SwePub - search: WFRF:(Abdi Abdulhakim M.)

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1.	Diriye, Abdishakur W., et al. (author) Public preference for sustainable land use policies – Empirical results from multinomial logit model analysis 2022 In: Land Use Policy. - : Elsevier BV. - 0264-8377. ; 114 Journal article (peer-reviewed)abstract Public preferences for sustainable land use policy instruments and the motivations behind such preferences are important to make appropriate policies. Based on survey data (n = 309) from northeastern Somalia, we examined preferences for a set of land use policy instruments relative to no policy (i.e. the current status quo) and how cultural worldviews predict such preferences. We used a multinomial logit model to analyze the comparative evaluation of choices due to its interpretability and robustness to violations of normality. Overall, the results show that the respondents are likely to consent to all types of land use policy instruments relative to no policy and are more inclined to market-based and informational policy instruments. Specifically, preferences for regulatory policy instruments are positively associated with hierarchy and egalitarian worldviews and are negatively associated with fatalism and individualistic worldviews with only hierarchy and fatalism are significant. The market-based policy instrument is desirable to all cultural worldviews except fatalism, but only egalitarian and individual worldviews are significant. Preferences for informational policy instruments are positively associated with all cultural worldviews but only egalitarian worldviews showed a significant effect. Although there are some contradictions, these results are broadly consistent with the proposition of the cultural theory of risk. This study highlights that preferences for land use policies are heterogeneous with cultural worldviews mainly explaining the sources of this heterogeneity. It is evident that the respondents were willing to consent to land use policies relative to the status quo of no policy and indicates the need for concerted effort to reduce land degradation and deforestation in the country. We, therefore, recommend that policymakers incorporate the different ways that humans perceive and interpret social-environmental relations into policy decisions to achieve sustainable policy outcomes.
2.	Diriye, Abdishakur W., et al. (author) Value of cultural worldviews and message framing for the acceptability of sustainable land use zoning policies in post-conflict Somalia 2021 In: Journal of Environmental Planning and Management. - : Informa UK Limited. - 0964-0568 .- 1360-0559. Journal article (peer-reviewed)abstract Public acceptability is important for sustainable land use zoning policy to be successfully implemented. This study examined the effectiveness of tailoring messages with cultural worldviews to induce positive attitudes and improve public acceptability of sustainable land use zoning policy in a post-conflict setting. A total of 538 participants were randomly divided into three groups. Two were treatment groups and received promotional information about a hypothetical land use zoning policy, and one group was the control group and received no promotional information. The results indicate that information provision results in positive attitudes and higher public acceptability of land use zoning policy. Arguments that correspond to participants' cultural worldviews generated more positive attitudes and higher acceptability than arguments that conflict with their cultural worldviews. This study recommends targeting messages with peoples’ cultural worldviews as an effective strategy in inducing positive attitudes and higher acceptability for sustainable land use zoning policy in Somalia.
3.	Jama, Osman M., et al. (author) Participation of civil society in decisions to mitigate environmental degradation in post-conflict societies: evidence from Somalia 2020 In: Journal of Environmental Planning and Management. - : Informa UK Limited. - 0964-0568 .- 1360-0559. ; 63:9, s. 1695-1715 Journal article (peer-reviewed)abstract The question of the degree to which participation by civil society contributes to environmental decisions in post-conflict societies has received little attention. This study sheds light on the extent to which degrees of participation contribute to environmental decision-making in the Puntland State of Somalia using questionnaire surveys. We found that active participation has the highest contribution to environmental decisions. Our findings also indicated that the most pressing forms of environmental degradation in Puntland, as perceived by the respondents, are land degradation, drought related to the scarcity of rainfall, and deforestation. This study recommends “environmental cooperation” built into the peace-building process as a clear-cut concept to tackle both environmental degradation and conflicts. At the core of this concept is active participation and collaboration between civil society and the government as a means of mitigating environmental degradation in post-conflict Somalia. This will result in favorable environmental conditions and sustainable peace.
4.	Jama, Osman M., et al. (author) Understanding young people’s perception toward forestation as a strategy to mitigate climate change in a post-conflict developing country 2023 In: Environment, Development and Sustainability. - : Springer Science and Business Media LLC. - 1387-585X .- 1573-2975. ; 25:6, s. 4787-4811 Journal article (peer-reviewed)abstract Understanding the perceptions of young people is a critical issue in the formulation and implementation of climate change mitigation strategies. Based on cognitive hierarchy theory, the present study aims to investigate the factors that motivate or hinder young people’s perception of forestation as a strategy to mitigate climate change in post-conflict Somalia. This study hypothesized a model in which climate change knowledge, risk perception and forest value orientations (anthropocentric/biocentric) influence attitude toward forestation and attitude, in turn, predicts behavioral intentions. We randomly surveyed students from three universities in three different regions of Somalia and collected 434 structured survey questionnaires. Using structural equation modeling, the results showed that climate change knowledge is a significant predictor of behavioral intention but not attitude toward forestation. The results also revealed that young people’s perception toward forestation as a strategy to mitigate climate change is significantly influenced by biocentric value orientation both directly and indirectly through attitude toward forestation. Contrary to previous studies, our results indicate that attitude partially mediates the relationship between biocentric value orientation and behavioral intentions and fully mediates the relationship between anthropocentric value orientation, risk perception and behavioral intentions, while it did not show any mediation results between climate change knowledge and behavioral intention. We found that the young people’s climate action or inaction is mainly shaped by climate change knowledge, biocentric value orientation, and attitude toward forestation. Finally, climate change mitigation efforts should avoid relying solely on attitude for behavioral decision-making formation and instead incorporate other factors into a more comprehensive framework.
5.	Abdi, Abdulhakim M., et al. (author) Biodiversity decline with increasing crop productivity in agricultural fields revealed by satellite remote sensing 2021 In: Ecological Indicators. - : Elsevier BV. - 1470-160X. ; 130 Journal article (peer-reviewed)abstract Increasing land-use intensity is a main driver of biodiversity loss in farmland, but measuring proxies for land-use intensity across entire landscapes is challenging. Here, we develop a novel method for the assessment of the impact of land-use intensity on biodiversity in agricultural landscapes using remote sensing parameters derived from the Sentinel-2 satellites. We link crop phenology and productivity parameters derived from time-series of a two-band enhanced vegetation index with biodiversity indicators (insect pollinators and insect-pollinated vascular plants) in agricultural fields in southern Sweden, with contrasting land management (i.e. conventional and organic farming). Our results show that arable land-use intensity in cereal systems dominated by spring-sown cereals can be approximated using Sentinel-2 productivity parameters. This was shown by the significant positive correlations between the amplitude and maximum value of the enhanced vegetation index on one side and farmer reported yields on the other. We also found that conventional cereal fields had 17% higher maximum and 13% higher amplitude of their enhanced vegetation index than organic fields. Sentinel-2 derived parameters were more strongly correlated with the abundance and species richness of bumblebees and the richness of vascular plants than the abundance and species richness of butterflies. The relationships we found between biodiversity and crop production proxies are consistent with predictions that increasing agricultural land-use intensity decreases field biodiversity. The newly developed method based on crop phenology and productivity parameters derived from Sentinel-2 data serves as a proof of concept for the assessment of the impact of land-use intensity on biodiversity over cereal fields across larger areas. It enables the estimation of arable productivity in cereal systems, which can then be used by ecologists and develop tools for land managers as a proxy for land-use intensity. Coupled with spatially explicit databases on agricultural land-use, this method will enable crop-specific cereal productivity estimation across large geographical regions.
6.	Abdi, Abdulhakim M., et al. (author) Satellite Remote Sensing of Savannas: Current Status and Emerging Opportunities 2022 In: Journal of Remote Sensing. - : American Association for the Advancement of Science (AAAS). - 2694-1589. ; 2022 Journal article (peer-reviewed)abstract Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere. Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity. Monitoring the spatial and temporal dynamics of savanna ecosystem structure (e.g., partitioning woody and herbaceous vegetation) and function (e.g., aboveground biomass) is of high importance. Major challenges include misclassification of savannas as forests at the mesic end of their range, disentangling the contribution of woody and herbaceous vegetation to aboveground biomass, and quantifying and mapping fuel loads. Here, we review current (2010–present) research in the application of satellite remote sensing in savannas at regional and global scales. We identify emerging opportunities in satellite remote sensing that can help overcome existing challenges. We provide recommendations on how these opportunities can be leveraged, specifically (1) the development of a conceptual framework that leads to a consistent definition of savannas in remote sensing; (2) improving mapping of savannas to include ecologically relevant information such as soil properties and fire activity; (3) exploiting high-resolution imagery provided by nanosatellites to better understand the role of landscape structure in ecosystem functioning; and (4) using novel approaches from artificial intelligence and machine learning in combination with multisource satellite observations, e.g., multi-/hyperspectral, synthetic aperture radar (SAR), and light detection and ranging (lidar), and data on plant traits to infer potentially new relationships between biotic and abiotic components of savannas that can be either proven or disproven with targeted field experiments.
7.	Abel, Christin, et al. (author) Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions 2023 In: Global Change Biology. - 1354-1013. ; 29:14, s. 3954-3969 Journal article (peer-reviewed)abstract Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor-pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water-related stress as compared to areas not exposed to water-related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non-stressed systems. Conversely, opposite relationships were found for soil parameters such as root-zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water-related stress (or no stress) is important, for example within management strategies to maintain and restore dryland vegetation.
8.	Abel, Christin, et al. (author) The human–environment nexus and vegetation–rainfall sensitivity in tropical drylands 2020 In: Nature Sustainability. - : Springer Science and Business Media LLC. - 2398-9629. ; 4, s. 25-32 Journal article (peer-reviewed)abstract Global climate change is projected to lead to an increase in both the areal extent and degree of aridity in the world’s drylands. At the same time, the majority of drylands are located in developing countries where high population densities and rapid population growth place additional pressure on the ecosystem. Thus, drylands are particularly vulnerable to environmental changes and large-scale environmental degradation. However, little is known about the long-term functional response of vegetation to such changes induced by the interplay of complex human–environmental interactions. Here we use time series of satellite data to show how vegetation productivity in relation to water availability, which is a major aspect of vegetation functioning in tropical drylands, has changed over the past two decades. In total, one-third of tropical dryland ecosystems show significant (P < 0.05) changes in vegetation–rainfall sensitivity with pronounced differences between regions and continents. We identify population as the main driver of negative changes, especially for developing countries. This is contrasted by positive changes in vegetation–rainfall sensitivity in richer countries, probably resulting from favourable climatic conditions and/or caused by an intensification and expansion of human land management. Our results highlight geographic and economic differences in the relationship between vegetation–rainfall sensitivity and associated drivers in tropical drylands, marking an important step towards the identification, understanding and mitigation of potential negative effects from a changing world on ecosystems and human well-being.
9.	Al-Kharusi, Enass Said, et al. (author) Drought Offsets the Controls on Colored Dissolved Organic Matter in Lakes 2024 In: Remote Sensing. - 2072-4292. ; 16:8 Journal article (peer-reviewed)abstract The concentration of colored dissolved organic matter (CDOM) in lakes is strongly influenced by climate, land cover, and topographic settings, but it is not known how drought may affect the relative importance of these controls. Here, we evaluate the controls of CDOM during two summers with strongly contrasting values of the Palmer drought index (PDI), indicating wet vs. dry conditions. We hypothesized that lake CDOM during a wet summer season is regulated mainly by the surrounding land cover to which the lakes are hydrologically connected, while, during drought, the lakes are disconnected from the catchment and CDOM is regulated by climatic and morphometric factors that govern the internal turnover of CDOM in the lakes. A suite of climate, land cover, and morphometric variables was assembled and used to explain remotely sensed CDOM values for 255 boreal lakes distributed across broad environmental and geographic gradients in Sweden and Norway. We found that PDI explained the variability in CDOM among lakes in a dry year, but not in a wet year, and that severe drought strongly decreased CDOM during the dry year. Large lakes, especially, with a presumed high degree of catchment uncoupling, showed low CDOM during the dry year. However, in disagreement with our hypothesis, climate, land cover, and morphometry all showed a stronger impact on lake CDOM in wet vs. dry years. Thus, drought systematically weakened the predictability of CDOM variations at the same time as CDOM was offset toward lower values. Our results show that drought not only has a direct effect on CDOM, but also acts indirectly by changing the spatial regulation of CDOM in boreal lakes.
10.	Al-kharusi, Enass Said., et al. (author) Large-Scale Retrieval of Coloured Dissolved Organic Matter in Northern Lakes Using Sentinel-2 Data 2020 In: Remote Sensing. - : MDPI AG. - 2072-4292. ; 12:1, s. 157-157 Journal article (peer-reviewed)abstract Owing to the significant societal value of inland water resources, there is a need for cost-effective monitoring of water quality on large scales. We tested the suitability of the recently launched Sentinel-2A to monitor a key water quality parameter, coloured dissolved organic matter (CDOM), in various types of lakes in northern Sweden. Values of a(420)CDOM (CDOM absorption at 420 nm wavelength) were obtained by analyzing water samples from 46 lakes in five districts across Sweden within an area of approximately 800 km2. We evaluated the relationships between a(420)CDOM and band ratios derived from Sentinel-2A Level-1C and Level-2A products. The band ratios B2/B3 (460 nm/560 nm) and B3/B5 (560 nm/705 nm) showed poor relationships with a(420)CDOM in Level-1C and 2A data both before and after the removal of outliers. However, there was a slightly stronger power relationship between the atmospherically-corrected B3/B4 ratio and a(420)CDOM (R2 = 0.28, n = 46), and this relationship was further improved (R2 = 0.65, n = 41) by removing observations affected by light haze and cirrus clouds. This study covered a wide range of lakes in different landscape settings and demonstrates the broad applicability of a(420)CDOM retrieval algorithms based on the B3/B4 ratio derived from Sentinel-2A. View Full-Text
11.	Boke-Olén, Niklas, et al. (author) Estimating Grazing Potentials in Sudan Using Daily Carbon Allocation in Dynamic Vegetation Model 2018 In: Rangeland Ecology and Management. - : Elsevier BV. - 1550-7424. ; 71:6, s. 792-797 Journal article (peer-reviewed)abstract Livestock production is important for local food security and as a source of income in sub-Saharan Africa. The human population of the region is expected to double by 2050, and at the same time climate change is predicted to negatively affect grazing resources vital to livestock. Therefore, it is essential to model the potential grazing output of sub-Saharan Africa in both present and future climatic conditions. Standard tools to simulate plant productivity are dynamic vegetation models (DVMs). However, as they typically allocate carbon to plant growth at an annual time step, they have a limited capability to simulate grazing. Here, we present a novel implementation of daily carbon allocation for grasses into the DVM Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) and apply this to study the grazing potential for the Kordofan region in Sudan. The results show a latitudinal split in grazing resources, where the northern parts of Kordofan are unexploited and southern parts are overused. Overall, we found that the modeled grazing potential of Kordofan is 16% higher than the livestock usage reported in the Food and Agricultural Organization of the United Nations, indicating a mitigation potential in the form of a spatial relocation of the herds.
12.	Eklund, Lina, et al. (author) On the Geopolitics of Fire, Conflict and Land in the Kurdistan Region of Iraq 2021 In: Remote Sensing. - : MDPI AG. - 2072-4292. ; 13:8, s. 1575-1575 Journal article (peer-reviewed)abstract There is limited understanding of the geopolitics of fire, conflict, and land, for example, how conflict and fire are related and how conflict impacts the biophysical environment. Since 2014, the natural environment in the Kurdistan Region of Iraq has been negatively affected by recurrent conflict that coincided with a sharp increase in the number of reported fires. Against this background, this study explores the spatiotemporal aspects of conflict, fire, and land use and land cover in this region. We combine several satellite-derived products, including land use and land cover, active fire, and precipitation. We apply a partial correlation analysis to understand the relationship between fire, conflict, climate, and land use and land cover. Conflict events and fires have increased since 2014 and have followed a similar temporal pattern, and we show that certain conflicts were particular to certain land use and land cover contexts. For example, the conflict involving the Islamic State was concentrated in southern areas with bare soil/sparse vegetation, and the conflict involving Turkey largely took place in northern mountainous areas characterized by natural vegetation and rugged topography. This dichotomy indicates divergent effects of conflict on the land system. A surprising finding was that fire hotspots had a low positive correlation with the amplitude of distance to conflict while accounting for other variables such as land cover and climate. The high statistical significance of this relationship indicates nonlinearity and implies that a larger range of distances to conflict creates more space for the fires to spread in the surrounding landscape. At the same time, fire hotspots had a weaker but negative correlation to distance from conflict events, which is somewhat expected as areas farther away from conflict locations have lower exposure risk to fires. We discuss the implications of these findings within the geopolitical context of the region and acknowledge the limitations of the study. We conclude with a summary of the main findings and recommendations for future research.
13.	Fang, Zhongxiang, et al. (author) Globally Increasing Atmospheric Aridity Over the 21st Century 2022 In: Earth's Future. - 2328-4277. ; 10:10 Journal article (peer-reviewed)abstract Vapor pressure deficit (VPD) is of great importance to control the land-atmosphere exchange of water and CO2. Here we use in situ observations to assess the performance of monthly VPD calculated from state-of-the-art data sets including CRU, ERA5, and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2). We investigate trends in VPD at global scale and for different climatic zones for 1981–2020 and future trends (2021–2100) from Coupled Model Inter-comparison Project phase 6 (CMIP6) outputs. The results show that monthly VPD estimated from CRU, ERA5, and MERRA2 correlated well against in situ estimates from 15,531 World Meteorological Organization stations, with R2 ranging between 0.92 and 0.96. Moreover, robust correlations were also found across in situ stations and when analyzing different months separately. During 1981–2020, VPD increased in all climatic zones, with the strongest increase in the arid zone, followed by tropical, temperate, cold and polar zones. CMIP6 simulations show a continuously increasing trend in VPD (0.028 hPa year−1), with the largest increase in the arid zone (0.063 hPa year−1). The magnitudes of trends are found to increase following the magnitude of CO2 increases in the future emission scenarios. We highlight that atmospheric aridification will continue under global warming, which may pose an increasing threat to terrestrial ecosystems and particularly dryland agricultural systems.
14.	Georganos, Stefanos, et al. (author) Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression 2017 In: Journal of Arid Environments. - : Elsevier BV. - 0140-1963. ; , s. 64-74 Journal article (peer-reviewed)abstract The Sahel of Africa is an eco-sensitive zone with complex relations emerging between vegetation productivity and rainfall. These relationships are spatially non-stationary, non-linear, scale dependant and often fail to be successfully modelled by conventional regression models. In response, we apply a local modelling technique, Geographically Weighted Regression (GWR), which allows for relationships to vary in space. We applied the GWR using climatic data (Normalized Vegetation Difference Index and rainfall) on an annual basis during the growing seasons (June–September) for 2002–2012. The operating scale of the Sahelian NDVI–rainfall relationship was found to stabilize around 160 km. With the selection of an appropriate scale, the spatial pattern of the NDVI-rainfall relationship was significantly better explained by the GWR than the traditional Ordinary Least Squares (OLS) regression. GWR performed better in terms of predictive power, accuracy and reduced residual autocorrelation. Moreover, GWR formed spatial clusters with local regression coefficients significantly higher or lower than those that the global OLS model resulted in, highlighting local variations. Areas near wetlands and irrigated lands displayed weak correlations while humid areas such as the Sudanian region at southern Sahel produced higher and more significant correlations. Finally, the spatial relationship of rainfall and NDVI displayed temporal variations as there were significant differences in the spatial trends throughout the study period.
15.	Hosseiny, Benyamin, et al. (author) Urban land use and land cover classification with interpretable machine learning – A case study using Sentinel-2 and auxiliary data 2022 In: Remote Sensing Applications: Society and Environment. - : Elsevier BV. - 2352-9385. ; 28 Journal article (peer-reviewed)abstract The European commission launch of the twin Sentinel-2 satellites provides new opportunities for land use and land cover (LULC) classification because of the readily availability of their data and their enhanced spatial, temporal and spectral resolutions. The rapid development of machine learning over the past decade led to data-driven models being at the forefront of high accuracy predictions of the physical world. However, the contribution of the driving variables behind these predictions cannot be explained beyond generalized metrics of overall performance. Here, we compared the performance of three shallow learners (support vector machines, random forest, and extreme gradient boosting) as well as two deep learners (a convolutional neural network and a residual network with 50 layers) in and around the city of Malmö in southern Sweden. Our complete analysis suite involved 141 input features, 85 scenarios, and 8 LULC classes. We explored the interpretability of the five learners using Shapley additive explanations to better understand feature importance at the level of individual LULC classes. The purpose of class-level feature importance was to identify the most parsimonious combination of features that could reasonably map a particular class and enhance overall map accuracy. We showed that not only do overall accuracies increase from shallow (mean = 84.64%) to deep learners (mean = 92.63%) but that the number of explanatory variables required to obtain maximum accuracy decreases along the same gradient. Furthermore, we demonstrated that class-level importance metrics can be successfully identified using Shapley additive explanations in both shallow and deep learners, which allows for a more detailed understanding of variable importance. We show that for certain LULC classes there is a convergence of variable importance across all the algorithms, which helps explain model predictions and aid the selection of more parsimonious models. The use of class-level feature importance metrics is still new in LULC classification, and this study provides important insight into the potential of more nuanced importance metrics.
16.	Jamali, Sadegh, et al. (author) Satellite-Observed Spatial and Temporal Sea Surface Temperature Trends of the Baltic Sea between 1982 and 2021 2023 In: Remote Sensing. - : MDPI AG. - 2072-4292. ; 15:1 Journal article (peer-reviewed)abstract The Baltic Sea is one of the fastest-warming marginal seas globally, and its temperature rise has adversely affected its physical and biochemical characteristics. In this study, forty years (1982–2021) of sea surface temperature (SST) data from the advanced very high resolution radiometer (AVHRR) were used to investigate spatial and temporal SST variability of the Baltic Sea. To this end, annual maximum and minimum SST stacked series, i.e., time series of stacked layers of satellite data, were generated using high-quality observations acquired at night and were fed to an automatic algorithm to detect linear and non-linear trend patterns. The linear trend pattern was the dominant trend type in both stacked series, while more pixels with non-linear trend patterns were detected when using the annual minimum SST. However, both stacked series showed increases in SST across the Baltic Sea. Annual maximum SST increased by an average of 0.062 ± 0.041 °C per year between 1982 and 2021, while annual minimum SST increased by an average of 0.035 ± 0.017 °C per year over the same period. Averaging annual maximum and minimum trends produces a spatial average of 0.048 ± 0.022 °C rise in SST per year over the last four decades.
17.	Kazemzadeh, Majid, et al. (author) Four Decades of Air Temperature Data over Iran Reveal Linear and Nonlinear Warming 2022 In: Journal of Meteorological Research. - : Springer Science and Business Media LLC. - 2095-6037 .- 2198-0934. ; 36:3, s. 462-477 Journal article (peer-reviewed)abstract Spatiotemporal analysis of long-term changes in air temperature is of prime importance for climate change research and the development of effective mitigation and adaptation strategies. Although there is considerable research on air temperature change across the globe, most of it has been on linear trends and time series analysis of nonlinear trends has not received enough attention. Here, we analyze spatiotemporal patterns of monthly and annual mean (Tmean), maximum (Tmax) and minimum (Tmin) air temperature at 47 synoptic stations across climate zones in Iran for a 40-year time period (1978–2017). We applied a polynomial fitting scheme (Polytrend) to both monthly and annual air temperature data to detect trends and classify them into linear and nonlinear (quadratic and cubic) categories. The highest magnitude of increasing trends were observed in the annual Tmin (0.47 °C per decade) and the lowest magnitude was for the annual Tmax (0.4°C per decade). Across the country, increasing trends (x̄ = 37.2%) had higher spatial coverage than the decreasing trends (x̄ = 3.2%). Warming trends in Tmean (65.3%) and Tmin (73.1%) were mainly observed in humid climate zone while warming trends in Tmax were in semi-arid (43.9%) and arid (34.1%) climates. Linear change with a positive trend was predominant in all Tmean (56.7%), Tmax (67.8%) and Tmin (71.2%) and for both monthly and annual datasets. Further, the linear trends had the highest warming rate in annual Tmin (0.83°C per decade) and Tmean (0.46°C per decade) whereas the nonlinear trends had the highest warming rate in annual Tmax (0.52°C per decade). The linear trend type was predominant in humid climate zones whereas the nonlinear trends (quadratic and cubic) were mainly observed in the arid climate zones.
18.	Metcalfe, Daniel B., et al. (author) Patchy field sampling biases understanding of climate change impacts across the Arctic 2018 In: Nature Ecology and Evolution. - : Springer Science and Business Media LLC. - 2397-334X. ; 2:9, s. 1443-1448 Journal article (peer-reviewed)abstract Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.
19.	Rizinjirabake, Fabien, et al. (author) Data for dynamics analysis of riverine dissolved organic carbon in Rukarara watershed, Rwanda 2018 In: Data in Brief. - : Elsevier BV. - 2352-3409. ; 20, s. 1252-1255 Journal article (peer-reviewed)abstract This data article presents water stage, flow, and net primary productivity (NPP) data that were used to analyze the dynamics of the riverine dissolved organic carbon (DOC) dynamics in the Rukarara River watershed in Rwanda. We measured water stage data every 15 min and calculated daily averages used to estimate flow based on rating curves. The rating curves were produced using several measured contemporaneous water stage and flow data. Estimated flow data were used to calculate water dissolved organic carbon (DOC) loadings separate the total stream flow into quick and baseflow. Annual NPP data for a 15-year period were used to estimate the effect of proportion of stream DOC loading on carbon sequestration within the Rukarara River watershed.
20.	Rizinjirabake, Fabien, et al. (author) Riverine dissolved organic carbon in Rukarara River Watershed, Rwanda 2018 In: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 643, s. 793-806 Journal article (peer-reviewed)abstract Dissolved organic carbon (DOC) loading is rarely estimated in tropical watersheds. This study quantifies DOC loading in the Rukarara River Watershed (RRW), a Rwandan tropical forest and agricultural watershed, and evaluates its relationship with hydrological factors, land use and land cover (LULC), and topography to better understand the impact of stream DOC export on watershed carbon budgets. The annual average load for the study period was 977.80 kg C, which represents approximately 8.44% of the net primary productivity of the watershed. The mean daily exports were 0.37, 0.14, 0.075 and 0.32 kg C/m2 in streams located in natural forest, tea plantation, small farming areas, and at the outlet of the river, respectively. LULC is a factor that influences DOC loading. The quick flow was the main source of stream DOC at all study sites. Stream DOC increases with increasing water flow, indicating a positive relationship. Thus, the expectation is that a change in land cover and/or rainfall will result in a change of stream DOC dynamics within the watershed. Topography was also found to influence the dynamics of stream DOC through its effect on overland flow in terms of drainage area and total length of flow paths. Tea plantations were located in areas of high drainage density and projected increase of rainfall in the region, as a consequence of climate change, could increase stream DOC content and affect stream water quality, biodiversity, balance between autotrophy and heterotrophy, and bioavailability of toxic compounds within the RRW.
21.	Sallaba, Florian, et al. (author) Future supply and demand of net primary production in the Sahel 2017 In: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 8:4, s. 1191-1221 Journal article (peer-reviewed)abstract In the 21st century, climate change in combination with increasing demand, mainly from population growth, will exert greater pressure on the ecosystems of the Sahel to supply food and feed resources. The balance between supply and demand, defined as the annual biomass required for human consumption, serves as a key metric for quantifying basic resource shortfalls over broad regions.Here we apply an exploratory modelling framework to analyse the variations in the timing and geography of different NPP (net primary production) supply-demand scenarios, with distinct assumptions determining supply and demand, for the 21st century Sahel. We achieve this by coupling a simple NPP supply model forced with projections from four representative concentration pathways with a global, reduced-complexity demand model driven by socio-economic data and assumptions derived from five shared socio-economic pathways.For the scenario that deviates least from current socio-economic and climate trends, we find that per capita NPP begins to outstrip supply in the 2040s, while by 2050 half the countries in the Sahel experience NPP shortfalls. We also find that despite variations in the timing of the onset of NPP shortfalls, demand cannot consistently be met across the majority of scenarios. Moreover, large between-country variations are shown across the scenarios, in which by the year 2050 some countries consistently experience shortage or surplus, while others shift from surplus to shortage. At the local level (i.e. grid cell), hotspots of total NPP shortfall consistently occur in the same locations across all scenarios but vary in size and magnitude. These hotspots are linked to population density and high demand. For all scenarios, total simulated NPP supply doubles by 2050 but is outpaced by increasing demand due to a combination of population growth and the adoption of diets rich in animal products. Finally, variations in the timing of the onset and end of supply shortfalls stem from the assumptions that underpin the shared socio-economic pathways rather than the representative concentration pathways.Our results suggest that the UN sustainable development goals for eradicating hunger are at high risk for failure. This emphasizes the importance of policy interventions such as the implementation of sustainable and healthy diets, family planning, reducing yield gaps, and encouraging the transfer of resources to impoverished areas via trade relations.
22.	Virkkala, Anna-maria Ilona, et al. (author) Identifying multidisciplinary research gaps across Arctic terrestrial gradients 2019 In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 14:12 Journal article (peer-reviewed)abstract Global warming is driving environmental change in the Arctic. However, our current understanding of this change varies strongly among different environmental disciplines and is limited by the number and distribution of field sampling locations. Here, we use a quantitative framework based on multivariate statistical modeling to present the current state of sampling across environmental disciplines in the Arctic. We utilize an existing database of georeferenced Arctic field studies to investigate how sampling locations and citations of disciplines are distributed across Arctic topographical, soil and vegetation conditions, and highlight critical regions for potential new research areas in different disciplines. Continuous permafrost landscapes, and the northernmost Arctic bioclimatic zones are studied and cited the least in relation to their extent in many disciplines. We show that the clusters of sampling locations and citations are not uniform across disciplines. Sampling locations in Botany and Biogeochemistry cover environmental gradients the best, and Microbiology, Meteorology, Geosciences and Geographic Information Systems / Remote Sensing / Modeling have the worst coverage. We conclude that across all disciplines, more research is needed particularly in the Canadian Arctic Archipelago, northern Greenland, central and eastern Siberia, and in some disciplines, in Canadian mainland, central Alaska, western Siberia and northern Taimyr region. We provide detailed maps of potential new sampling locations for each environmental discipline that consider multiple variables simultaneously. These results will help prioritize future research efforts, thus increasing our knowledge about the Arctic environmental change.

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