2,066 research outputs found

    Variation in mainland Northwest Territories late-winter muskox (Ovibos moschatus) density estimations and habitat associations above and below treeline.

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    The Arctic and Sub-Arctic ecosystems are seeing accelerated changes in temperature, landcover, and consequently species abundance and distributions. Reliable distributions, and associated population density estimates, are essential for effective conservation and management efforts. Growing concerns from northern communities regarding the relationship between muskox and declining caribou populations strengthens the need for updated information on muskox populations within mainland Northwest Territories (NWT). The first objective for my research was to quantify and map updated winter estimates of abundance, density, and distribution of muskoxen within three recent survey regions located in mainland NWT, using a multiple covariate distance sampling method (MCDS), paired with density surface modelling (DSM). My second objective was to explore spatial and social predictors of muskox habitat associations to help infer the extent and potential causes of their contemporary southward expansion across mainland NWT. I tested two competing hypotheses that drive ungulate distributions generally across large spatial and temporal scales of high habitat heterogeneity, as encompassed by the study regions investigated here; muskox density and distribution may be driven by the nutritional landscape where environmental covariates representing high forage quality best predict muskox occurrence. Alternatively, muskox density and distribution may be driven by a predatory landscape, where environmental covariates that support antipredator grouping behaviours best predict muskox occurrence. Through my analyses I infer muskox populations are stable in northern regions (the Sahtú and Beaufort Delta regions) and growing in southern regions (the East Arm region) of mainland NWT; range expansion of muskoxen appears to be continuing southward beyond their historical boundary. I showed varying support for both hypotheses. Muskox density was best predicted by nutritionally important environmental covariates but muskox distribution did not uphold my nutritional hypothesis, while group size was often correlated with land cover that supports antipredator grouping behaviours. However, weak, and inconsistent results across all regions suggest that unmeasured environmental conditions that occur similarly in all regions may also influence muskox occurrence and grouping behaviours. Snow depth and predator occurrence may be important considerations for future investigation. I suggest continued and expanded aerial survey efforts and additional environmental data collected at finer spatial grains may help to inform future muskox density and distribution analyses across mainland NWT

    Tipping Points and Early Warning Signals in the Climate-Carbon System

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    This is a thesis about tipping points and early warning signals. The tipping points investigated are related to various components of the climate-carbon system. In contrast, the work on early warning signals has more generic applications, however in this thesis they are analysed in the context of the climate-carbon system. The thesis begins with an introduction to the climate-carbon system as well as a discussion of tipping points in the Earth system. Then a more mathematical summary of tipping points and early warning signals is given. An investigation into the ‘compost bomb’ is undertaken, in which the spatial structure of soils is accounted for. It is found that a hot summer could cause a compost bomb. The effect of biogeochemical heating on the stability of the global carbon cycle is investigated and it is found to play only a small role. The potential for instabilities in the climate-carbon cycle is further investigated when the dynamic behaviour of the ocean carbon cycle is accounted for. It is found that some CMIP6 models may be close to having an unstable carbon cycle. Spatial early warning signals are investigated in the context of more rapidly forced systems. It is found that spatial early warning signals perform better when the system is rapidly forced compared with time series based early warning signals. The typical assumptions about white noise made when using early warning signals are also studied. It is found that time correlated noise may mask the early warning signal. It is shown that a spectral analysis can avoid this problem.European Commissio

    An empirical assessment of the potential of post-fire recovery of tree-forest communities in Mediterranean environments

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    The accumulation of fuel and the homogenization of the landscape in Mediterranean forests are leading to an increasingly hazardous behavior of wildfires, fostering larger, more intense, severe, and frequent wildfires. The onset of climate change is intensifying this behavior, fostering the occurrence of extreme forest fires threatening the persistence of forest communities. In this study we present an assessment of the post-fire recovery potential of the most representative tree-forest communities affected by fire in Spain: Pinus halepensis, Pinus nigra, Pinus pinaster and Quercus ilex. A large database of field data collected during specific campaigns -carried out 25 years after the fire- is used in combination with remote sensing, forest inventory and geospatial data to build an empirical model capable of predicting the chances of recovery. The model, calibrated using Random Forest, combines information on burn severity (remote sensing estimates of the Composite Burn Index), local topography (slope and terrain aspect) and climatic data (mean values and trends of temperature and precipitation) to provide information on the degree of similarity (vegetation height, horizontal cover of the vegetation layer along vertical strata, aboveground biomass and species diversity) between the plots burned in the summer of 1994 and the unburned control. Overall, only 33 out of the 131 burned plots could be considered as recovered, that is, reaching a similar state to unburned stands in neighboring areas. Our results suggest a primary role played by burn severity (the higher the severity the lower the probability of recovery), but strongly modulated by local topographic features (higher probability of recovery on steep north-facing slopes). In turn, increasingly warm and wetter conditions increased the chance of recovery

    Response of soil nutrients and erodibility to slope aspect in the northern agro-pastoral ecotone, China

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    Soil erosion, considered a major environmental and social problem, leads to the loss of soil nutrients and the degradation of soil structure and impacts plant growth. However, data on the effects of land use changes caused by vegetation restoration on soil nutrients and erodibility for different slope aspects are limited. This study was conducted to detect the response of soil nutrients and erodibility to slope aspect in a typical watershed in the northern agro-pastoral ecotone in China. The following indexes were used to determine the improvement in soil nutrients and erodibility through a weighted summation method: the comprehensive soil nutrient index and the comprehensive soil erodibility index. The results showed that the vegetation types with the highest comprehensive soil quality index (CSQI) values on western, northern, southern, and eastern slopes were Pinus sylvestris and Astragalus melilotoides (1.45), Caragana korshinskii and Capillipedium parviflorum (2.35), Astragalus melilotoides (4.78), and Caragana korshinskii and Lespedeza bicolor (5.00), respectively. Slope aspect had a significant effect on understory vegetation characteristics, soil nutrients, and soil erodibility. Understory vegetation and soil characteristics explained 50.86 %–74.56 % of the total variance in soil nutrients and the erodibility. Mean weight diameter and total phosphorus were the main factors that affected the CSQI for different slope aspects. Our study suggests that the combinations of species, such as C. korshinskii and L. bicolor, were the optimal selection to improve soil nutrients and soil erodibility for any slope aspect.</p

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    In-season crop yield forecasting in Africa by coupling remote sensing and crop modeling: A systematic literature review

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    Timely and accurate estimation of crop yield before harvest is crucial for national food policy and security assessments. Crop models and remote sensing techniques have been combined and applied in crop yield estimation on a regional scale. Previous studies have proposed models for estimating canopy state variables and soil properties based on remote sensing data and assimilating these estimated canopy state variables into crop models. This paper presents an overview of the comparative introduction, latest developments and applications of crop models, remote sensing techniques, and data assimilation methods in the growth status monitoring and yield estimation of crops, facilitating the improvement of crop models and RS coupling approach in Africa

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    Avaliação de dados polarimétricos e de atributos de textura em imagens SAR para discriminar a floresta secundária em uma área de domínio de floresta amazônica

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    This study aims to evaluate the ability of Sentinel-1 polarimetric and backscatter attributes in relation to COSMO-SkyMed (CSM) texture and backscatter features to discriminate secondary vegetation areas in an Amazon Forest domain area, located in Mato Grosso state. In this study, we used polarizations VV and VH from Sentinel-1 Synthetic Aperture Radar (SAR) image and HH from CSM SAR image, both in Single Look Complex format. In the Sentinel-1 image, a covariance matrix was generated and the H-Alpha target decomposition theorem was applied, allowing to obtain the attributes Entropy and Angle alpha. In the CSM image obtained the Gray-Level Co-Occurrence Matrix (GLCM) texture attributes: dissimilarity, contrast, homogeneity and second moment. The Support Vector Machine (SVM) algorithm was used for the classification. The Sentinel-1 polarimetric attributes result, with a Kappa index of 0.70 and an overall accuracy of 79.58%, performed better than those derived from CSM, with a Kappa index of 0.56 and overall accuracy 63.67%. However, the Sentinel-1 and CSM attributes did not present satisfactory results to discriminate the different stages of secondary forest.O objetivo do presente estudo foi avaliar a capacidade de atributos polarimétricos e de retroespalhamento do Sentinel-1 em relação às feições de textura e de retroespalhamento do COSMO-SkyMed (CSM), em discriminar diferentes estágios de floresta secundária em uma área de domínio de Floresta Amazônica, no estado do Mato Grosso. Neste estudo, utilizou-se uma imagem de Radar de Abertura Sintética (SAR) do Sentinel-1 nas polarizações VV e VH e uma imagem SAR do CSM na polarização HH, ambas no formato Single Look Complex. Na imagem Sentinel-1 foi gerada a matriz de covariância e aplicado o teorema de decomposição de alvos H-Alpha, para obtenção dos atributos Entropia e Ângulo alfa. Na imagem CSM, foram obtidos os atributos de textura a partir da matriz de co-ocorrência de níveis de cinza (GLCM): dissimilaridade, contraste, homogeneidade e segundo momento. Para a classificação, foi utilizado o algoritmo Máquina de Vetores de Suporte (SVM). A classificação derivada dos atributos polarimétricos do Sentinel-1, com índice Kappa de 0,70 e exatidão global de 79,58%, apresentou desempenho superior àquela derivada do CSM, com índice Kappa de 0,56 e exatidão global de 63,67%. Entretanto, tanto os atributos derivados do Sentinel-1 como do CSM não apresentaram resultados satisfatórios para discriminar os diferentes estágios de floresta secundária

    The structure of maturity: immature trees may drive the productivity of mature forests

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    Relating forest productivity to local variations in forest structure has been a long-standing challenge. Previous studies often focused on the connection between forest structure and stand-level photosynthesis (GPP). However, biomass production (NPP) and net ecosystem exchange (NEE) are also subject to respiration and other carbon losses, which vary with local conditions and life history traits. Here, we use a simulation approach to study how these losses impact forest productivity and reveal themselves in forest structure. We fit the process-based forest model Formind to a 25ha inventory of an old-growth temperate forest in China and classify trees as "mature" (full-grown) or "immature" based on their intrinsic carbon use efficiency. Our results reveal a strong negative connection between the stand-level carbon use efficiency and the prevalence of mature trees: GPP increases with the total basal area, whereas NPP and NEE are driven by the basal area of immature trees. Accordingly, the basal area entropy - a structural proxy for the prevalence of immature trees - correlated well with NPP and NEE and had higher predictive power than other structural characteristics such as Shannon diversity and height standard deviation. Our results were robust across spatial scales (0.04-1ha) and yield promising hypotheses field studies and new theoretical work
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