Intensification pathways for beef and dairy cattle production systems: Impacts on GHG emissions, land occupation and land use change

This study conducted a life cycle assessment (LCA) investigating energy, land occupation, greenhouse gas (GHG) emissions, fresh water consumption and stress-weighted water use from production of export lamb in the major production regions of New South Wales, Victoria and South Australia. The study used data from regional datasets and case study farms, and applied new methods for assessing water use using detailed farm water balances and water stress weighting. Land occupation was assessed with reference to the proportion of arable and non-arable land and allocation of liveweight (LW) and greasy wool was handled using a protein mass method. Fossil fuel energy demand ranged from 2.5 to 7.0 MJ/kg LW, fresh water consumption from 58.1 to 238.9 L/kg LW, stress-weighted water use from 2.9 to 137.8 L H2O-e/kg LW and crop land occupation from 0.2 to 2.0 m2/kg LW. Fossil fuel energy demand was dominated by on-farm energy demand, and differed between regions and datasets in response to production intensity and the use of purchased inputs such as fertiliser. Regional fresh water consumption was dominated by irrigation water use and losses from farm water supply, with smaller contributions from livestock drinking water. GHG emissions ranged from 6.1 to 7.3 kg CO2-e/kg LW and additional removals or emissions from land use (due to cultivation and fertilisation) and direct land-use change (due to deforestation over previous 20 years) were found to be modest, contributing between –1.6 and 0.3 kg CO2-e/kg LW for different scenarios assessing soil carbon flux. Excluding land use and direct land-use change, enteric CH4 contributed 83–89% of emissions, suggesting that emissions intensity can be reduced by focussing on flock production efficiency. Resource use and emissions were similar for export lamb production in the major production states of Australia, and GHG emissions were similar to other major global lamb producers. The results show impacts from lamb production on competitive resources to be low, as lamb production systems predominantly utilised non-arable land unsuited to alternative food production systems that rely on crop production, and water from regions with low water stress.

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Assessment of Land Use Impacts on the Natural Environment. Part 1: An Analytical Framework for Pure Land Occupation and Land Use Change (8 pp)

The International Journal of Life Cycle Assessment ◽

10.1065/lca2006.12.292.1 ◽

2006 ◽

Vol 12 (1) ◽

pp. 16-23 ◽

Cited By ~ 93

Author(s):

Roland Scholz

Keyword(s):

Land Use ◽

Land Use Change ◽

Natural Environment ◽

Analytical Framework ◽

Land Use Impacts ◽

Pure Land ◽

Land Occupation

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Biofuel production and soil GHG emissions after land-use change to switchgrass and giant reed in the U.S. Southeast

Food and Energy Security ◽

10.1002/fes3.125 ◽

2017 ◽

Vol 7 (1) ◽

pp. e00125 ◽

Cited By ~ 5

Author(s):

Andrea Nocentini ◽

John Field ◽

Andrea Monti ◽

Keith Paustian

Keyword(s):

Land Use ◽

Land Use Change ◽

Ghg Emissions ◽

Biofuel Production ◽

Giant Reed ◽

The U.S

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Breeding strategies for sustainable intensification of developing smallholder dairy cattle production systems

10.18174/405836 ◽

2017 ◽

Author(s):

Charles Mbogo Kariuki

Keyword(s):

Dairy Cattle ◽

Production Systems ◽

Sustainable Intensification ◽

Breeding Strategies ◽

Cattle Production ◽

Smallholder Dairy

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Inhibited development of Ostertagia ostertagi in relation to production systems for cattle

Parasitology ◽

10.1017/s003118200005410x ◽

1982 ◽

Vol 85 (1) ◽

pp. 21-25 ◽

Cited By ~ 16

Author(s):

M. G. Smeal ◽

A. D. Donald

Keyword(s):

Beef Cattle ◽

Dairy Cattle ◽

Production System ◽

Production Systems ◽

New South ◽

New South Wales ◽

Cattle Production ◽

Ostertagia Ostertagi ◽

South Wales

SUMMARYOn a coastal farm in New South Wales where beef and dairy cattle production was carried on side-by-side, separate pasture plots were contaminated with eggs of Ostertagia ostertagi by calves from each production system in autumn, winter or spring. Successive groups of parasite-free tracer calves grazed on the plots for 14 days at 4-week intervals and were then killed for worm counts 14 days after removal from pasture. On all plots, the proportion of inhibited early 4th-stage larvae in tracer calves reached a maximum in spring, and was consistently and very significantly higher in calves which grazed plots contaminated with O. ostertagi of beef cattle origin. Factors which may be responsible for this difference between beef and dairy cattle populations of O. ostertagi are discussed.

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Evaluation of the land use evolution near solid waste landfills using a new weighted environmental index based on GIS techniques

10.5194/egusphere-egu21-12671 ◽

2021 ◽

Author(s):

Javier Rodrigo-Ilarri ◽

Claudia P. Romero-Hernández ◽

María-Elena Rodrigo-Clavero

Keyword(s):

Land Use ◽

Statistical Analysis ◽

Land Use Change ◽

Solid Waste ◽

Aerial Photographs ◽

Environmental Index ◽

Land Occupation ◽

Gis Techniques ◽

Anthropogenic Intervention ◽

Over Time

Land use in the nearby of a Municipal Solid Waste (MSW) landfill can be strongly affected by the waste management tasks (transport, land&#64257;lling and closure). Effects extend from the phases prior to the construction of the land&#64257;ll until years after the completion of the land&#64257;lling process in areas located beyond the perimeter of the plot occupied by the land&#64257;ll.&#160;In this work a new methodology for the analysis of land use change over time is presented. The methodology is based on the use of a new environmental index named WEI (Weighted Environmental Index). WEI is based on the use of GIS techniques accounting for different information sources (digital cartography, aerial photographs and satellite images). WEI assigns environmental values to land use based on the degree of anthropogenic intervention and its occupation surface.&#160;A georeferenced multitemporal statistical analysis is performed considering the values of WEI previously assigned to every land use. The methodology has been applied to analyze the land use change near the main MSW land&#64257;lls of Valencia Region (Spain) where land&#64257;lling is currently the only waste disposal technique available. Data have been obtained from the Spanish Land Occupation Information System (SIOSE) public database and integrate GIS information about land use/land cover on an extensive, high-detailed scale. Results demonstrate the application of the WEI to real case studies and the importance of integrating statistical analysis of WEI evolution over time to arrive at a better understanding of the socio-economic and environmental processes that induce land-use change.

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Mapping land use on Irish raised bogs using Sentinel-2 imagery and Google Earth Engine

10.5194/egusphere-egu21-9262 ◽

2021 ◽

Author(s):

Wahaj Habib ◽

John Connolly ◽

Kevin McGuiness

Keyword(s):

Land Use ◽

High Resolution ◽

Land Use Change ◽

Optical Sensors ◽

Ghg Emissions ◽

Google Earth ◽

Good Prospect ◽

Raised Bogs ◽

Google Earth Engine ◽

Sentinel 2

Peatlands are one of the most space-efficient terrestrial carbon stores. They cover approximately 3 % of the terrestrial land surface and account for about one-third of the total soil organic carbon stock. Peatlands have been under severe strain for centuries all over the world due to management related activities. In Ireland, peatlands span over approximately 14600 km2, and 85 % of that has already been degraded to some extent. To achieve temperature goals agreed in the Paris agreement and fulfil the EU&#8217;s commitment to quantifying the Carbon/Green House Gases (C/GHG) emissions from land use, land use change forestry, accurate mapping and identification of management related activities (land use) on peatlands is important.High-resolution multispectral satellite imagery by European Space Agency (ESA) i.e., Sentinel-2 provides a good prospect for mapping peatland land use in Ireland. However, due to persistent cloud cover over Ireland, and the inability of optical sensors to penetrate the clouds makes the acquisition of clear sky imagery a challenge and hence hampers the analysis of the landscape. Google Earth Engine (a cloud-based planetary-scale satellite image platform) was used to create a cloud-free image mosaic from sentinel-2 data was created for raised bogs in Ireland (images collected for the time period between 2017-2020). A preliminary analysis was conducted to identify peatland land use classes, i.e., grassland/pasture, crop/tillage, built-up, cutover, cutaway and coniferous, broadleaf forests using this mosaicked image. The land-use classification results may be used as a baseline dataset since currently, no high-resolution peatland land use dataset exists for Ireland. It can also be used for quantification of land-use change on peatlands. Moreover, since Ireland will now be voluntarily accounting the GHG emissions from managed wetlands (including bogs), this data could also be useful for such type of assessment.

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Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS Data

Sustainability ◽

10.3390/su122410234 ◽

2020 ◽

Vol 12 (24) ◽

pp. 10234

Author(s):

Javier Rodrigo-Ilarri ◽

Claudia P. Romero ◽

María-Elena Rodrigo-Clavero

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Case Studies ◽

Object Oriented ◽

Land Use Land Cover ◽

Environmental Index ◽

Land Occupation ◽

Gis Data ◽

Over Time

For the first time, this paper introduces and describes a new Weighted Environmental Index (WEI) based on object-oriented models and GIS data. The index has been designed to integrate all the available information from extensive and detailed GIS databases. After the conceptual definition of the index has been justified, two applications for the regional and local scales of the WEI are shown. The applications analyze the evolution over time of the environmental value from land-use change for two different case studies in Spain: the Valencian Region and the L’Alcora municipality. Data have been obtained from the Spanish Land Occupation Information System (SIOSE) public database and integrate GIS information about land use/land cover on an extensive, high-detailed scale. Results demonstrate the application of the WEI to real case studies and the importance of integrating statistical analysis of WEI evolution over time to arrive at a better understanding of the socio-economic and environmental processes that induce land-use change.

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Biofuels and land-use changes: searching for the top model

Interface Focus ◽

10.1098/rsfs.2010.0043 ◽

2011 ◽

Vol 1 (2) ◽

pp. 224-232 ◽

Cited By ~ 41

Author(s):

Andre M. Nassar ◽

Leila Harfuch ◽

Luciane C. Bachion ◽

Marcelo R. Moreira

Keyword(s):

Land Use ◽

Land Use Change ◽

Policy Making ◽

Agricultural Sector ◽

Land Use Changes ◽

Ghg Emissions ◽

Biofuel Production ◽

Policy Makers ◽

Green House Gas ◽

Biofuel Policies

The use of agricultural-based biofuels has expanded. Discussions on how to assess green house gas (GHG) emissions from biofuel policies, specifically on (non-observed) land-use change (LUC) effects involve two main topics: (i) the limitations on the existing methodologies, and (ii) how to isolate the effects of biofuels. This paper discusses the main methodologies currently used by policy-makers to take decisions on how to quantify LUCs owing to biofuel production expansion. It is our opinion that the concerns regarding GHG emissions associated with LUCs should focus on the agricultural sector as a whole rather than concentrating on biofuel production. Actually, there are several limitations of economic models and deterministic methodologies for simulating and explaining LUCs resulting from the expansion of the agricultural sector. However, it is equally true that there are avenues of possibilities to improve models and make them more accurate and precise in order to be used for policy-making. Models available need several improvements to reach perfection. Any top model requires a concentration of interdisciplinary designers in order to replicate empirical evidence and capture correctly the agricultural sector dynamics for different countries and regions. Forgetting those limitations means that models will be used for the wrong purposes.

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