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Bannink A.,Wageningen University | van Schijndel M.W.,Netherlands Environmental Assessment Agency PBL | Dijkstra J.,Wageningen University
Animal Feed Science and Technology | Year: 2011

The protocol for the National Inventory of agricultural greenhouse gas emissions in The Netherlands includes a dynamic and mechanistic model of animal digestion and fermentation as an Intergovernmental Panel on Climate Change (IPCC) Tier 3 approach to estimate enteric CH4 emission by dairy cows. The model differs from an IPCC Tier 2 approach in that it predicts hydrogen sources (i.e., production of acetate and butyrate, microbial growth on amino acids as an N source) and sinks (i.e., production of propionate and the remainder of the volatile fatty acids (VFA), microbial growth on ammonia as an N source, saturation of unsaturated long chain fatty acids) in the rumen and large intestine, and elimination of excess hydrogen by methanogenesis. As a result, the model predicts CH4 emission by considering various dietary characteristics, including the types of carbohydrate, protein, fat, intrinsic degradation characteristics of feeds, as well as ruminal fractional passage rates, fluid volume and acidity, instead of assuming a fixed CH4 energy conversion factor in the Tier 2 approach. Annual statistics of diet and performance of the average dairy cow in The Netherlands from 1990 until 2008 indicate that dry matter intake and yield of fat and crude protein corrected milk (FPCM) per cow/year increased by 20 and 34% respectively. Based on annual data for diet and FPCM, the model predicted an increase in enteric CH4 emission from 111 (1990) to 128 (2008)kg/cow/year. As a result, CH4 emission per kg FPCM milk decreased by 13%. The predicted fraction of gross energy intake lost as CH4 energy gradually declined and was close to 0.06, which is the IPCC (1997) Tier 2 default value of 0.06 for dairy cows, but ∼10% lower than the IPCC (2006) updated value of 0.065. The 15% uncertainty value for predicted CH4 emissions for a reference diet was lower than the 20% assumed under Tier 2. Our analysis indicated that uncertainty of model predictions of CH4 emission is determined mostly by errors in feed intake estimation, in the representation of the stoichiometry of production of VFA from fermented substrate, and in the acidity of rumen contents. Further uncertainty of predicted CH4 emission was due to errors in estimation of dietary composition of ingredients and in chemical compositions of dietary components. Results demonstrate that prediction of CH4 should not solely focus on representing effects of nutrition on overall digestion and apparent feed utilization by cows, but that additional attention is needed to address effects of nutrition on intra-ruminal fermentation conditions, and their effects on formation of VFA and the rumen hydrogen balance. This article is part of the special issue entitled: Greenhouse Gases in Animal Agriculture-Finding a Balance between Food and Emissions, Guest Edited by T.A. McAllister, Section Guest Editors: K.A. Beauchemin, X. Hao, S. McGinn and Editor for Animal Feed Science and Technology, P.H. Robinson. © 2011 Elsevier B.V. Source

Bellard C.,University Paris - Sud | Thuiller W.,CNRS Alpine Ecology Laboratory | Leroy B.,University of Rennes 1 | Genovesi P.,Institute for Environmental Protection and Research | And 2 more authors.
Global Change Biology | Year: 2013

Biological invasion is increasingly recognized as one of the greatest threats to biodiversity. Using ensemble forecasts from species distribution models to project future suitable areas of the 100 of the world's worst invasive species defined by the International Union for the Conservation of Nature, we show that both climate and land use changes will likely cause drastic species range shifts. Looking at potential spatial aggregation of invasive species, we identify three future hotspots of invasion in Europe, northeastern North America, and Oceania. We also emphasize that some regions could lose a significant number of invasive alien species, creating opportunities for ecosystem restoration. From the list of 100, scenarios of potential range distributions show a consistent shrinking for invasive amphibians and birds, while for aquatic and terrestrial invertebrates distributions are projected to substantially increase in most cases. Given the harmful impacts these invasive species currently have on ecosystems, these species will likely dramatically influence the future of biodiversity. © 2013 John Wiley & Sons Ltd. Source

Van Oudenhoven A.P.E.,Wageningen University | Petz K.,Wageningen University | Alkemade R.,Netherlands Environmental Assessment Agency PBL | Hein L.,Wageningen University | De Groot R.S.,Wageningen University
Ecological Indicators | Year: 2012

Land management is an important factor that affects ecosystem services provision. However, interactions between land management, ecological processes and ecosystem service provision are still not fully understood. Indicators can help to better understand these interactions and provide information for policy-makers to prioritise land management interventions. In this paper, we develop a framework for the systematic selection of indicators, to assess the link between land management and ecosystem services provision in a spatially explicit manner. Our framework distinguishes between ecosystem properties, ecosystem functions, and ecosystem services. We tested the framework in a case study in The Netherlands. For the case study, we identified 12 property indicators, 9 function indicators and 9 service indicators. The indicators were used to examine the effect of land management on food provision, air quality regulation and recreation opportunities. Land management was found to not only affect ecosystem properties, but also ecosystem functions and services directly. Several criteria were used to evaluate the usefulness of the selected indicators, including scalability, sensitivity to land management change, spatial explicitness, and portability. The results show that the proposed framework can be used to determine quantitative links between indicators, so that land management effects on ecosystem services provision can be modelled in a spatially explicit manner. © 2012 Elsevier Ltd. All rights reserved. Source

Trisurat Y.,Kasetsart University | Alkemade R.,Netherlands Environmental Assessment Agency PBL | Verburg P.H.,VU University Amsterdam
Environmental Management | Year: 2010

Rapid deforestation has occurred in northern Thailand over the last few decades and it is expected to continue. The government has implemented conservation policies aimed at maintaining forest cover of 50% or more and promoting agribusiness, forestry, and tourism development in the region. The goal of this paper was to analyze the likely effects of various directions of development on the region. Specific objectives were (1) to forecast land-use change and land-use patterns across the region based on three scenarios, (2) to analyze the consequences for biodiversity, and (3) to identify areas most susceptible to future deforestation and high biodiversity loss. The study combined a dynamic land-use change model (Dyna-CLUE) with a model for biodiversity assessment (GLOBIO3). The Dyna-CLUE model was used to determine the spatial patterns of land-use change for the three scenarios. The methodology developed for the Global Biodiversity Assessment Model framework (GLOBIO 3) was used to estimate biodiversity intactness expressed as the remaining relative mean species abundance (MSA) of the original species relative to their abundance in the primary vegetation. The results revealed that forest cover in 2050 would mainly persist in the west and upper north of the region, which is rugged and not easily accessible. In contrast, the highest deforestation was expected to occur in the lower north. MSA values decreased from 0.52 in 2002 to 0.45, 0.46, and 0.48, respectively, for the three scenarios in 2050. In addition, the estimated area with a high threat to biodiversity (an MSA decrease >0.5) derived from the simulated land-use maps in 2050 was approximately 2.8% of the region for the trend scenario. In contrast, the high-threat areas covered 1.6 and 0.3% of the region for the integrated-management and conservation-oriented scenarios, respectively. Based on the model outcomes, conservation measures were recommended to minimize the impacts of deforestation on biodiversity. The model results indicated that only establishing a fixed percentage of forest was not efficient in conserving biodiversity. Measures aimed at the conservation of locations with high biodiversity values, limited fragmentation, and careful consideration of road expansion in pristine forest areas may be more efficient to achieve biodiversity conservation. © 2010 Springer Science+Business Media, LLC. Source

Raspe O.,University Utrecht | van Oort F.,Netherlands Environmental Assessment Agency PBL
Annals of Regional Science | Year: 2011

If localized knowledge spillovers are important, new firms will tend to locate in proximity of one another, as well as other knowledge sources, in order to capitalize on external knowledge stocks. Although theories that emphasize knowledge spillovers thus present the urban and regional character of a firm's proximity to knowledge sources as a stylized fact, the microfoundations of economic growth in agglomerations are among the most anticipated issues in urban economic research. In this paper, we define knowledge-intensive environments along several dimensions, and analyze newfirms' survival and growth at the individual level.We applymultilevel regression to avoid potential estimation biases, and use firm-level data for newly established manufacturing and business services firms over the period of 2001-2006 in the Netherlands. We find that the urban knowledge context significantly relates to firmlevel employment growth, but that this is conditioned by heterogeneous features of the firm population and knowledge externalities, including (a) industries-more in services than in manufacturing; (b) types of knowledge context-more positively related to (non-technical) innovation than to (technologically) R&D related variables; and (c) types of post entry process-different for survival and growth. We also find significant interaction effects between the growth of R&D-specialized firms with university presence. © Springer-Verlag 2009. Source

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