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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.