analysis, there were significant differences (p < 0.0001) for chlorophyll-a concentration among sites, months and years whereas TSS was significant during the study months (p < 0.05). A strong positive significant correlation among both predicted TSS vs. chlorophyll-a and measured vs. predicted chlorophyll-a and TSS concentrations as well as an inverse relationship between reservoir chlorophyll-a concentrations and water level were found (p < 0.001 in all cases). In conclusion, total chlorophyll-a concentration in Malilangwe Reservoir was successfully derived from Landsat remote sensing data suggesting that the Landsat sensor is suitable for real-time monitoring over relatively short timescales and for small reservoirs. Satellite data can allow for surveying of chlorophyll-a concentration in aquatic ecosystems, thus, providing invaluable data in data scarce (limited on site ground measurements) environments.
- Full Text: false
- Date Issued: 2015