Utilisation des aménagements agroforestiers linéaires par les mammifères en milieu agricole intensif

L'intensification agricole entraîne une vaste perte d'habitat et de connectivité du paysage. Les espèces subsistantes dans ces paysages dominés par l'agriculture utilisent souvent des éléments du paysage linéaires et minces, comme des haies brise-vent et des fossés végétalisés, en tant qu’habitat ou comme corridor de déplacement entre les parcelles d’habitat. Toutefois, la compréhension de l’utilisation de ces aménagements agroforestiers linéaires (AAL) par la faune est limitée et pourrait profiter de l’utilisation de données de télédétection à haute résolution, qui sont non biaisées, détaillées et reproductibles. Le but de cette étude est d’évaluer les caractéristiques qui affectent l’utilisation des AAL par les mammifères de moyenne et grande taille, avec des données in situ et de télédétection, dans un paysage dominé par l’agriculture dans le sud du Québec. Vingt-trois AAL ont été sélectionnés et caractérisés, à la fois par des relevés terrain et des analyses de télédétection (entre autres métriques LiDAR et indices de végétation). La fréquentation de chaque AAL par les mammifères a été mesurée à l'aide de pièges photographiques, de la fin du printemps au début de l'automne 2018. Nous avons obtenu 431 détections de mammifères, tous les AAL combinés. Parmi ces détections, sept espèces ont été répertoriées, toutes opportunistes et bien adaptées au milieu agricole. Nos résultats démontrent qu’il y a des différences significatives dans l'utilisation des AAL par les mammifères, liées à l'influence unique de l’assemblage des caractéristiques considérés. Une dizaine de modèles de régression ont été testés et le modèle retenu basé sur l'AICc comprend plusieurs caractéristiques, tant locales que du paysage. Les coefficients de ce modèle indiquent une relation positive entre l’utilisation des AAL par les mammifères et leur longueur, le couvert arborescent et la quantité d’habitat environnant, alors que cette relation est négative avec la largeur et les perturbations anthropiques. Les données dérivées de télédétection ont contribué à ce modèle final, rappelant leur utilité dans les études sur les habitats fauniques. Ces résultats indiquent que de nombreux facteurs semblent influencer l’utilisation des AAL dans le sud du Québec, que ce soit comme corridor ou comme habitat pour les mammifères. Les informations fournies par cette étude ont généré des suggestions pour une gestion favorable des AAL et la conservation de la faune sauvage en milieu agricole.Agricultural intensification causes habitat modification, sometimes leading to habitat loss and subsequent loss of connectivity. Remaining species in these agriculture-dominated landscapes often use hedgerows, such as windbreaks or riparian strips, as movement corridors or even as habitats. However, the understanding of the use of these hedgerows by mammals is limited and could be improved with the use of high-resolution remote sensing data, which are unbiased, detailed and repeatable. The aim of this study was to assess the attributes that affect medium- and large-sized mammals’ use of hedgerows, with in situ and remotely sensed data (including LiDAR and multispectral images) in an agriculture-dominated landscape in southern Québec. Twenty-three hedgerows were selected and characterized with both field surveys and remote sensing analyses, like LiDAR metrics and vegetation indices. Wildlife frequentation of each hedgerow was measured using camera traps, from late spring to early fall in 2018. 431 mammal detections were obtained among all 23 hedgerows. From this, seven species were recorded, all of them opportunistic and well adapted to agricultural environment. Results showed significant differences in mammal use of hedgerows. Coefficients of the better-ranked models based on AICc indicated a positive relationship between hedgerow length and their use by mammals, and a negative relationship with the hedgerow width. Hedgerow use by mammals also increased as tree cover increased, as habitat became more available and as human disturbance decreased. These results characterized for the first time the variables influencing hedgerow use by a broad set of medium- and large-sized mammal species and confirmed their use as both movement corridor and habitat. This study also confirmed the complementary usefulness of variables derived from remote sensing combined with field data. The low explanatory power of variables often cited in the literature (e.g. NDVI, canopy height) also highlights the need to further explore their specific influence on mammals. The information provided by this study supports the beneficial role played by hedgerows for wildlife conservation in intensive agricultural landscapes. Management guidelines are provided as well as future research avenues

Monitoring the Sustainable Intensification of Arable Agriculture:the Potential Role of Earth Observation

Sustainable intensification (SI) has been proposed as a possible solution to the conflicting problems of meeting projected increases in food demand and preserving environmental quality. SI would provide necessary production increases while simultaneously reducing or eliminating environmental degradation, without taking land from competing demands. An important component of achieving these aims is the development of suitable methods for assessing the temporal variability of both the intensification and sustainability of agriculture. Current assessments rely on traditional data collection methods that produce data of limited spatial and temporal resolution. Earth Observation (EO) provides a readily accessible, long-term dataset with global coverage at various spatial and temporal resolutions. In this paper we demonstrate how EO could significantly contribute to SI assessments, providing opportunities to quantify agricultural intensity and environmental sustainability. We review an extensive body of research on EO-based methods to assess multiple indicators of both agricultural intensity and environmental sustainability. To date these techniques have not been combined to assess SI; here we identify the opportunities and initial steps required to achieve this. In this context, we propose the development of a set of essential sustainable intensification variables (ESIVs) that could be derived from EO data

Modelling susceptibility to Parthenium hysterophorus invasion in KwaZulu-Natal Province, South Africa using physical, climatic and remotely sensed derived variables.

Master of Science in Environmental Sciences. University of KwaZulu-Natal. Pietermaritzburg, 2018.Invasive alien plants (IAP) are considered as one of the major causes of global change. Parthenium hysterophorus is recognized as one of the world’s most aggressive, harmful and extremely resilient invasive plant species. It has adverse impacts on the environment, economies, biodiversity, human health and agriculture. Identification and modelling of areas vulnerable to Parthenium invasion is critical for proactive control and site- specific management of its spread. This study sought to test the performance of Maxent algorithm in modelling habitats susceptible to Parthenium invasion using selected environmental and physical variables and remotely sensed data. Specifically, the study sought to identify key physical and bio-climatic variables that influence the distribution of Parthenium. Furthermore, the study sought to determine the value of the freely available Sentinel 2 multispectral instrument (MSI) datasets in concert with environmental variables in modelling habitat susceptible to Parthenium invasion. The Maximum Entropy model (MaxEnt) machine learning algorithm was used to model Parthenium invasion using presence - only records (n = 274). Results showed that landscapes characterized by low elevation, close proximity to roads and high precipitation were the most susceptible to Parthenium invasion. An Area under curve (AUC) value of 0.946 was attained, indicating that the model derived using the aforementioned optimal physical and bio-climatic variables performed better than random. Based on the high AUC values, results also showed that all the model scenarios derived from spectral bands and environmental variables, vegetation indices and environmental variables and a combination of spectral bands, vegetation indices and environmental variables performed better than random, with AUC values of 0.976, 0.970 and 0.974, respectively. The higher accuracy exhibited by the optimal model (bands and environmental variables) can be attributed to the integration of red edge band centered at 705 nm in Sentinel 2 MSI and environmental variables in predicting areas susceptible to Parthenium. Overall, these results demonstrate the potential of integrating the freely available Sentinel 2 MSI data and environmental variables to improve the mapping of habitat susceptibility to Parthenium invasion. These results could be beneficial for early detection, site -specific weed management and long-term monitoring

Challenges and opportunities in harnessing satellite remote-sensing for biodiversity monitoring

The ability of remote-sensing technologies to rapidly deliver data on habitat quantity (e.g., amount, configuration) and quality (e.g., structure, distribution of individual plant species, habitat types and/or communities, persistence) across a range of spatial resolutions and temporal frequencies is increasingly sought-after in conservation management. However, several problematic issues (e.g., imagery correction and registration, image interpretation, habitat type and quality definitions, assessment and monitoring procedures, uncertainties inherent in mapping, expert knowledge integration, scale selection, analysis of the interrelationships between habitat quality and landscape structure) challenge the effective and reliable use of such data and techniques. We discuss these issues, as a contribution to the development of a common language, framework and suite of research approaches among ecologists, remote-sensing experts and stakeholders (conservation managers) on the ground, and highlight recent theoretical and applied advances that provide opportunities for meeting these challenges. Reconciling differing stakeholder perspectives and needs will boost the timely provisioning of reliable information on the current and changing distribution of biodiversity to enable effective conservation managemen

Challenges and opportunities in harnessing satellite remote-sensing for biodiversity monitoring

The ability of remote-sensing technologies to rapidly deliver data on habitat quantity (e.g., amount, configuration) and quality (e.g., structure, distribution of individual plant species, habitat types and/or communities, persistence) across a range of spatial resolutions and temporal frequencies is increasingly sought-after in conservation management. However, several problematic issues (e.g., imagery correction and registration, image interpretation, habitat type and quality definitions, assessment and monitoring procedures, uncertainties inherent in mapping, expert knowledge integration, scale selection, analysis of the interrelationships between habitat quality and landscape structure) challenge the effective and reliable use of such data and techniques. We discuss these issues, as a contribution to the development of a common language, framework and suite of research approaches among ecologists, remote-sensing experts and stakeholders (conservation managers) on the ground, and highlight recent theoretical and applied advances that provide opportunities for meeting these challenges. Reconciling differing stakeholder perspectives and needs will boost the timely provisioning of reliable information on the current and changing distribution of biodiversity to enable effective conservation managemen

Challenges and opportunities in harnessing satellite remote-sensing for biodiversity monitoring

The ability of remote-sensing technologies to rapidly deliver data on habitat quantity (e.g., amount, configuration) and quality (e.g., structure, distribution of individual plant species, habitat types and/or communities, persistence) across a range of spatial resolutions and temporal frequencies is increasingly sought-after in conservation management. However, several problematic issues (e.g., imagery correction and registration, image interpretation, habitat type and quality definitions, assessment and monitoring procedures, uncertainties inherent in mapping, expert knowledge integration, scale selection, analysis of the interrelationships between habitat quality and landscape structure) challenge the effective and reliable use of such data and techniques. We discuss these issues, as a contribution to the development of a common language, framework and suite of research approaches among ecologists, remote-sensing experts and stakeholders (conservation managers) on the ground, and highlight recent theoretical and applied advances that provide opportunities for meeting these challenges. Reconciling differing stakeholder perspectives and needs will boost the timely provisioning of reliable information on the current and changing distribution of biodiversity to enable effective conservation management

Challenges and opportunities in harnessing satellite remote-sensing for biodiversity monitoring

8restrictedInternationalBothThe ability of remote-sensing technologies to rapidly deliver data on habitat quantity (e.g., amount, configuration) and quality (e.g., structure, distribution of individual plant species, habitat types and/or communities, persistence) across a range of spatial resolutions and temporal frequencies is increasingly sought-after in conservation management. However, several problematic issues (e.g., imagery correction and registration, image interpretation, habitat type and quality definitions, assessment and monitoring procedures, uncertainties inherent in mapping, expert knowledge integration, scale selection, analysis of the interrelationships between habitat quality and landscape structure) challenge the effective and reliable use of such data and techniques. We discuss these issues, as a contribution to the development of a common language, framework and suite of research approaches among ecologists, remote-sensing experts and stakeholders (conservation managers) on the ground, and highlight recent theoretical and applied advances that provide opportunities for meeting these challenges. Reconciling differing stakeholder perspectives and needs will boost the timely provisioning of reliable information on the current and changing distribution of biodiversity to enable effective conservation managementrestrictedMairota, P.; Cafarelli, B.; Didham, R.K.; Lovergine, F.P.; Lucas, R.M.; Nagendra, H.; Rocchini, D.; Tarantino, C.Mairota, P.; Cafarelli, B.; Didham, R.K.; Lovergine, F.P.; Lucas, R.M.; Nagendra, H.; Rocchini, D.; Tarantino, C

Object-based mapping of temperate marine habitats from multi-resolution remote sensing data

PhD ThesisHabitat maps are needed to inform marine spatial planning but current methods of field survey and data interpretation are time-consuming and subjective. Object-based image analysis (OBIA) and remote sensing could deliver objective, cost-effective solutions informed by ecological knowledge. OBIA enables development of automated workflows to segment imagery, creating ecologically meaningful objects which are then classified based on spectral or geometric properties, relationships to other objects and contextual data. Successfully applied to terrestrial and tropical marine habitats for over a decade, turbidity and lack of suitable remotely sensed data had limited OBIA’s use in temperate seas to date. This thesis evaluates the potential of OBIA and remote sensing to inform designation, management and monitoring of temperate Marine Protected Areas (MPAs) through four studies conducted in English North Sea MPAs. An initial study developed OBIA workflows to produce circalittoral habitat maps from acoustic data using sequential threshold-based and nearest neighbour classifications. These methods produced accurate substratum maps over large areas but could not reliably predict distribution of species communities from purely physical data under largely homogeneous environmental conditions. OBIA methods were then tested in an intertidal MPA with fine-scale habitat heterogeneity using high resolution imagery collected by unmanned aerial vehicle. Topographic models were created from the imagery using photogrammetry. Validation of these models through comparison with ground truth measurements showed high vertical accuracy and the ability to detect decimetre-scale features. The topographic and spectral layers were interpreted simultaneously using OBIA, producing habitat maps at two thematic scales. Classifier comparison showed that Random Forests Abstract ii outperformed the nearest neighbour approach, while a knowledge-based rule set produced accurate results but requires further research to improve reproducibility. The final study applied OBIA methods to aerial and LiDAR time-series, demonstrating that despite considerable variability in the data, pre- and post-classification change detection methods had sufficient accuracy to monitor deviation from a background level of natural environmental fluctuation. This thesis demonstrates the potential of OBIA and remote sensing for large-scale rapid assessment, detailed surveillance and change detection, providing insight to inform choice of classifier, sampling protocol and thematic scale which should aid wider adoption of these methods in temperate MPAs.Natural Environment Research Council and Natural Englan

Sustainable intensification of arable agriculture:The role of Earth Observation in quantifying the agricultural landscape

By 2050, global food production must increase by 70% to meet the demands of a growing population with shifting food consumption patterns. Sustainable intensification has been suggested as a possible mechanism to meet this demand without significant detrimental impact to the environment. Appropriate monitoring techniques are required to ensure that attempts to sustainably intensify arable agriculture are successful. Current assessments rely on datasets with limited spatial and temporal resolution and coverage such as field data and farm surveys. Earth Observation (EO) data overcome limitations of resolution and coverage, and have the potential to make a significant contribution to sustainable intensification assessments. Despite the variety of established EO-based methods to assess multiple indicators of agricultural intensity (e.g. yield) and environmental quality (e.g. vegetation and ecosystem health), to date no one has attempted to combine these methods to provide an assessment of sustainable intensification. The aim of this thesis, therefore, is to demonstrate the feasibility of using EO to assess the sustainability of agricultural intensification. This is achieved by constructing two novel EO-based indicators of agricultural intensity and environmental quality, namely wheat yield and farmland bird richness. By combining these indicators, a novel performance feature space is created that can be used to assess the relative performance of arable areas. This thesis demonstrates that integrating EO data with in situ data allows assessments of agricultural performance to be made across broad spatial scales unobtainable with field data alone. This feature space can provide an assessment of the relative performance of individual arable areas, providing valuable information to identify best management practices in different areas and inform future management and policy decisions. The demonstration of this agricultural performance assessment method represents an important first step in the creation of an operational EO-based monitoring system to assess sustainable intensification, ensuring we are able to meet future food demands in an environmentally sustainable way