Thanks to the construction of large databases such as LINKS and GENLIAS based on Dutch civil certificates, our knowledge of individual demographic behavior in the past has improved significantly. ...However, the use of such research infrastructures also introduces some potential pitfalls, as these databases do not contain all information available from the original sources. For instance, variables that are available on the original source but lacking in LINKS are the places of residence of the bride and the groom at marriage. A common practice among researchers using LINKS and GENLIAS is therefore to identify migrants by comparing an individual’s birth place with the place of marriage. The place of marriage, however, is not necessarily identical to the place of residence, because couples traditionally contracted their marriage in the bride's or bride's parents' municipality of residence. It is therefore particularly likely that grooms are erroneously considered as migrants even though they had never moved before marriage. In this paper we explore whether this poses a problem to studies using the place of marriage as an equivalent to the place of residence. This will be achieved with the help of the marriage certificates release from the Historical Sample of the Netherlands (HSN), which, unlike LINKS, contains both the place of marriage of the couple and the residence of the bride and groom, and allows us to compare the findings derived from both approaches. The analyses show that identifying migrants based on place of marriage causes indeed a significant overestimation of male migrants, but not of female migrants. We therefore suggest the use of a couple's place of first childbirth as a robustness check to avoid overestimating male migration in the past.
•The framework of the EU N Expert Panel was applied to farmer field data covering the period 2015–2017.•N-use efficiency (NUE) was on average 0.7–1.0 kg N kg−1 N for Dutch arable crops.•Annual N ...surplus (Ns) was on average 20–80 kg N ha−1 for Dutch arable crops.•In Dutch farming, technological advances without reducing N inputs are unlikely to improve NUE or N surplus.•Highest NUE and lowest Ns can be achieved with mineral fertilisers, which comes with trade-offs at national level.
Nitrogen (N) management is important for farmers to balance production, economic and environmental performance of their farms. This is particularly true in the intensive cropping systems of northwest Europe where tuber, root and bulb crops are cultivated in rotation with cereal crops and where an intensive livestock sector makes organic manures available at low cost for arable farmers. Here, we build upon a large database of farmer field data to assess mineral and organic fertiliser N performance, and its determinants, for the major arable crops in the Netherlands according to the guidelines provided by the EU N Expert Panel (EUNEP). The EUNEP framework quantifies N outputs and N inputs, N-use efficiency as the ratio between N outputs and N inputs (NUE in kg N output harvested per kg N input) and N surplus as the difference between N inputs and N outputs (Ns in kg N ha−1). As a next step, biophysical and crop management determinants of N performance were explored using data from different years, soil types and N management in relation to the amount, source, time and method of N applied. NUE was on average ca. 0.95 kg N kg−1 N for seed potato, sugar beet and spring onion, 0.87 kg N kg−1 N for ware potato, ca. 0.80 kg N kg−1 N for starch potato and winter wheat and, ca. 0.70 kg N kg−1 N for spring barley, all within or above the target range of 0.50–0.90 kg N kg−1 N proposed by the EUNEP. Ns was on average below the EUNEP threshold of 80 kg N ha−1 for all crops: 78 kg N ha−1 for ware potato and winter wheat, ca. 70 kg N ha−1 for starch potato, ca. 50 kg N ha−1 for spring barley, ca. 25 kg N ha−1 for sugar beet and spring onion and less than 20 kg N ha−1 for seed potato. Although average Ns was below 80 kg N ha−1, ca. 40% of the ware potato, starch potato and winter wheat fields analyzed had Ns above this threshold. The relatively high NUE combined with high Ns for most crops are the result of high N outputs (yields) combined with high N application rates. Moreover, high NUE and small Ns were mostly associated with smaller N application rates and with the use of mineral fertilisers instead of organic fertilisers, while there were no clear relationships between the two indicators on the one hand with N application time or method on the other. We conclude NUE and Ns were on average within the EUNEP target range for most crops, but there are still a considerable number of under-performing farms where increases in NUE and reductions in Ns are possible through reducing N inputs. We recommend future research to assess the benefits of organic fertilisers from a circularity perspective at regional and national levels and to cross-validate the crop-specific results presented in this study with NUE assessments at cropping systems level.
As elsewhere in Western Europe, large scale intensive agriculture dominates the landscape of the Netherlands. Grassland for dairy production occupies more than a quarter of its land surface. The high ...production intensity on conventionally farmed grassland leads to poor habitat quality, resulting in sharp declines in bird and insect numbers. Nature-inclusive agriculture (NIA) comprises innovations in farm management, technology and resource use that have the potential to address farmland biodiversity decline, but few Dutch farmers implement these.
We aim to analyze the adoption of NIA practices in the Dutch dairy sector. Specifically, we study the influence of the dominant agri-food regime on the innovation system for NIA.
Innovation Systems Analysis was performed to identify the various structural barriers which hinder adoption. Our study used a multi-method design in which data on NIA in the Dutch dairy sector was collected via a literature study, four workshops and a focus group discussion.
We identified five key blocking mechanisms that hinder adoption of nature-inclusive agriculture in the Dutch dairy sector: (1) insufficient economic incentives for farmers, (2) limited action perspective of many dairy farmers in the Netherlands, (3) lack of a concrete and shared vision for NIA, (4) lack of NIA-specific and integral knowledge and (5) regime resistance, which moreover is connected to each of the previous blocking mechanisms. Our analysis shows that one of the empirical novelties of this paper is that these blocking mechanisms are strongly interlinked in the Dutch dairy sector, thereby perpetuating a situation of lock-in. We conclude that in order to accelerate adoption of nature-inclusive farming practices, problems need to be addressed in conjunction with one another, and therefore holistic approaches are key. A second important conclusion is that in order to foster growth of the innovation system around NIA, the focus should not only be on innovation, but also on transforming current regimes, in particular the currently dominant economic paradigms of growth and yield maximization.
By unraveling strongly interlinked blocking mechanisms, this paper provides intervention points to accelerate the transition towards NIA in the Netherlands. These intervention points are not only located within the innovation system, but should preferable be sought for in the broader structures and institutions of the dominant agri-food regime.
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•Uptake of nature-inclusive practices in the Dutch dairy sector is currently low.•Through Innovation Systems Analysis we identified five blocking mechanisms hindering uptake.•These include lack of financial incentives and shared visions, limited action perspectives and knowledge transfer problems•The productivist agriculture paradigm is a recurring blocking mechanism requiring institutional change•Change needs to come from incumbents, requiring policies aimed at regime transformation
•A comparison of 7 classifiers for travel mode prediction is performed.•Prediction accuracy and variable importance for each travel mode is investigated.•Among the investigated classifiers, random ...forest performs best.•Trip distance followed by the number of cars are the most important variables.•The importance of other variables varies with travel mode and classifier.
The analysis of travel mode choice is an important task in transportation planning and policy making in order to understand and predict travel demands. While advances in machine learning have led to numerous powerful classifiers, their usefulness for modeling travel mode choice remains largely unexplored. Using extensive Dutch travel diary data from the years 2010 to 2012, enriched with variables on the built and natural environment as well as on weather conditions, this study compares the predictive performance of seven selected machine learning classifiers for travel mode choice analysis and makes recommendations for model selection. In addition, it addresses the importance of different variables and how they relate to different travel modes. The results show that random forest performs significantly better than any other of the investigated classifiers, including the commonly used multinomial logit model. While trip distance is found to be the most important variable, the importance of the other variables varies with classifiers and travel modes. The importance of the meteorological variables is highest for support vector machine, while temperature is particularly important for predicting bicycle and public transport trips. The results suggest that the analysis of variable importance with respect to the different classifiers and travel modes is essential for a better understanding and effective modeling of people’s travel behavior.
The analysis of strontium isotope ratios in human dental enamel has become important in the fields of archaeological and forensic science for determining provenance and hence mobility. The ...prerequisite for the approach relies on a correlation between dietary Sr intake and the underlying local geology. This premise is brought into question for anthropological forensic investigations by the increasing globalisation of food supply, the establishment of nation-wide or international supermarket chains, and increasing urbanisation. To better understand the processes that cause spatial variation of Sr isotope ratios in the modern environment, this study determines the range of 87Sr/86Sr ratios in the modern Dutch environment based on 296 modern human dental enamel and tap water samples. Tap water 87Sr/86Sr from the Netherlands range from 0.70837 to 0.71278 (ΔSrmax–min = 0.0044) and modern human enamel from 0.70847 to 0.70995 (ΔSrmax–min = 0.0015). The 87Sr/86Sr ratios of tap water are predominantly determined by the underlying bedrock geology at the sampling point. In contrast, the human enamel data record an insignificant, weak correlation with water supply or local geology. Hence, the main principle behind the application of 87Sr/86Sr as a proxy for mobility appears invalid in the modern globalised Dutch context. The range of 87Sr/86Sr in modern Dutch humans that can be used for anthropological forensic investigations is between 0.7085 and 0.7100 (n = 153), with 98.0% of individuals between 0.7088 and 0.7099.
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•87Sr/86Sr ratios of modern dental enamel and tap water were measured and compared.•No correlation between 87Sr/86Sr ratios of tap water and human dental enamel.•A model for the prediction of dental enamel 87Sr/86Sr data could not be established.•98% of Dutch inhabitants have 87Sr/86Sr ratios between 0.7088 and 0.7099.•Sr isoscapes must be used with caution in forensic provenancing investigations.
Climate change is projected to increase flood risks in certain regions due to an increase in both precipitation and sea level rise. In addition, socio-economic scenarios project an increase in ...urbanization in flood prone areas, which results in a higher damage potential. The combined effect of climate and land use change on flood risks requires innovative adaptation policies to cope with rising risks. Increasingly, attention is paid to the role insurance can play in mitigating damage by providing incentives to policyholders to undertake damage reducing measures. The willingness of homeowners in the Netherlands to undertake measures that mitigate flood damage in exchange for benefits on hypothetical flood insurance policies is examined using surveys. The results indicate that many homeowners are willing to make investments in mitigation. In particular, approximately two-thirds are willing to invest in water barriers in exchange for a premium reduction and about a fifth are willing to replace floor types that are vulnerable to flooding with water resistant floor types. Furthermore, about a quarter are willing to move central heating installations to floors safe against flooding in favor of a reduction in the insurance premium. Estimates of the effectiveness of these mitigation measures to limit potential flood damage in the river delta indicate that prevented damage could be substantial, namely in the order of 1 billion euro or larger. Reductions in (absolute) flood risk due to mitigation are especially large under climate change. A probit model indicates that existing arrangements for compensating flood damage, risk awareness and perceptions, and geographical characteristics are important determinants in the decision to undertake mitigation.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a major global health problem, and public health surveillance is crucial to monitor and prevent virus spread. ...Wastewater-based epidemiology has been proposed as an addition to disease-based surveillance because virus is shed in the feces of ≈40% of infected persons. We used next-generation sequencing of sewage samples to evaluate the diversity of SARS-CoV-2 at the community level in the Netherlands and Belgium. Phylogenetic analysis revealed the presence of the most prevalent clades (19A, 20A, and 20B) and clustering of sewage samples with clinical samples from the same region. We distinguished multiple clades within a single sewage sample by using low-frequency variant analysis. In addition, several novel mutations in the SARS-CoV-2 genome were detected. Our results illustrate how wastewater can be used to investigate the diversity of SARS-CoV-2 viruses circulating in a community and identify new outbreaks.
Starting with the analysis of the diary kept by Constantijn Huygens Jr in the second half of the 17th century, this book sketches a panoramic view of life among Dutch regents and at the court of ...William and Mary, including an eyewitness account of the Glorious Revolution, and highlighting themes such as scientific progress, book and art collecting.
•A large database of farmer’s field data was combined with crop growth modelling.•Yield gaps for the main arable crops in the Netherlands were ca. 30% of Yp.•Variation in Ya was mostly explained by ...sowing and harvest dates.•Actual water productivity was about half of its potential for most arable crops.•Big data are useful to describe current systems but not to predict their performance.
Yield gaps and water productivity are key indicators to monitor the progress towards more sustainable and productive cropping systems. Individual farmers are collecting increasing amounts of data (‘big data’), which can help monitor the process of sustainable intensification at local level. In this study, we build upon such data to quantify the magnitude and identify the biophysical and management determinants of on-farm yield gaps and water productivity for the main arable crops cultivated in the Netherlands. The analysis focused on ware, seed and starch potatoes, sugar beet, spring onion, winter wheat and spring barley and covered the period 2015–2017. A crop modelling approach based on crop coefficients (kc) and daily weather data was used to estimate the potential yield (Yp), radiation intercepted and potential evapotranspiration (ETP) for each crop. Yield gaps were estimated to be ca. 10% of Yp for sugar beet, 25–30% of Yp for ware, seed and starch potato and spring barley, and 35–40% of Yp for spring onion and winter wheat. Variation in actual yields was associated with water availability in key periods of the growing season as well as with sowing and harvest dates. However, the R2 of the fitted regressions was rather low (20–49%). Current levels of crop water productivity ranged between 13 kg DM ha−1 mm−1 for spring barley, ca. 15 kg DM ha−1 mm−1 for seed potato, spring onion and winter wheat, 23 kg DM ha−1 mm−1 for ware potato and ca. 25 kg DM ha−1 mm−1 for starch potato and sugar beet. These values are about half of their potential, but increasing actual water productivity further is restricted by rainfall amount and distribution. However, doing so should not be prioritized over reducing environmental impacts of these intensive cropping systems in the short-term and may require large investments from farm to regional levels in the long-term. Although these findings are most relevant to similar cropping systems in NW Europe, the underlying methods are generic and can be used to benchmark crop performance in other cropping systems. Based on this work, we argue that ‘big data’ are currently most useful to describe cropping systems at regional scale and derive benchmarks of farm performance but not as much to predict and explain crop yield variability in time and space.
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