Community dynamics of insular biotas in space and time

The various features determining species distributions remain enigmatic in ecology. This thesis deals with the spatial and temporal dynamics of land birds on the islands of the Dahlak archipelago, the Red Sea, and of mammals, birds and reptiles among the forest fragments of the archipelago-like east African coastal forest. The bird species richness on the islands of the Dahlak archipelago depended on area, isolation and extent of habitat. Similarly, species richness of the east African forest fragments was related to area, habitat diversity and isolation but the importance of each factor varied among taxa as well as among generalists and specialists. For example, area influenced species richness of most categories except specialist mammals and reptiles, habitat diversity was more important for forest specialists than generalists, and isolation was important only for birds. In both study areas, similarity in bird species composition decreased with increasing distances among isolates suggesting that dispersal from source pools and among isolates facilitate re-colonization. The nested community structure, i.e. species composition of species−poor communities are a subset of species−rich communities, of birds in the Dahlak archipelago depended on area and the distribution of a few habitats. Similarities in community patterns and cooccurrence patterns, at both community and species levels, were mainly related to habitat preferences and corresponding distributions of habitats as well as inter-island distances. Also, the distributional patterns suggest that predator-prey interactions can be a determinant of the spatial distribution of, at least, the prey. There was no evidence of competitive exclusion. The nested structure on the islands of the Dahlak archipelago remained fairly stable over a period of 35 years even in this arid region. The turnover dynamics were broadly predictable from the nested pattern but not always consistent with other expectations from nested community structure. Taken together my results show that mechanisms on varying spatial and temporal scales act on species distributions, and that the influence may vary among taxa mainly depending on dispersal ability. In the case of conservation, comprehensive strategies accounting for these variations are needed

The role of climate and plant functional trade-offs in shaping global biome and biodiversity patterns

Aim: Two of the oldest observations in plant geography are the increase in plant diversity from the poles towards the tropics and the global geographic distribution of vegetation physiognomy (biomes). The objective of this paper is to use a process-based vegetation model to evaluate the relationship between modelled and observed global patterns of plant diversity and the geographic distribution of biomes.Location: The global terrestrial biosphere.Methods: We implemented and tested a novel vegetation model aimed at identifying strategies that enable plants to grow and reproduce within particular climatic conditions across the globe. Our model simulates plant survival according to the fundamental ecophysiological processes of water uptake, photosynthesis, reproduction and phenology. We evaluated the survival of an ensemble of 10,000 plant growth strategies across the range of global climatic conditions. For the simulated regional plant assemblages we quantified functional richness, functional diversity and functional identity.Results: A strong relationship was found (correlation coefficient of 0.75) between the modelled and the observed plant diversity. Our approach demonstrates that plant functional dissimilarity increases and then saturates with increasing plant diversity. Six of the major Earth biomes were reproduced by clustering grid cells according to their functional identity (mean functional traits of a regional plant assemblage). These biome clusters were in fair agreement with two other global vegetation schemes: a satellite image classification and a biogeography model (kappa statistics around 0.4).Main conclusions: Our model reproduces the observed global patterns of plant diversity and vegetation physiognomy from the number and identity of simulated plant growth strategies. These plant growth strategies emerge from the first principles of climatic constraints and plant functional trade-offs. Our study makes important contributions to furthering the understanding of how climate affects patterns of plant diversity and vegetation physiognomy from a process-based rather than a phenomenological perspective

Mapping the broad habitats of the Burren using satellite imagery

Teagasc acknowledges the support of the Research Stimulus Fund of the Department of Agriculture and Food, funded by the Irish Government under the National Development Plan 2000 – 2006.End of project reportThis project has successfully used satellite imagery to survey and map the extent and spatial distribution of broad habitat types within the Burren, and we have represented this information on a digitised habitat map. this information on a digitised habitat map. This map is the first to show the distribution of the broad habitats of the Burren and will be an important tool in aiding future decisions as to how the habitats of the Burren should be managed to the benefit of both the farmer and the environment. The map provides the first estimate of the area of the Burren affected by scrub encroachment – this being one of the most significant threats to the EU priority habitats in the region. On a particularly challenging area with a high diversity and complexity of habitats, remote sensing appears to offer a very effective and cost-efficient alternative to broad-scale habitat mapping on a field-by-field basis. The use of high-resolution imagery and ground-truthing should be adopted to complete a detailed national survey of habitats and land use in Ireland. This would support more effective implementation of both the Agriculture sector’s obligations under the Habitats Directive, and agri-environmental schemes with wildlife objectives. The outputs provided by such mapping approaches could inform the targeting of agri-environmental objectives, and increase the efficiency of detecting areas of high conservation value for monitoring by more conventional methods. The detailed land use descriptions offered by such imagery are also of high relevance to modelling approaches and risk assessment for implementation of land use policies such as the Water Framework Directive and Nitrates Directive.Department of Agriculture, Food and the Marin

Identifying and Forecasting Potential Biophysical Risk Areas within a Tropical Mangrove Ecosystem Using Multi-Sensor Data

Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities

Shallow-water benthic habitats of St. John, U.S. Virgin Islands

Coral reef ecosystems of the Virgin Islands Coral Reef National Monument, Virgin Islands National Park and the surrounding waters of St. John, U.S. Virgin Islands are a precious natural resource worthy of special protection and conservation. The mosaic of habitats including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important ecosystem services to the community of St. John, such as fishing, tourism and shoreline protection. However, coral reef ecosystems throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy the natural heritage of these marine habitats. Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding St. John to support more effective management and conservation of ocean resources within the National Park system. This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new maps to a previous NOAA effort. Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at each level of the scheme. The ability to apply any component of this scheme was dependent on being able to identify and delineate a given feature in remotely sensed imagery

The role of remote sensing in the development of SMART indicators for ecosystem services assessment

Human beings benefit from a wide range of goods and services from the natural environment that are collectively known as ecosystem services. However, rapid natural habitat loss, overexploitation and climate change is causing accelerating losses of populations and species, with largely unknown consequences on ecosystem functioning and the sustainable provision of ecosystem services. It is crucial, therefore, to develop a suite of indicators of the health and status of ecosystems, to monitor and quantify services delivery and to facilitate policy responses to stop and reverse negative trends. An effective framework to facilitate the development of suitable indicators is by using the SMART approach, which defines five criteria that could be applied to set monitoring and management goals, which are Specific, Measurable, Achievable, Realistic and Time-sensitive. Remote sensing provides a useful data source that can monitor ecosystems over multiple spatial and temporal scales. Although the development and application of landscape indicators (vegetation indices, for example) derived from remote sensing data are comparatively advanced, it is acknowledged that a number of organisms and ecosystem processes are not detectable by remote sensing. This paper explores several approaches to overcome this limitation, by examining the strong affinity of species with dominant habitat structures and through the coupling of remote sensing and ecosystem process models using examples drawn from a number of important ecosystems

Evaluation of the causes of error in the MCD45 burned-area product for the savannas of northern South America [Evaluación de las causas de error en el producto de área quemada MCD45 para las sabanas del norte de Suramérica]

Forest fires contribute to deforestation and have been considered a significant source of CO2 emissions. There are global maps that estimate the area affected by a fire using the reflectance variation of the surface. In this study, we evaluated the reliability and the causes of error of the MCD45 Burned Area Product, by applying the confusion matrix method to the Orinoco River Basin. This basin is located in the northern zone of South America, and consists mainly of savanna ecosystems. For the evaluation, we used as reference data five pairs of Landsat images, covering 165,000 km2. The Burned Area Product estimated a burned area of 7,576.43 km2, which is lower than the area of 12,100.16 km2 found with Landsat images, leading to an overall underestimation. The causes of error are associated to the spatial resolution of the map, and to some structures of the algorithm that generates the map