Steven R. Schill

Assessing vulnerability: an integrated approach for mapping adaptive capacity, sensitivity, and exposure

Making decisions and efficiently allocating resources to reduce the vulnerability of coastal communities requires, among other things, an understanding of the factors that make a society vulnerable to climate and coastal hazards. One way of doing this is through the analysis of spatial data. We demonstrate how to apply GIS methods to spatially represent socioeconomic vulnerability in Grenada, a tropical small island developing state (SIDS) in the Eastern Caribbean. Our model combines spatial features representing variables of social sensitivity, community adaptive capacity, and community exposure to flooding in an integrated vulnerability index. We draw from the fields of climate change adaptation, disaster management, and poverty and development to select our variables enabling unique, cross sector, applications of our assessment. Mapping our results illustrates that vulnerability to flooding is not evenly distributed across the country and is not driven by the same factors in all areas of Grenada. This indicates a need for the implementation of different strategies in communities across Grenada to help effectively reduce vulnerability to climate and coastal hazards. The approach presented in this paper can be used to address national issues on climate change adaptation, disaster management, and poverty and development and more effectively utilize funds in order to reduce community vulnerability to natural hazards today and in the future.

No Reef Is an Island: Integrating Coral Reef Connectivity Data into the Design of Regional-Scale Marine Protected Area Networks

We integrated coral reef connectivity data for the Caribbean and Gulf of Mexico into a conservation decision-making framework for designing a regional scale marine protected area (MPA) network that provides insight into ecological and political contexts. We used an ocean circulation model and regional coral reef data to simulate eight spawning events from 2008–2011, applying a maximum 30-day pelagic larval duration and 20% mortality rate. Coral larval dispersal patterns were analyzed between coral reefs across jurisdictional marine zones to identify spatial relationships between larval sources and destinations within countries and territories across the region. We applied our results in Marxan, a conservation planning software tool, to identify a regional coral reef MPA network design that meets conservation goals, minimizes underlying threats, and maintains coral reef connectivity. Our results suggest that approximately 77% of coral reefs identified as having a high regional connectivity value are not included in the existing MPA network. This research is unique because we quantify and report coral larval connectivity data by marine ecoregions and Exclusive Economic Zones (EZZ) and use this information to identify gaps in the current Caribbean-wide MPA network by integrating asymmetric connectivity information in Marxan to design a regional MPA network that includes important reef network connections. The identification of important reef connectivity metrics guides the selection of priority conservation areas and supports resilience at the whole system level into the future.

Remote Sensing for Biodiversity

Remote sensing (RS)—taking images or other measurements of Earth from above—provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding trends, and also provides key input into assessments, international agreements, and conservation management. Historically, RS data have often been expensive and hard to use, but changes over the last decade have resulted in massive amounts of global data being available at no cost, as well as significant (if not yet complete) simplification of access and use. This chapter provides a baseline set of information about using RS for conservation applications in three realms: terrestrial, marine, and freshwater. After a brief overview of the mechanics of RS and how it can be applied, terrestrial systems are discussed, focusing first on ecosystems and then moving on to species and genes. Marine systems are discussed next in the context of habitat extent and condition and including key marine-specific challenges. This is followed by discussion of the special considerations of freshwater habitats such as rivers, focusing on freshwater ecosystems, species, and ecosystem services.

Temporal Modeling of Bidirectional Reflection Distribution Function (BRDF) in Coastal Vegetation

The bidirectional reflection distribution function (BRDF) is a theoretical concept that describes the relationship between a targets irradiance geometry and the viewing angle of the sensor relative to the target. The BRDF can significantly affect the radiometric quality of remotely sensed data, particularly in off-nadir views. This research used a NASA Sandmeier Field Goniometer (SFG) to collect hourly canopy spectral reflectance at 76 hemispherical angles at two study sites within the North Inlet-Winyah Bay National Estuarine Research Reserve during late winter (March 2000—low live biomass and high dead biomass) and late summer (October 2000—high live biomass and low dead biomass). The objective of this research was to compare and quantify the temporal differences of high spectral and angular resolution BRDF diurnal data for smooth cordgrass (Spartina alterniflora) communities. These data were collected to model and quantify BRDF canopy patterns as they relate to in situ biophysical measurements and phenological change. The hypothesis tested was that temporal changes in LAI, biomass, height, geometry, understory, and tide levels throughout the phenological cycle can be spectrally quantified to provide insight into BRDF research. These data were used to create graphic plots to provide a quantitative assessment of temporal BRDF patterns and biophysical characteristics. This research identified bands that are least impacted by the BRDF, recognized optimal Sun/sensor angles-of-view, and provided insight into radiometrically adjusting remotely sensed data to minimize BRDF effects. Once scientists understand the nature of BRDF in relation to phenological changes within the vegetation canopy, they can begin to apply models to improve the accuracy of information extracted from remotely sensed data.

Distribution of Mangrove Habitats of Grenada and the Grenadines

ABSTRACT Moore, G.E.; Gilmer, B.F., and Schill, S.R., 2015. Distribution of mangrove habitats of Grenada and the Grenadines. Mangroves of Grenada and the Grenadines represent significant habitat within the regional context of the Eastern Caribbean. Losses of mangroves through storms, development, and climate change have negative impacts on critical ecosystem services. Estimates of mangrove area exist in the literature but do not fully reflect current conditions, effects of disturbance, and results of recovery; they also do not differentiate these areas by community types. Advances in imagery and remote sensing approaches allow higher-resolution resource mapping. We used remote sensing, image interpretation, and field verification techniques to provide current estimates of the extent and distribution of mangroves. Our results provide the greatest areal total of mangroves to date. Despite loss of mangroves in the recent past, we accounted for approximately 15% more hectares than estimated in the 1990s and 28% more than predicted by hypothetical models for 2005. The discrepancies between prior and current mapped areas are likely due to differences in mapping precision and incomplete surveys that omitted the smaller Grenadine islands but also reflect actual increases in cover from natural recovery and recruitment following historic storm events. Basin mangroves represented the greatest area, while riverine and scrub contributed the least. Fringe mangroves were moderately abundant but were composed of small, isolated patches with high vulnerability to coastal storms and limited opportunity for inland retreat. Documenting the presence and distribution of mangroves, and specifically mangrove community types, will be of value to conservation, restoration, and management planning in light of predicted sea level rise and climate change effects.

Spatial planning for a green economy: National-level hydrologic ecosystem services priority areas for Gabon

Rapidly developing countries contain both the bulk of intact natural areas and biodiversity, and the greatest untapped natural resource stocks, placing them at the forefront of “green” economic development opportunities. However, most lack scientific tools to create development plans that account for biodiversity and ecosystem services, diminishing the real potential to be sustainable. Existing methods focus on biodiversity and carbon priority areas across large geographies (e.g., countries, states/provinces), leaving out essential services associated with water supplies, among others. These hydrologic ecosystem services (HES) are especially absent from methods applied at large geographies and in data-limited contexts. Here, we present a novel, spatially explicit, and relatively simple methodology to identify countrywide HES priority areas. We applied our methodology to the Gabonese Republic, a country undergoing a major economic transformation under a governmental commitment to balance conservation and development goals. We present the first national-scale maps of HES priority areas across Gabon for erosion control, nutrient retention, and groundwater recharge. Priority sub-watersheds covered 44% of the country’s extent. Only 3% of the country was identified as a priority area for all HES simultaneously, highlighting the need to conserve different areas for each different hydrologic service. While spatial tradeoffs occur amongst HES, we identified synergies with two other conservation values, given that 66% of HES priority areas intersect regions of above average area-weighted (by sub-watersheds) total forest carbon stocks and 38% intersect with terrestrial national parks. Considering implications for development, we identified HES priority areas overlapping current or proposed major roads, forestry concessions, and active mining concessions, highlighting the need for proactive planning for avoidance areas and compensatory offsets to mitigate potential conflicts. Collectively, our results provide insight into strategies to protect HES as part of Gabon’s development strategy, while providing a replicable methodology for application to new scales, geographies, and policy contexts.

A Systematic Framework for Spatial Conservation Planning and Ecological Priority Design: An Example from St. Lucia, Eastern Caribbean

Rare and endangered species attract attention everywhere; this is certainly true within the Western world. During any inventory work at the stations, questions about rare and endangered species come up quickly. It is a very popular topic and many individuals and organizations are interested in trying to save and study these species, or at least to claim doing so in public. It must be seen as a phenomenon why this topic ranks so high on the agenda for the public, in the commercial media, and with many conservationists and students? Perhaps rare species are indicative of how we as a society, perceive, interact with, and understand nature?

Identifying Riverine Sand and Gravel Deposits Using A High Resolution Day‐night Temperature Difference Map and Digitized Aerial Photography

Abstract Sand and gravel are important natural resources used in construction. Point bars in rivers often contain sand and gravel deposits that are identified through laborious and expensive field investigation. This research examined remote sensing‐assisted methods of discriminating between surficial sediment deposits of varying particle sizes (e.g. silt/clay, sand and gravel) based on a) the differences in their diurnal temperature properties, and b) daytime spectral reflectance. NASAs Airborne Terrestrial Applications Sensor (ATLAS) was used to obtain pre‐dawn and mid‐day 2.5 × 2.5 m spatial resolution data in the visible, near‐infrared, mid‐infrared, and thermal‐infrared regions of the electromagnetic spectrum. Natural color aerial photography were also collected. The pre‐dawn and mid‐day thermal infrared data were regressed with in situ temperature measurements to produce pre‐dawn and mid‐day temperature maps. These data were differenced to produce a day‐night temperature difference map. The temperature difference image was useful for discriminating between sand and gravel but not between different classes of gravel. Three bands of pre‐dawn thermal infrared data and the digitized aerial photography were classified independently. The classification of surface materials based on the pre‐dawn thermal infrared data was superior to the classification derived from the aerial photography based on Kappa analysis.