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Similar to a normal wave, a shock wave travels as energy through matter but it causes an abrupt raise of pressure, temperature and density. In this study the influence of shock waves on wood structure were investigated in the light of possible future industrial utilization e.g. timber impregnating treatment.
In strukturschwachen ländlichen Regionen die nachhaltige Entwicklung und Digitalisierung durch Transferprojekte zu unterstützen und gemeinsam mit regionalen Akteuren weiterzuentwickeln ‐ das ist das Ziel des Verbundvorhabens InNoWest ‐ Einfach machen! Gemeinsam nachhaltig und digital in Nord-West-Brandenburg. Wir stellen das Projekt vor.
Die Hochschulrektorenkonferenz hat sich 2018 für eine „Kultur der Nachhaltigkeit“ ausgesprochen. Um dieses neue Leitbild für die Hochschulentwicklung auszugestalten, hat sich das Verbundvorhaben Hochschulen in Gesellschaft – Realexperimente transformativer Lern- und Forschungsprozesse für eine Kultur der Nachhaltigkeit an Hochschulen gegründet. Es will alle relevanten Stakeholder von Hochschulen ansprechen und einen wichtigen Impuls für die Nachhaltigkeitstransformation an Hochschulen setzen.
Feeding effects of the invasive, polyphagous brown marmorated stink bug (BMSB), Halyomorpha halys (Hemiptera:Pentatomidae), on some agricultural fruits (hazelnut, blueberry, mandarin, lemon) were investigated in Guria and Samegrelo regions of Georgia in 2019 and 2020. The damage to hazelnut kernels was evaluated when H. halys adults were allowed to feed on kernels in different stages of development. Furthermore, BMSB adults were allowed to feed on almost ripened fruits of blueberry, on small mandarin fruits which were not yet well developed, and on ripened fruits of mandarin. The evaluation of damage on lemon was recorded after allowing adult BMSB on small, not yet developed fruits and on almost developed fruits. It was shown that hazelnuts are susceptible to damage caused by feeding of BMSB throughout the entire period of kernel development (100% of kernels were damaged and did not develop at all). Furthermore, BMSB damages blueberry severely (100% damage) when the fruits are almost ripened. Damage to mandarin fruits in early development stages was over 90%, and 100% of ripened mandarin fruits dropped to the ground. We did not find any damage when BMSB was allowed to feed on Lemon throughout the development of the fruits.
Rainfed farmers are among the most vulnerable farming communities to climate change in Pakistan because of the heavy reliance of crop farming on rain and of farmers’ livelihoods on crop farming. The best and most timely responses against climate change are suitable adaptation measures. Accurately perceiving the risks associated with climate change is an essential factor for planning and then implementing adaptations. Using farm household-level data of 400 rainfed farmers collected through a well-designed and field-tested questionnaire, this study examines the association between various adaptation stages (climate risk perceptions, adaptation planning, and implementation of adaptation) and their determinants using a multivariate probit (MVP) model. The findings indicate that farmers’ perceptions of climatic changes are in line with historical climatic data. Climate risk management (CRM) trainings and digital agriculture extension and communication (DAEC) services (indicators of formal institutional arrangements) show a highly significant impact on all adaptation stages. Input market distance, farmer cooperative meetings (an indicator of informal institutional arrangement), off-farm income, education, and number of male family members are among the other key determinants. A highly significant association between various adaptation stages indicates that accurate climate risk perceptions lead to planning and implementation of adaptations. When risk perceptions are underestimated or lacking, then adaptations do not occur. The results further indicate that the timely availability of reliable information on advanced agricultural inputs, weather parameters, crop farming advisory services, and market information could help rainfed farmers devise sound adaptations to minimize risks associated with climate change. The study recommends the provision of CRM trainings and DAEC services to provide a better understanding and promote sound adaptation planning through the adaptive capacity enhancement of rainfed farming communities for sustainable production and livelihood security.
Primary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe’s known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985–2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests.
By leveraging a wide range of novel, data-driven technologies for agricultural production and agri-food value chains, digital agriculture presents potential enhancements to sustainability across food systems. Accordingly, digital agriculture has received considerable attention in policy in recent years, with emphasis mostly placed on the potential of digital agriculture to improve efficiency, productivity and food security, and less attention given to how digitalization may impact other principles of sustainable development, such as biodiversity conservation, soil protection, and human health, for example. Here, we review high-level policy and law in the German and European context to highlight a number of important institutional, societal, and legal preconditions for leveraging digital agriculture to achieve diverse sustainability targets. Additionally, we combine foresight analysis with our review to reflect on how future frame conditions influencing agricultural digitalization and sustainability could conceivably arise. The major points are the following: (1) some polices consider the benefits of digital agriculture, although only to a limited extent and mostly in terms of resource use efficiency; (2) law as it applies to digital agriculture is emerging but is highly fragmented; and (3) the adoption of digital agriculture and if it is used to enhance sustainability will be dependent on future data ownership regimes.
CONTEXT
Current research emphasises that agricultural innovation projects are influenced in multiple ways by the Agricultural Innovation Systems (AIS) in which they operate. Yet little attention has been paid to the reverse direction of this relationship, i.e. how agricultural innovation projects affect AIS in the course of their innovative activities. Accordingly, there are currently no tools to measure such AIS spillovers from agricultural innovation projects.
OBJECTIVE
This paper shows that even where agricultural innovation projects have not been designed with the explicit aim of influencing AIS they can have spillovers on the AIS in which they operate. Based on this finding, it argues that designing agricultural innovation projects in a way that maximises such positive and reduces negative AIS spillovers would be a useful tool for strengthening agricultural innovation capacities in a particular territory or sector.
METHODS
Based on the concept of agricultural innovation projects as Organisational Innovation Systems (OIS) that are embedded in AIS, the paper develops an analytical framework for assessing spillovers of such projects on AIS and applies it to a case study of an Operational Group in the German Federal State of Hessen.
RESULTS AND CONCLUSIONS
The case study shows that agricultural innovation projects may yield diverse spillovers on the AIS in which they operate. In addition to considering how agricultural innovation projects are shaped – constrained and/or enabled – by AIS, the research community on agricultural innovation should pay more attention to this side of the interrelation of AIS and agricultural innovation projects. Designing agricultural innovation projects responsibly so that spillovers on AIS are monitored can help to improve national or sectoral AIS.
SIGNIFICANCE
This paper points to an underexplored issue in research on agricultural innovation and, related to this, a thus far unused potential policy tool for improving national and sectoral AIS. It further develops the concept of innovation projects as OIS into an approach for assessing the effects of projects on AIS; an area of project assessment that until now has not been adequately covered.
Since the Soviet breakup, rural communities in the Kazakhstan–China borderlands have faced cataclysmic social, economic, and ecological transformations. Collective and state farms have been replaced by precarious smallholder agriculture suffering from a decline in financial inputs and the deterioration of infrastructure. At the same time, dynamic transformations of border permeability (and trans-border reconnections) between Kazakhstan and China have challenged the until relatively recent widespread Soviet rhetoric on Western China (or rather Xinjiang) as an underdeveloped space across the border. This article is based on several months of fieldwork between 2019 and 2021 in Panfilov District, located at major cross-border road and railway intersections and hosting important infrastructural objects, such as a dry port, a major railway transhipment hub, and a trans-border special economic zone. The article explores how the border situation (and the border’s changing permeability for people, commodities, and ideas since the early 1990s) as well as the implementation of new trans-border infrastructures eventually shaped local discourses and practices in the socio-economic development of south-east Kazakhstan’s agricultural sector. It is scrutinized herein how various forms of trans-border socio-economic interactions (although heavily regulated) and China’s (agri-) economic policy in Xinjiang started to affect farmers’ ambitions and practices across the border.
Islands have unique vulnerabilities to biodiversity loss and climate change. Current Nationally Determined Contributions under the Paris Agreement are insufficient to avoid the irreversible loss of critical island ecosystems. Existing research, policies, and finance also do not sufficiently address small islands’ social-environmental challenges. For instance, the new Global Biodiversity Framework (GBF) mentions islands in the invasive species management target. This focus is important, as islands are at high risk to biological invasions; however, this is the only GBF target that mentions islands. There are threats of equal or greater urgency to small islands, including coastal hazards and overexploitation. Ecosystems such as coral reefs and mangroves are crucial for biodiversity, coastal protection, and human livelihoods, yet are unaddressed in the GBF. While research and global policy, including targeted financial flows, have a strong focus on Small Island Developing States (SIDS), the situation of other small islands has been largely overlooked. Here, through a review of policy developments and examples from islands in the Philippines and Chile, we urge that conservation and climate change policies place greater emphasis on acknowledging the diversity of small islands and their unique governance challenges, extending the focus beyond SIDS. Moving forward, global policy and research should include the recognition of small islands as metacommunities linked by interacting species and social-ecological systems to emphasize their connectivity rather than their isolation. Coalition-building and knowledge-sharing, particularly with local, Indigenous and traditional knowledge-holders from small islands, is needed to meet global goals on biodiversity and sustainable development by 2030.
Since the 1990s, Mongolia's capital city Ulaanbaatar has recorded steady and rapid population growth due to rural-urban migration. So far, little is known about how the social and ecological conditions of migration interact. Thus, in our study we investigated the rural-urban migration process from the countryside to the capital in the Eastern Steppe conducting semi-structured interviews. Our results show that this rural-urban migration often follows a stepwise process from smaller settlements to larger urban agglomerations. The results also demonstrate a complex interplay between the prevailing social, economic, and ecological factors. While social factors (kinship, education) show the same relevance at each step of migration, ecological factors such as the occurrence of dzud seem more relevant at the early stages, from the steppe to the sum centres. Ecological factors only seem to rank second in importance, after social reasons. Economic reasons are also revealed to be very significant but seem most relevant the closer the migrations are to the capital. These results are essential in order to cope with current and future challenges of population development and find solutions to enable traditional Mongolian nomadism even under a modern lifestyle.
Extensively used grasslands (meadows and pastures) are ecologically valuable areas in the agricultural landscape and part of the multifunctional agriculture. In Germany, the quality of these grasslands is assessed based on the occurrence of certain plant species known as indicator or character species, with indicators being defined at regional level. Therefore, the recognition of these indicators on a spatial level is a prerequisite for monitoring grassland biodiversity. The identification of indicator species for the status quo of grassland using traditional methods was found to be challenging and tedious. Deep learning-algorithms applied to high-resolution UAV imagery could be the key solution, where UAV with remote sensors can map a large area of grassland in comparison to manual or ground mapping methods and deep learning-algorithms can automate the detection process. In this research work, we use an EfficientDet based algorithm to train an object detection model capable of recognizing indicators on RGB data. The experimental results show that this approach is very promising in contrast to the difficult and time-consuming manual recognition methods. The model was trained with the momentum-SGD optimizer with a momentum value of 0.9 and a learning rate of 0.0001. The model was trained and tested on 1200 images and achieves 45.7 AP (and 85.7 AP50) on test data set. The dataset includes images of four distinct indicator plant species: Armeria maritima, Campanula patula, Cirsium oleraceum, and Daucus carota
Digitale Plattformen avancieren zu einem wichtigen Teil der kommunalen Daseinsvorsorge. Richtig eingesetzt, können plattformbasierte Leistungen ein wirksames Steuerungsinstrument für eine nachhaltige Kommunalentwicklung darstellen. Für diese kommunale Gestaltungsaufgabe wird in der Kurzstudie ein Kriterienkatalog erarbeitet, anhand dessen die Nachhaltigkeitspotenziale und -risiken unterschiedlicher Plattformmodelle beschrieben und untersucht werden können.
Sustainability innovations influence societal transformations through the development of new products, processes, organizations, behaviors or values. Although various research approaches have tackled technological innovations in the last few decades, the specificities and enabling conditions of individual sustainability innovations remain rather unknown. We therefore propose an analytical framework, built on learning from the social–ecological systems and transitions literature. The sustainability innovation framework features four dimensions: context, actors, process and outcomes, which are detailed in 31 variables. We use the sustainability innovation framework to analyze two case studies selected in the Schorfheide-Chorin Biosphere Reserve, Germany. The first refers to technological and organizational innovation in mobility, while the second relates to social and organizational innovation in agriculture. As a result, we highlight commonalities and differences in enabling conditions and variables between the two cases, which underpin the influence of trust, commitment, resource availability, experimenting, learning, advocating, and cooperating for innovation development. The cases further demonstrate that sustainability innovations develop as bundles of interdependent, entangled novelties, due to their disruptive character. Their specificity thereby resides in positive outcomes in terms of social–ecological integrity and equity. This study therefore contributes to transitions studies via a detailed characterization of sustainability innovations and of their outcomes, as well as through a generic synthesis of variables into an analytical framework that is applicable to a large and diverse range of individual sustainability innovations. Further empirical studies should test these findings in other contexts, to pinpoint generic innovation development patterns and to develop a typology of sustainability innovation archetypes.
The project presented here has pursued two main goals. First, the so-called Tourism Sustainability Satellite Account (TSSA), an accounting system for measuring the sustainability of tourism in Germany, which was initially developed and applied in the previous project phase,
was repopulated with the currently available data. The TSSA is an extended tourism satellite account (TSA) and indicator system respectively that is essentially based on the statistical
frameworks of national accounts (NA) and environmental economic accounts (EEA). In addition, the TSSA includes social indicators that measure the sustainability of labour relations in tourism.
The TSSA thus enables a systematic attribution of the economic, environmental and social impacts of tourism to tourism-related economic sectors at the national level.
The results of the TSSA update show that tourism in Germany continues to make a significant contribution to value added and job creation. Around 3.6 % of total gross value added and 6.1 % of employment were attributable to tourism in Germany in 2019. However, labour productivity in the tourism sector remains relatively low.
In terms of environmental impact, energy consumption in the tourism sector has slightly increased compared to the last measurement (based on data from 2015 or 2016). However, energy intensity has decreased over the same period. Energy intensity in tourism is about as
high as for the average of the German economy. Regarding tourism-induced greenhouse gas (GHG) emissions, and particularly emissions intensity, the situation has also improved, even though the GHG emissions intensity of tourism is still well above the average of the German economy. Within the tourism sector, transportation (in particular aviation and shipping) contribute the most to energy use and GHG emissions. By contrast, tourism-induced water consumption appears to be less of a problem in Germany. The water intensity of tourism is significantly lower than the average of the German economy. Within the tourism sector it is the highest in accommodation and gastronomy.
In terms of the social sustainability dimension, the relatively low and decreasing income gap between men and women (known as the Gender Pay Gap; unadjusted) in the tourism sector over time is worth mentioning. By contrast, all other indicators regarding the working conditions in tourism continue to perform less favourably. Consequently, employees in the tourism sector still assess the working conditions as worse compared to the average of the overall economy.
It has already been shown in the previous project phase that for some sustainability indicators, especially from the ecological dimension, a consideration within the framework of the TSSA approach is not possible without restrictions. This is due, among other things, to the insufficient data available from official statistics and the complexity of causally attributing certain ecological effects to tourism activities. In the second part of the project presented here, a detailed research of existing data bases was therefore conducted for the environmental indicators "biodiversity", "water quality", "noise pollution", "land use", "air emissions" and "waste generation" as well as for the social indicator "tourism acceptance". Based on this, it was evaluated to what extent alternative accounting approaches - as a supplement to the TSSA measurement system - can indicate the tourism effect. The data screening initially confirmed the insufficient data
availability at national level.
The subsequent feasibility analysis yielded that a spatial differentiation according to the degree of tourism relevance (based on tourism density and intensity) and an ensuing analysis of the
change in environmental conditions in regions strongly influenced by tourism in comparison to the overall German average represents an opportunity to quantify the contribution of tourism e.g. to land use. On the one hand, existing official regional data could be used here. On the other hand, additional data collections at the local level would also be essential for certain environmental indicators in the future. In other cases, in particular for biodiversity impacts and
solid waste generation, the preconditions for suitable data availability must be created first. By contrast, the acceptance of tourism by residents can easily be measured through standardised
surveys.
The aim of the presented project was to develop a practicable system for measuring sustainability of national tourism in Germany. Initially, 18 sustainability criteria for tourism were identified. In a second step, these criteria were analyzed with regard to their measurability using indicators in a coherent accounting system in compliance with international recommendations. The outcome is a Tourism Sustainability Satellite Account (TSSA), a system of
indicators which is mainly based on statistical frameworks of national accounts and environmental-economic accounts. In addition, social indicators have been added that mainly measure decent job creation in tourism. Thus, the TSSA allows a systematic allocation of the
economic, ecological and social impacts of tourism to the tourism-relevant economic sectors at a national level. However, there is still a need for development of some sustainability indicators,
especially from the management and, to some extent, the ecological sector.
As a test, the TSSA indicators have been filled with currently available data. The results show that tourism in Germany contributes significantly to creating added value and jobs, although labor productivity is low. In terms of ecological impacts, climate impacts with a slightly above-average greenhouse gas intensity compared to the economy as a whole are at the top of the list, although this intensity varies significantly within the tourism sub-sectors. Working conditions are generally considered to be less sustainable than in other industries. Only the pay gap between men and women is significantly smaller than in other sectors of the economy.
Tourism needs to reduce emissions in line with other economic sectors, if the international community's objective of staying global warming at 1.5°-2.0 °C is to be achieved. This will require the industry to half emissions to 2030, and to reach net-zero by mid-century. Mitigation requires consideration of four dimensions, the Scales, Scopes, Stakeholders and Strategies of carbon management. The paper provides a systematic review of these dimensions and their interrelationships, with a focus on emission inventory comprehensiveness; allocation principles at different scales; clearly defined responsibilities for decarbonization; and the identification of significant mitigation strategies. The paper concludes that without mitigation efforts, tourism will deplete 40% of the world's remaining carbon budget to 1.5 °C. Yet, the most powerful decarbonization measures face major corporate, political and technical barriers. Without worldwide policy efforts at the national scale to manage the sector's emissions, tourism will turn into one of the major drivers of climate change.
Random year intercepts in mixed models help to assess uncertainties in insect population trends
(2023)
1. An increasing number of studies is investigating insect population trends based on time series data. However, the available data is often subject to temporal pseudoreplication. Inter-annual variability of environmental conditions and strong fluctuations in insect abundances can impede reliable trend estimation. Temporal random effect structures in regression models have been proposed as solution for this issue, but remain controversial.
2. We investigated trends in ground beetle abundance across 24 years using generalised linear mixed models. We fitted four models: A base model, a model featuring a random year intercept, a model featuring basic weather parameters, and a model featuring both random year intercept and weather parameters. We then performed a simple sensitivity analysis to assess the robustness of the four models with respect to influential years, also testing for possible spurious baseline and snapshot effects.
3. The model structure had a significant impact on the overall magnitude of the estimated trends. However, we found almost no difference among the models in how the removal of single years (sensitivity analysis) relatively affected trend coefficients. The two models with a random year intercept yielded significantly larger confidence intervals and their p-values were more sensitive during sensitivity analysis. Significant differences of the model with random year intercept and weather parameters to all other models suggest that the random year effects and specific weather effects are rather additive than interchangeable.
4. We conclude that random year intercepts help to produce more reliable and cautious uncertainty measures for insect population trends. Moreover, they might help to identify influential years in sensitivity analyses more easily. We recommend random year intercepts in addition to any variables representing temporally variable environmental conditions, such as weather variables.
Learning and transdisciplinary research are widely acknowledged as key components for achieving sustainability; however, the links between these concepts remain vague in the sustainability literature. Recently, emphasis has been given to transdisciplinary learning, highlighting its potential as an approach that contributes to solving real-world problems. To better understand and foster transdisciplinary learning for sustainability transformations, it is relevant to pay attention to two dimensions that define transdisciplinary learning: social interaction (individual learning in a social setting, as a group, or beyond the group), and learning forms (single-, double-, or triple-loop learning). This article introduces a conceptual framework built upon these two dimensions to understand three specific forms of transdisciplinary learning as a) individual competence development, b) experience-based collaboration, and c) societal interaction. This framework helps to clarify the design of learning processes as well as their interactions in transdisciplinary processes to support transformative change.
CONTEXT
Innovation is an important driver of increased productivity, sustainability and resilience in agriculture, forestry and related sectors. An analysis of how different types of multi-actor co-innovation partnerships function can help to identify the reasons why some are more successful than others in ‘speeding up’ innovation.
OBJECTIVE
To provide a framework for the analysis of the co-innovation process, we developed a multidimensional conceptual typology of co-innovation activities based on a review of 200 such partnerships involving farmers and foresters from across Europe. This framework is based on innovation systems theory and the prevailing policy context of the ‘multi-actor approach’.
METHODS
The overarching concept or dependent variable measured by the typology is ‘effectiveness of co-innovation by a multi-actor partnership’ and the two dimensions of the overarching concept are the ‘structural components of the Organisational Innovation System’, with four categories, and ‘attitude towards interaction’, with two categories. The result is a matrix of eight ‘ideal types’ of co-innovation activity. These eight types are characterised according to first-order constructs derived from our research data.
RESULTS AND CONCLUSIONS
The results show that the co-innovation process can successfully take contrasting forms according to the ‘contextual contingencies’ encountered by the partnership. In other words, no one ideal type is intrinsically ‘superior’ to another but may be more ‘appropriate’ in given circumstances. Factors influencing approaches to implementation include actor capacities, aspirations and networks, the co-innovation topic and its influence on the partnership size and the workplan structure, the type of co-innovation activity outputs and the need to engage with the ‘larger periphery’ of stakeholders, and the nature of the enabling environment.
SIGNIFICANCE
The typology is not a classification since the ideal types represent organisational forms that might exist rather than real partnerships. However, the analytical framework it provides will help policy makers and programme managers to develop targeted interventions, according to actor needs and local circumstances, for ‘speeding up’ innovation.
Livestock farming, which produces milk and meat, is practised by nearly all cultures. But in addition to this, grazing livestock fulfils other fundamentally important roles, one of which is the maintenance of open landscapes, which in turn provides habitat for many rare plant and animal species. Whether wild large herbivores, such as red deer (Cervus elaphus), benefit from the management of the open landscapes is unknown, and there are conflicting views on the nature of the interaction between livestock and wildlife. To investigate this question, we studied interactions in space and time between red deer and livestock in an 787 ha fenced pasture in eastern Germany. First, we used faecal pellet counts to determine whether red deer were using the fenced pasture and whether livestock were using the entire available pasture. Second, we fitted ten red deer, as well as eight Konik horses (Equus ferus caballus) and eight Heck cattle (Bos taurus) with GPS-collars. These data allowed us to perform analyses of space–time interactions. The faecal pellet data showed that red deer did indeed use the fenced pasture and that livestock used the entire extent of the pasture. Further, we verified a neutral space–time interaction between red deer and livestock within the pasture. Thus, there was no indication of a negative effect of the presence of livestock on red deer inside the pasture. For these reasons, we recommend that low-intensity grazing by cattle and horses can maintain open landscapes without detrimental effects on the use of the area by red deer.
In commercial transaction of stacked roundwood, the estimation of the stack net volume plays a key role. One generalized method to determine the net volume is using conversion factors that relate the gross and net volumes. In this literature review the developed methods to estimate the conversion factors as well as their influencing parameters were analyzed based on 153 references from America and Europe. According to the results, 48 different methods (including their variants) for estimating the conversion factors were developed. The newest methods enabled their accurate determination inexpensively, e.g., photo-optical methods or 3D simulation models. The analyzed references revealed that 30 parameters influence the conversion factors. Based on this comprehensive review, each stakeholder involved in the roundwood supply chain can know which method is used for estimating the conversion factors in the analyzed territories and which influencing parameters should be considered when purchasing roundwood in order to accurately assess the solid wood content in the stacks.
The concept of ecosystem services, especially in combination with economic valuation, can illuminate trade-offs involved in soil management, policy and governance, and thus support decision making. In this paper, we investigate and highlight the potential and limitations of the economic valuation of soil-based ecosystem services to inform sustainable soil management and policy. We formulate a definition of soil-based ecosystem services as basis for conducting a review of existing soil valuation studies with a focus on the inclusion of ecosystem services and the choice of valuation methods. We find that, so far, the economic valuation of soil-based ecosystem services has covered only a small number of such services and most studies have employed cost-based methods rather than state-of-the-art preference-based valuation methods, even though the latter would better acknowledge the public good character of soil related services. Therefore, the relevance of existing valuation studies for political processes is low. Broadening the spectrum of analyzed ecosystem services as well as using preference-based methods would likely increase the informational quality and policy relevance of valuation results. We point out options for improvement based on recent advances in economic valuation theory and practice. We conclude by investigating the specific roles economic valuation results can play in different phases of the policy-making process, and the specific requirements for its usefulness in this context.
Scientific evidence suggests that there is room for eradicating poverty and hunger by increasing food production through the adoption of modern agricultural practices by farmers. This study aimed, first, to explore the relationship between the farmers’ awareness and adoption of improved wheat varieties. Second, it aimed to find the key factors that govern the farmers’ awareness and adoption of extension-recommended innovations in the rainfed cropping system of the Khyber Pakhtunkhwa, Pakistan. Data were collected from 395 respondents. A binary logit model was used to analyze the effect of the farmers’ socioeconomic and farm-specific characteristics on their awareness and adoption of the extension-suggested wheat varieties. Moreover, qualitative data from 40 key informants were collected for in-depth analysis. The results show a strong association between the farmers’ awareness of a technology (improved wheat varieties) and its adoption. The results of the logit model show that their extension contacts, income from agriculture, and access to credit positively affected the farmers’ awareness, whereas their education and household sizes negatively affected their awareness. Moreover, the factors that positively influenced the farmers’ decision to adopt the technology included the extension contact, the confidence in the extension, the risk-bearing attitude, and the credit access, whereas the household size and education negatively affected it. The results of the key informant interviews reveal that the high incidence of poverty, the low soil fertility, the farmers’ inability to make effective decisions, the lack of accurate weather predictability in the rainfed farming system, the lack of government interest, and the asymmetric information in the inputs markets contributed to the farmers’ low levels of awareness and to their poor adoption of improved agricultural technologies. These results indicate that any intervention aimed at the awareness and adoption by farmers of improved technologies, such as new wheat varieties, should recognize the heterogeneity in the farmers’ socioeconomic and farm-specific characteristics.
Using survey information of 150 randomly selected households across 21 villages of the forest-rich district of Swat, Pakistan, this study assessed households’ decision-making behaviors in depending on income from nearby forested land using socio-economic attributes. The evidence from the study may aid in making the existing policies be better targeted toward families that depend on the forest for income. Descriptive statistics and econometric techniques such as logit and tobit were used to analyze the data. Respondent households obtained the highest share of their income from off-farm activities (37%) and least from forest activities (16%). Fuelwood constitutes the biggest share (66%) of forest income, followed by medical plants (20%) and fodder (13%). We found that households with more physical assets, more family members working in off-farm jobs, and households earning more income from off-farm jobs were significantly and negatively associated with households’ decision to depend on forest income and total income obtained. We also found that households with less distance to the market and membership to joint forest management committees (JFMCs) were significantly and negatively associated with households’ total income obtained. However, household size was significantly and positively related to households’ decision of forest dependency. The study recommends the creation of off-farm opportunities and inclusion of local people in the management of forests through establishment of JFMCs, particularly for large and poor families.
This study investigates the factors that affect farmers’ access to agricultural credit and its role in adopting improved agricultural technologies in the rain-fed zone of Khyber Pakhtunkhwa (KP), Pakistan. Using logistic models, we assess and compare the relative role of farmers’ socioeconomic attributes in their access to credit and adoption strategies. The results indicate a moderate positive association between farmers’ access to agricultural credit and their adoption of improved agricultural technologies. The binary logit model’s results indicate that farmers with a large-sized farm, high farm income, better access to information, and large physical asset ownership showed a positive influence on credit access. However, farming experience showed a negative effect on farmers’ access to agricultural credit. Regarding farmers’ credit sources, this study found that asset-rich farmers with more farming experience and better access to information relied more on banks than on input providers and informal credit sources. Similarly, older farmers with more education, larger farm sizes and high farm income were more likely to have borrowed from input providers than banks. We conclude that the role of the effective provision of information on credit and agricultural technology is imperative and requires separate policies that are specifically aimed at different groups of farmers with different socioeconomic and farm-related characteristics.
The low agricultural productivity of key crops and food insecurity continue to be key issues in Sub-Saharan Africa (SSA) and Tanzania. The growing population, depleting resources, and changing climate further amplify these issues. Globally, many agricultural technologies (AgTs) are available as pathways for improved agricultural productivity and food security, however, they have had relatively little success in SSA and Tanzania. This is because the uptake of AgTs is a complex process, which is highly localized, involving multiple actors, stages, and spatial and time dimensions. Smallholder farmers often experience issues of sustainability, constraints for adoption, and scaling-up throughout the uptake process of AgTs, all of which vary by region. This indicates a need for a systematic and simultaneous understanding of sustainability, constraints for adoption, and scaling-up of AgTs to better guide agricultural strategy and policy interventions in SSA and Tanzania. Moreover, in order to understand the local settings better, a consideration of the perceptions of the farmers themselves, who are the primary actors in the uptake process of AgTs, is key. Acknowledging this, the study takes on a case study approach, using the scaling-up assessment (ScalA) method and three focus group discussions with a total of 44 smallholder farmers to systematically and simultaneously assess the sustainability, constraints for adoption, and scaling-up of three AgTs (use of fertilizers, improved seeds, and small-scale irrigation) in Tanzania. The study finds that the farmers perceive all three AgTs to be sustainable for the study region. Adoption rates are perceived to be medium for use of fertilizers, high for improved seeds, and low for small-scale irrigation. The most significant constraints for adoption experienced by the farmers are lack of technical physical inputs, marketing facilities, and know-how. Scaling-up is perceived to be well fulfilled for use of fertilizers and improved seeds, but only partially fulfilled for small-scale irrigation, which is the most limited of the three AgTs. The most significant constraints for scaling-up experienced by farmers are a lack of confidence in the added value of the AgTs beyond project activities, marketing facilities, and technical physical inputs. The overall success potential is high for the use of fertilizers and improved seeds, and the average for small-scale irrigation. The farmers’ perceptions partially indicate why the bundle of AgTs is lacking in the study region and provide a basis for discussing targeted agricultural and policy interventions in Tanzania.
Climate change is a severe threat to the agricultural sector in general and to rainfed farming in particular. The aim of this study was to investigate the factors that can potentially affect the adaptation process against climate change. This study focused on wheat farmers and farming systems in the rainfed agroecological zone of Pakistan. Farmers’ data related to climate change fatalism, the availability of climate-specific extension services, socioeconomic and institutional variables, and farm characteristics were collected. A logit model to assess farmers’ decisions to adopt an adaptation measure and a multinomial logit model to assess their choice of various adaptation measures were used. The results showed that fatalistic farmers were unlikely to implement climate change adaptation measures. The variables related to the climate-specific extension services, including farmers’ participation in training on climate-resilient crop farming and the availability of mobile communication-based advisory services, had highly significant and positive impacts on farmers’ decisions and their choice of adaptation measures. Input market access and tractor ownership also had positive and significant impacts on farmers’ decisions to adapt and their choice of adaptation measures. This study highlights the need to improve rainfed-wheat farmers’ education levels to change their fatalistic attitudes towards climate change. Furthermore, government action is needed to provide climate-specific extension services to ensure sustainable production levels that will ultimately lead to food and livelihood security under a changing climate.
In Tanzania, the increasing population coupled with climate change amplifies issues of food insecurity and negatively impacts the livelihoods of smallholder farmer households. To address these issues a range of water conservation techniques (WCTs) have been useful. However, the adoption of these WCTs in Tanzania has been limited due to many reasons. With the objective to better understand and identify the factors that significantly influence the adoption of WCTs in Tanzania, the study uses survey data from 701 smallholder farmer households and a bivariate logistic regression, to provide, for the first time, a comprehensive model for the adoption of WCTs in Tanzania that includes a range of individual, household, socio-economic, and farmer perception related variables (factors). The evaluation shows that 120 farmers (17.12%) adopted WCTs and finds the farmer perceptions of rainfall instability, household wealth, and food security to be crucial. The results suggest that policy interventions should encourage conservation behavior (especially when the rainfall is perceived to be uncertain), emphasize the economic and food security-related benefits of adopting WCTs, include strategies that make adoption of WCTs attractive to female-led households, attempt to reach greater number of farmers via social networks and provide better access to public funds for farmers.
Climate change challenges forest vitality both directly by increasing drought and heat periods and indirectly, e.g., by creating favorable conditions for mass outbreaks of phyllophagous insects. The large forests dominated by Scots pine (Pinus sylvestris L.) that cover the lowland regions in northeast Germany have already been affected regularly by cyclic mass propagations of defoliating insect species in the past with climate projections implying an even more advantageous environment for devastating outbreaks in the future. To improve predictive and responsive capacities we have investigated a wide range of ecological parameters to identify those most strongly related to past outbreak waves of three central species. In total, we analyzed 3,748 variables covering stand and neighborhood properties, site quality, and climatic conditions for an area of roughly 750,000 ha of pine forests in the period 2002–2016. To reflect sensitivity against varying climate, we computed “floating windows” in relation to critical phenological phases of the respective insects. The parameters with the highest explanatory power resulted from the variable importance measures of the Random Forest (RF) methodology and have been evaluated by a 10-fold cross-validation process. Our findings closely reflect the known specific gradation patterns and show that relative variable importance varies with species. While Lymantria monacha L. feeding was mainly dependent on the surroundings of the respective stand, Diprion pini L. proved to be almost exclusively susceptible to climatic effects in its population dynamics. Dendrolimus pini L. exhibited a mixed pattern of variable importance involving both climatic and forest structure parameters. In many cases the obtained statistical results support well-known ecological cause-effect relations and long-term population change dynamics. The RF delivered very high levels of sensitivity and specificity in the developed classifications and proved to be an excellent tool to handle the large amounts of data utilized for this study. While the presented classification approach may already support a better prognosis of the amplitude during the outbreak culmination, the obtained (most important) variables are proposed as preferable covariates for modeling population dynamics of the investigated insect species.
Humans are exposed to agricultural soils through inhalation, dermal contact, or the consumption of food. Human health may be at risk when soils are contaminated; while some soil contaminants such as heavy metals (HMs) have been extensively studied, others such as micro(nano)plastics (MNPs) or antibiotic-resistant bacteria (ARB) pose novel threats. This paper investigates the linkages between soil contamination and human health risk by reviewing the state of knowledge on HMs, MNPs, and ARB in agricultural soils. A keyword-based search in Web of Science, Scopus, and Google Scholar was conducted, complemented with a backward snowball search. We analysed main sources of contamination for agricultural soils, risks to human health differentiated by uptake pathway (ingestion, inhalation, dermal), and interactions of contaminants with microorganism, soil fauna, and plants. Results show that the emergence and spread of ARB and antibiotic resistant genes from agricultural soils and their contribution to antibiotic resistances of human pathogens is recognized as a significant threat. Likewise, a growing body of evidence indicates that MNPs are able to enter the food chain and to have potentially harmful effects on human health. For HM, knowledge of the effects on human health is well established. Multiple agricultural practices increase HM concentrations in soils, which may lead to adverse health effects from the ingestion of contaminated products or inhalation of contaminated soil particles. Severe knowledge gaps exist about the pathways of the contaminants, their behaviour in soil, and human uptake. Little is known about long-term exposure and impacts of MNPs, antibiotics and ARB on human health or about the possible combined effects of MNPs, ARB, and HMs. Missing monitoring systems inhibit a comprehensive assessment of human health risks. Our research demonstrates the need for human health risk assessment in the context of agricultural soils, in particular to be able to assess risks related to measures reinforcing the concept of the circular economy.
The concept of ecosystem services (ES) creates understanding of the value of ecosystems for human well-being. With regard to soils, it provides a framework for assessments of soil contributions and soil management impacts. However, a lack of standardization impedes comparisons between assessment studies and the building of synthesis information. The Common International Classification of Ecosystem Services (CICES) is an important step forward, although its application to soils is not without difficulty. CICES version 5.1 defines 83 ES classes, of which only some are relevant for soils. We compiled two subsets of CICES classes: one set of soil-related ES comprising 29 services defined as directly and quantifiably controlled by soils and their properties, processes and functions, and another set of 40 ES defined as being affected by agricultural soil management. Additionally, we conducted a systematic literature review, searching for published lists of soil-related ES that claim completeness. We identified 11 relevant lists. Of all CICES classes, 12 were included in more than 75% of the lists, whereas another 36 classes were included in 25–75% of them. Regarding the suitability of the CICES classification for addressing ES in the context of soils and their agricultural management, we identified constraints, such as overlaps, gaps, and highly specific or very broad class definitions. Close cooperation between the soil research and ES communities could ensure better consideration of soils in future CICES updates. A shortlist of 25 service classes affected by agricultural soil management facilitates a standardized approach and may function as checklists in impact assessments.
Large carnivores are currently recolonizing Europe following legal protection, but increased mortality in landscapes highly impacted by humans may limit further population expansion. We analyzed mortality and disappearance rates of 35 wolves (of which three emigrated, nine died and 14 disappeared by 1 January 2020) by genetic monitoring in the heavily cultivated and densely populated Jutland peninsula (Denmark and Schleswig-Holstein, Germany). Annual traffic kill rate estimates ranged from 0.37 (95% CI: 0.11–0.85) to 0.78 (0.51–0.96) in the German part, equivalent to 0.08 (0.02–0.29)–0.25 (0.13–0.46) for the entire region, in the absence of any registered Danish roadkills. In Denmark, annual mortality rate estimates ranged from 0.46 (0.29–0.67) to 0.52 (0.35–0.71), predominantly from cryptic mortality. Despite successful reproductions, we conclude the region is a wolf population sink, primarily driven by cryptic mortality, most likely illegal killing. We hypothesize that frequent encounters between wolves and wolf-averse persecutors in cultivated landscapes may cause unsustainably high mortality rates despite the majority of hunters respecting protection laws.
The Earth system and the human system are intrinsically linked. Anthropogenic greenhouse gas emissions have led to the climate crisis, which is causing unprecedented extreme events and could trigger Earth system tipping elements. Physical and social forces can lead to tipping points and cascading effects via feedbacks and telecoupling, but the current generation of climate-economy models do not generally take account of these interactions and feedbacks. Here, we show the importance of the interplay between human societies and Earth systems in creating tipping points and cascading effects and the way they in turn affect sustainability and security. The lack of modeling of these links can lead to an underestimation of climate and societal risks as well as how societal tipping points can be harnessed to moderate physical impacts. This calls for the systematic development of models for a better integration and understanding of Earth and human systems at different spatial and temporal scales, specifically those that enable decision-making to reduce the likelihood of crossing local or global tipping points.
Scholars have argued that circular economy (CE) must be upscaled and globalized to address excessive resource extraction and waste generation. Many CE practitioners consider the first international CE agreement between China and the EU a milestone towards such an effort. This analysis shows why this expectation is premature. European and Chinese stakeholders’ optimistic and depoliticized CE narratives disable communication regarding development disparities, negative competition and distrust, which shape geopolitical rivalry. While skeptical narratives that address political barriers exist, they fall short of suggesting alternatives. Based on 72 stakeholder interviews, 40 documents and participant observation, these results highlight the critical importance of investigating narrative strategies to repoliticize environmental cooperation. Such narrative strategies would support contestation and negotiation on development disparities and open channels for joint conceptualization of implementation scales for environmental strategies, circular or otherwise. We therefore propose using constructivist perspectives of international relations to explore discursive barriers and enablers to global environmental action.
The variation of wood species processed in sawmills in developing countries generates composite waste which presents treatment challenges due to a lack of understanding of their physicochemical characteristics for proper planning for clean energy generation. Most of the waste is discarded or burnt openly which releases harmful gases into the environment. This study investigated the physicochemical characteristics of mixed sawdust generated from five wood species generated at a Ghanaian sawmill in Oforikrom Municipality for improving waste treatment. The particle size distribution (PSD), bulk density, proximate and ultimate values, thermogravimetric analysis (TGA) and structural analysis were used to characterize the composite sawdust for briquetting and gasification purposes. It was found that the net heating value (17.46 MJ/kg), some proximate and ultimate values meet briquette standard but high percentages of ash (2.95%), moisture (41.48%) and the possibility of nitrogen oxides emissions were notable challenges. PSD resulted in different high fine fractions which are unsuitable for densification. The increase of sieving amplitudes at 30, 50 and 80 rpm generated an average increase in sieve efficiency of fines by 4.22%. Mixing of fines (42.38–46.6%) and optimum particle size (53.40–57.62%) fractions was suggested as the best approach to enhance briquette density and durability. The FTIR spectra showed a range of peaks such as 1734.46 cm−1, 1620.48 cm−1, 1506.50 cm−1, 1462.02 cm−1, 1420.32 cm−1 etc. for functional groups identification. Composite sawdust spectra showed high absorbance with no shift of wavenumbers compared with temperate woods, however, it deviated massively when compared with industrial cellulose and organosolv lignin. TGA indicated that exact mixed wood pyrolysis temperatures, volatile and biochar fractions will always depend on sample compositions. The increase in heating rates yielded little significance to volatiles and char increments. Collection of clean sawdust and rooftop drying were recommended as a way of enhancing sawdust properties. Composite sawdust has a promising potential to support Ghana's activities for meeting the renewable energy generation targets. The understanding of these potential assessments is significant to boost the local municipality energy supply.
Scots pine (Pinus sylvestris L.) is the most widely distributed pine species in the world. In Germany, as in many other European countries, it is a very important species both culturally and economically. Few studies have focused on bark volumes being delivered to the wood industry together with the roundwood, being potentially a valuable resource for material or energetic utilization. Therefore, logs from six different forest sites were collected and bark variables including double bark thickness (DBT) in three different categories, diameter, and bark damage (as a degree of miss-DBT) in three different categories, diameter, and bark damage (as a degree of miss-ing bark) were measured and analyzed in order to model bark volume (Vbark) and bark mass (Mbark). The correlation analysis using Pearson’s method showed that the highest correlation coefficients were observed from the correla-tion between DBT and Vbark, as well as between DBT and Mbark. Also, results demonstrated that with DBT greater than 20 mm, the percentage of Vbark exceeded 20%. Finally, different linear regression models were recommended to predict Vbark and Mbark based on the other variables. The results of this study can be used in different wood industries in order to predict bark volume and bark mass of e.g. truckloads or roundwood stacks.
Following the dissolution of the Soviet Union, agricultural reforms in Central Asia often translated into the fragmentation of large fields into smaller shares. Most remote-sensing-based land use classification approaches are categorical in nature, and thus they are unable to capture these changes. We have developed an approach to detecting the timing of land fragmentation based on textural information from a time series of Landsat images for four Central Asian countries (Uzbekistan, Turkmenistan, Kyrgyzstan and Tajikistan) between 1990 and 2019. Our results showed that detected fragmentation events correspond well with documented agrarian reform processes in the different countries, and validation yielded maximum overall accuracies between 67 and 73%. In a case study of a former collective farm in Kyrgyzstan, we demonstrate how our method can accurately detect changes on the local scale. Texture time series data have great potential for analysing the trajectories of cropland fragmentation, in particular in regions where additional information on land use is limited.