Cumulative effects, anthropogenic changes, and modern life paths in sub-Arctic contexts. Envisioning the future in Northeastern British Columbia: the case of the Doig and Blueberry River First Nations

This work is an attempt to describe what is happening in North-eastern British Columbia, in an area where extractivism intertwined with the market-driven economy had been generating changes not always foreseen, understood, and mitigated. Drawing on my year of fieldwork (July 2019 - August 2020), I explore how the traditional lifestyle and socio-economic organization of the Doig and Blueberry River First Nations have been changed by the cumulative effects of industrial development. At first glance, resource extraction may be perceived as a solution to tackle the many problems of scattered and isolated Indigenous communities (i.e. unemployment, lack of opportunities for socio-cultural and economic continuity in the area). However, enjoying the benefits extractivism produces comes at a high price. It impacts Indigenous cosmovision and cultural heritage while shaping how community members envision the future and the kind of future(s) they perceive as possible. The timeliness of this ethnographic work is also confirmed by the litigation BRFN v. BC (2015-2021). For the first time in Canadian legal history, a trial on cumulative effects intertwined with Treaty 8 infringements and the recognition of Constitutional rights was initiated by a First Nation Band in an attempt to stop development projects to which the Band did not give its consent. The litigation came to an end in June 2021, with a ground-breaking verdict in which it was judged that the BC province could not continue to authorize activities that breach Treaty 8 and its unwritten promises. As a result, on 7th October 2021, a preliminary agreement between BRFN and the BC Government was reached. The province has agreed to allocate a total amount of C$ 65 million to the BRFN for land restoration activities and cultural practices revitalization. To explain the complex reality community members (and Fort St. John residents) meet in their everyday lives while facing extractivism, I introduce the concept of ‘atemporal modernity’ as an (a)temporal status in continuous becoming. I argue that people are trapped in such a status, perpetually waiting for a better future yet to come, which can only be achieved through extractivism. By letting people talk, I try to describe their everyday challenges while exploring which kind of future(s) community members envision to keep living off the land as long as ‘the sun shines, the rivers flow, and the grass grows’

Implementing UNDRIP in British Columbia in a Post-Yahey Context: What to Expect After the Yahey v. BC Litigation (S151727) and the Agreement on Industrial Development and Cumulative Effects Management

Almost two years after the ground-breaking verdict that the Supreme Court of British Columbia issued in the context of the Yahey v. BC litigation, on January 18, 2023, the Province of British Columbia signed a historic agreement with Blueberry River First Nation (BRFN) to address the cumulative effects of industrial development on the meaningful exercise of Treaty 8 rights in the Nation’s traditional territory while establishing collaborative approaches to land and resource planning. At the same time, the Province concluded agreements with other Treaty 8 First Nations (Doig River, Fort Nelson, McLeod Lake, Prophet River, Saulteau and West Moberly First Nations) concerning cumulative effects management, land planning and resource exploitation. These agreements have been praised as ground-breaking steps towards a new relationship that Government and Industry are eager to build with First Nations while healing the land and ensuring certainty for Industry to carry on resource development in British Columbia. This happens as the Province and the Federal Government move forward with their action plans to implement the United Nations Declaration on the Rights of Indigenous Peoples (hereafter UNDRIP) at the provincial and federal levels. It also comes at a time of significant challenges British Columbia must face, between new First Nations development projects (i.e., the Cedar LNG project) that the Province is actively supporting and recent litigations initiated by some First Nations to see UNDRIP adequately implemented in the BC legal framework (i.e., the trial initiated by Gitxaala and Ehattesaht First Nations concerning the lack of consultation regarding how BC grants mineral claims).

TopoVar90m: Global high-resolution topographic variables for environmental modeling

Topographical relief involves the vertical and horizontal variation of the Earth\u27s terrain and it drives processes in hydrology, climatology, geography and ecology. Its assessment and characterization is fundamental for various types of modeling and simulation analysis. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) currently provides the best high-resolution DEM globally available, at a 3 arc-second resolution (90m), due to the removal of multiple error components from the underlying SRTM3 and AW3D30 DEMs. To depict topographical variations worldwide, we developed a new dataset comprising different terrain features derived from the MERIT-DEM. The fully standardized topographical variables consist of slope, aspect, eastness, northness, roughness, terrain roughness index, vector ruggedness measure, topographic position index, stream power index, convergence, profile/tangential curvature, first/second order partial derivative and 10 geomorphological landform classes with their parameters features (intensity, exposition, range, variance, elongation, azimuth, extend and width). To assess how potential errors in the MERIT-DEM affect the derived topographic variables, we compared our results with the same variables derived from the National Elevation Dataset (NED), which is the best-available gridded elevation dataset for the United States. We compared the two data sources by calculating the first order derivative (i.e., rate of change through space measured in degrees) of the difference between a MERIT- derived vs. a NED-derived topographic variable. All newly-created topographic variables are readily available at a 3 arc-second resolution, for use as input data in various environmental models and analyses in the field of geography, geology, hydrology, ecology and biogeography

Exploring the Relationships of Fire Occurrence Variables by Means of CART and MARS Models

Recently, in the framework of long-term fire risk assessment, researcher have implemented spatial and non-spatial non-parametric prediction models to discover complex relationships among wildfire variables. The main scope was to overcome the assumption of spatial stationarity in the relationship among the response variable and the predictors, assumed by the traditional regression techniques. The present article aims to test and compare the potential of the CART and MARS models in predicting fire occurrence at local scale. The test is performed in the Arno River Basin, a fire prone area located in the central part of Italy. Road network, topographic variables and population data were implemented to build up fire prediction model using 1621 ignition points recorded during the period 1997-2003. The models produce two prediction maps slightly similar. In general the CART model overperform compare to the MARS one. Nonetheless, the MARS model produces a smoothened surface that theoretically better follow the probability of a fire event.JRC.H.7-Land management and natural hazard

Spectral Temporal Information for Missing Data Reconstruction (STIMDR) of Landsat Reflectance Time Series

The number of Landsat time-series applications has grown substantially because of its approximately 50-year history and relatively high spatial resolution for observing long term changes in the Earth’s surface. However, missing observations (i.e., gaps) caused by clouds and cloud shadows, orbit and sensing geometry, and sensor issues have broadly limited the development of Landsat time-series applications. Due to the large area and temporal and spatial irregularity of time-series gaps, it is difficult to find an efficient and highly precise method to fill them. The Missing Observation Prediction based on Spectral-Temporal Metrics (MOPSTM) method has been proposed and delivered good performance in filling large-area gaps of single-date Landsat images. However, it can be less practical for a time series longer than one year due to the lack of mechanics that exclude dissimilar data in time series (e.g., different phenology or changes in land cover). To solve this problem, this study proposes a new gap-filling method, Spectral Temporal Information for Missing Data Reconstruction (STIMDR), and examines its performance in Landsat reflectance time series. Two groups of experiments, including 2000 × 2000 pixel Landsat single-date images and Landsat time series acquired from four sites (Kenya, Finland, Germany, and China), were performed to test the new method. We simulated artificial gaps to evaluate predicted pixel values with real observations. Quantitative and qualitative evaluations of gap-filled images through comparisons with other state-of-the-art methods confirmed the more robust and accurate performance of the proposed method. In addition, the proposed method was also able to fill gaps contaminated by extreme cloud cover for a period (e.g., winter in high-latitude areas). A down-stream task of random forest supervised classification through both gap-filled simulated datasets and the original valid datasets verified that STIMDR-generated products are relevant to the user community for land cover applications

Forest Fires in Europe 2006

This is the seventh Forest Fires in Europe report published by the European Commission. The report is normally published in summer of the following year in order to allow the different countries to compile official statistics of the fire season regarding the total number of forest fires and burned area. The fire season of 2006 can be defined as a relatively mild season, and if the total number of fires was still relatively high, the total burned area was definitely well below the average. In general there were not many extreme fire events and only the large fires that devastated Galicia (Spain) in the first two weeks of August, were object of great concern. The Forest Fires in Europe 2006 report describes the latest developments in terms of support to forest fires fire prevention activities in the European Union, presents historical statistics in terms of number of fires and burned area, and describes the fire season in each of the contributing countries as well as the results from the European Forest Fire Information System: EFFIS Danger Forecast, that provides daily the 1, 2, and 3 day fire danger forecasts, EFFIS Rapid Damage Assessment, that performs the mapping and evaluation of land cover damages caused by fires of at least 50 ha, and includes also a summary of the impact of forest fires in Natura2000 areas in Galicia, Spain, in 2006.JRC.H.7-Land management and natural hazard

Forest Fires in Europe 2007

The long time series of forest fire data available for these 5 southern countries (Portugal, Spain, France, Italy and Greece) justifies a separate analysis as it has been the case in previous reports. During 2007, fires in these 5 countries burned a total are of 574 361 hectares, which is well above the average for the last 28 years. On the other hand, the number of fires that occured (42 259) is below the average for the last 28 years (see Table 1 for details). Figure 1a shows the total burnt area per year in the five Southern Member States since 1980. The statistics vary considerably from one year to the next, which clearly indicates how much the burnt area depends on seasonal metereological conditions.JRC.H.7-Land management and natural hazard

Estimating nitrogen and phosphorus concentrations in streams and rivers, within a machine learning framework.

Funder: University of Cambridge, Department of ZoologyFunder: NASA NNX17AI74GNitrogen (N) and Phosphorus (P) are essential nutritional elements for life processes in water bodies. However, in excessive quantities, they may represent a significant source of aquatic pollution. Eutrophication has become a widespread issue rising from a chemical nutrient imbalance and is largely attributed to anthropogenic activities. In view of this phenomenon, we present a new geo-dataset to estimate and map the concentrations of N and P in their various chemical forms at a spatial resolution of 30 arc-second (∼1 km) for the conterminous US. The models were built using Random Forest (RF), a machine learning algorithm that regressed the seasonally measured N and P concentrations collected at 62,495 stations across the US streams for the period of 1994-2018 onto a set of 47 in-house built environmental variables that are available at a near-global extent. The seasonal models were validated through internal and external validation procedures and the predictive powers measured by Pearson Coefficients reached approximately 0.66 on average

Estimating nitrogen and phosphorus concentrations in streams and rivers, within a machine learning framework.

Funder: University of Cambridge, Department of ZoologyFunder: NASA NNX17AI74GNitrogen (N) and Phosphorus (P) are essential nutritional elements for life processes in water bodies. However, in excessive quantities, they may represent a significant source of aquatic pollution. Eutrophication has become a widespread issue rising from a chemical nutrient imbalance and is largely attributed to anthropogenic activities. In view of this phenomenon, we present a new geo-dataset to estimate and map the concentrations of N and P in their various chemical forms at a spatial resolution of 30 arc-second (∼1 km) for the conterminous US. The models were built using Random Forest (RF), a machine learning algorithm that regressed the seasonally measured N and P concentrations collected at 62,495 stations across the US streams for the period of 1994-2018 onto a set of 47 in-house built environmental variables that are available at a near-global extent. The seasonal models were validated through internal and external validation procedures and the predictive powers measured by Pearson Coefficients reached approximately 0.66 on average

Hydrography90m: a new high-resolution global hydrographic dataset

The geographic distribution of streams and rivers drives a multitude of patterns and processes in hydrology, geomorphology, geography, and ecology. Therefore, a hydrographic network that accurately delineates both small streams and large rivers, along with their topographic and topological properties, with equal precision would be indispensable in the earth sciences. Currently, available global hydrographies do not feature small headwater streams in great detail. However, these headwaters are vital because they are estimated to contribute to more than 70 % of overall stream length. We aimed to fill this gap by using the MERIT Hydro digital elevation model at 3 arcsec (∼90 m at the Equator) to derive a globally seamless, standardised hydrographic network, the “Hydrography90m”, with corresponding stream topographic and topological information. A central feature of the network is the minimal upstream contributing area, i.e. flow accumulation, of 0.05 km2 (or 5 ha) to initiate a stream channel, which allowed us to extract headwater stream channels in great detail. By employing a suite of GRASS GIS hydrological modules, we calculated the range-wide upstream flow accumulation and flow direction to delineate a total of 1.6 million drainage basins and extracted globally a total of 726 million unique stream segments with their corresponding sub-catchments. In addition, we computed stream topographic variables comprising stream slope, gradient, length, and curvature attributes as well as stream topological variables to allow for network routing and various stream order classifications. We validated the spatial accuracy and flow accumulation of Hydrography90m against NHDPlus HR, an independent, national high-resolution hydrographic network dataset of the United States. Our validation shows that the newly developed Hydrography90m has the highest spatial precision and contains more headwater stream channels compared to three other global hydrographic datasets. This comprehensive approach provides a vital and long-overdue baseline for assessing actual streamflow in headwaters and opens new research avenues for high-resolution studies of surface water worldwide. Hydrography90m thus offers significant potential to facilitate the assessment of freshwater quantity and quality, inundation risk, biodiversity, conservation, and resource management objectives in a globally comprehensive and standardised manner. The Hydrography90m layers are available at https://doi.org/10.18728/igb-fred-762.1 (Amatulli et al., 2022a), and while they can be used directly in standard GIS applications, we recommend the seamless integration with hydrological modules in open-source QGIS and GRASS GIS software to further customise the data and derive optimal utility from it