Relative density of finds for assessing similarity-based maps of orchid occurrence

Similarity-based mapping of the expected distribution of 10 orchid species was conducted in a study area covering 300 km² in south-eastern Estonia. The observation track and species finds were recorded during fieldwork. Absence locations were generated on the line of observation track. Both presence and absence sites having an in-between distance of at least 100 m were used as training data. Expected presence/absence of a species was calculated according to similarity between the predictable location and selected observations (examples) of presence and absence sites. For each species, the machine learning system identified the best predictive sets by selecting the most useful variables out of 136 map and remote sensing features. Similarity-based estimations were evaluated both by training fit and by independent verification data. Reliability of the predictive maps was expressed also by usefulness ratios—the densities of validation find sites (1) in the predicted presence area relative to the density of those in the predicted absence area, and (2) relative to the share of the observation track in the predicted presence area and in the predicted absence area. The predictive mapping was most efficient for Dactylorhiza incarnata, D. russowii, Epipactis palustris, and Goodyera repens. We conclude that the profound coverage of observations on any larger area is unrealistic and the reliability of similarity-based predictive maps depends on the representativity of existing records relative to the diversity of the study area. The investigation showed that the studied species are much more common in nature than the records in the national database indicate.     

The impact of coastal flooding on conservation areas: A study of the Clyde Estuary, Scotland

This study examines the impact of flooding on land of high conservation value located along part of the southern shoreline of the River Clyde Estuary in western Scotland. This paper hypothesizes that, over the next 50 years, the frequency and extent of coastal flooding will increase due to the gradual effect of global warming and the consequent rise in sea-level and increase in storminess. It is argued that because of the great cost of constructing new flood defence systems it will not be possible to protect all land areas to an equal extent from flooding. A means of ranking different land use will be necessary so that society can make a rational judgement concerning which sections of coastline will be worth protecting. This study provides a methodology that combines an objective ranking of conservation areas using non-economic indicators with a GIS model of flood potential, and permits accurate forecasts of flood losses to conservation areas of different ecological value. The conservation case study used in this paper proposes the use of an ecological weighting value based on five ecological variables each of 10 categories. Tables and maps identify the sites that have been highlighted as consisting of the most ‘valuable’ conservation sites. The methodology makes extensive use of geographical information systems (GIS) to model the predicted areas of flooding and to calculate conservation weighting values of the land areas.     

遥感与GIS在蝗虫生境研究中的应用进展

蝗虫生境是蝗虫赖以生活、生存的环境。利用遥感技术获取与蝗虫密切相关的各种生境因子,并结合GIS技术研究和阐明蝗虫的生境因子对东亚飞蝗的产卵、孵化、成虫、迁飞等生育周期的影响机理,是实现对蝗虫监测、预测预警的基础。文章首先分析了各种蝗虫生境因子对蝗虫发生的影响机理,认为这些生境因子对蝗灾发生的影响不是孤立地起作用的,仅靠单个生境因子进行蝗灾的预测是不全面的,而遥感和GIS技术方便的获取、管理和分析多种生境因子数据,在大尺度蝗灾发生监测和预警中起到不可替代的作用。通过对遥感与GIS在蝗虫的不同发育阶段（蝗卵发育阶段、蝗蝻发育阶段和成虫阶段）的应用及其进展的分析,认为对蝗虫不同生育阶段的遥感监测需采用不同的参数和技术才能达到更好的效果,最后提出了遥感与GIS在蝗虫生境监测方面的未来发展方向。     

Testing the Generality of Bird-Habitat Models

Bird-habitat models are frequently used as predictive modeling tools—for example, to predict how a species will respond to habitat modifications. We investigated the generality of the predictions from this type of model. Multivariate models were developed for Golden Eagle (Aquila chrysaetos), Raven (Corvus corax), and Buzzard (Buteo buteo) living in northwest Scotland. Data were obtained for all habitat and nest locations within an area of 2349 km². This assemblage of species is relatively static with respect to both occupancy and spatial positioning. The area was split into five geographic subregions: two on the mainland and three on the adjacent Island of Mull, which has one of United Kingdom's richest raptor fauna assemblages. Because data were collected for all nest locations and habitats, it was possible to build models that did not incorporate sampling error. A range of predictive models was developed using discriminant analysis and logistic regression. The models differed with respect to the geographical origin of the data used for model development. The predictive success of these models was then assessed by applying them to validation data. The models showed a wide range of predictive success, ranging from only 6% of nest sites correctly predicted to 100% correctly predicted. Model validation techniques were used to ensure that the models' predictions were not statistical artefacts. The variability in prediction success seemed to result from methodological and ecological processes, including the data recording scheme and interregional differences in nesting habitat. The results from this study suggest that conservation biologists must be very careful about making predictions from such studies because we may be working with systems that are inherently unpredictable.     

Should We Protect the Strong or the Weak? Risk,Resilience, and the Selection of Marine Protected Areas

Abstract: It is thought that recovery of marine habitats from uncontrollable disturbance may be faster in marine reserves than in unprotected habitats. But which marine habitats should be protected, those areas at greatest risk or those at least risk? We first defined this problem mathematically for 2 alternate conservation objectives. We then analytically solved this problem for both objectives and determined under which conditions each of the different protection strategies was optimal. If the conservation objective was to maximize the chance of having at least 1 healthy site, then the best strategy was protection of the site at lowest risk. On the other hand, if the goal was to maximize the expected number of healthy sites, the optimal strategy was more complex. If protected sites were likely to spend a significant amount of time in a degraded state, then it was best to protect low‐risk sites. Alternatively, if most areas were generally healthy then, counterintuitively, it was best to protect sites at higher risk. We applied these strategies to a situation of cyclone disturbance of coral reefs on Australia's Great Barrier Reef. With regard to the risk of cyclone disturbance, the optimal reef to protect differed dramatically, depending on the expected speed of reef recovery of both protected and unprotected reefs. An adequate consideration of risk is fundamental to all conservation actions and can indicate surprising routes to conservation success.     

Developing a saltmarsh monitoring methodology to meet multiple policy and management objectives in Scotland

To meet Scotland’s conservation and legislative requirements to monitor and set management objectives for saltmarsh habitat, a national survey was developed jointly funded by Scottish Natural Heritage and the Scottish Environment Protection Agency. This national survey focussed on developing a fine scale vegetation map of all Scottish saltmarshes over 3 ha, which was digitised using GIS software. A condition monitoring protocol was also developed to assess the health of key ecological parameters of the saltmarsh system. A total of 7,704 ha of coastal habitat was surveyed as part of the project, which included 5,840 ha of saltmarsh vegetation and 1,864 ha of associated vegetation. The condition monitoring protocol results show that targets relating to the presence of built structures and transition integrity are not achieved more frequently than others. Targets for stock grazing intensity; the maintenance of saltmarsh extent; and poaching damage are also not achieved frequently. Further research is required to accurately reflect the condition of pioneer saltmarsh.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.     

The distribution and habitat preference of coastally occurring minke whales (Balaenoptera acutorostrata) in the outer southern Moray Firth, northeast Scotland

The coastal waters of the Moray Firth in northeast Scotland (57o41’N 2o40’W) provide rich, inshore feeding grounds for minke whales (Balaenoptera acutorostrata) during the summer and autumnal months. In order to better understand the habitat selection, movements and feeding ecology of the animals utilising this North Sea region, distribution data from the southern coastline of the outer Moray Firth were subsequently examined with respect to the marine physiography of the area, specifically the environmental variables water depth, slope, aspect and sediment-type. A total of 305 minke whale encounters – collected from dedicated boat surveys conducted between May and October 2001 to 2006 inclusive – were used in the construction of a Geographic Information System (GIS) for the 860 square-km study site. The subsequent analysis revealed a strong spatial preference by whales in this location for water depths between 20 and 50 metres (mean 46.9 m, SD = 30.9), steep slopes (mean 75.7 degrees, SD = 8.9), a northerly-facing aspect and sandy-gravel sediment type. Kruskal-Wallis tests for variance confirmed that the distribution of B. acutorostrata was significantly different across each of these physiographic features examined (P < 0.05). In particular, water depth and sediment type were shown to be highly correlated with the frequency of whales observed (Spearman’s Rank Correlation P < 0.05 for depth and sediment respectively). From these results, we conclude that sea bottom characteristics may be used to predict the fine-scale distribution of minke whales on their feeding grounds; the physiographic features identified providing valuable proxies for inferring prey distributions in the absence of fisheries data. However, an appreciation of both abiotic and biotic factors (using a combination of GIS and remote sensing outputs) is clearly desirable for ecosystem-based management approaches for the coastal conservation of these whales. The application of GIS capacities to ecological studies based largely on field data of these marine mammals is highly recommended in the present study to cetologists, environmental modellers and conservation managers alike.     

Rapid Assessment of Risks to a Mobile Marine Mammal in an Ecosystem-Scale Marine Protected Area

Abstract:  Ecosystem-scale networks of marine protected areas (MPAs) are important conservation tools, but their effectiveness is difficult to quantify in a time frame appropriate to species conservation because of uncertainties in the data available. The dugong ( Dugong dugon ) is a mobile marine species that occurs in shallow inshore waters of an ecosystem-scale network of MPAs (the Great Barrier Reef World Heritage Area [GBRWHA]). We developed a rapid approach to assess risk to dugongs in the region and evaluate options to ameliorate that risk. We used expert opinion and a Delphi technique to identify and rank 5 human factors with the potential to adversely affect dugongs and their sea grass habitats: netting, indigenous hunting, trawling, vessel traffic, and poor-quality terrestrial runoff. We then quantified and compared the distribution of these factors with a spatially explicit model of dugong distribution. We estimated that approximately 96% of habitat of high conservation value for dugongs in the GBRWHA is at low risk from human activities. Using a sensitivity analysis, we found that to decrease risk, commercial netting or indigenous hunting had to be reduced in remote areas and the effects of vessel traffic, terrestrial runoff, and commercial netting had to be reduced in urban areas. This approach enabled us to compare and rank risks so as to identify the most severe risks and locate specific sites that require further management attention.     

The impact of coastal flooding on conservation areas: A study of the Clyde Estuary, Scotland

This study examines the impact of flooding on land of high conservation value located along part of the southern shoreline of the River Clyde Estuary in western Scotland. This paper hypothesizes that, over the next 50 years, the frequency and extent of coastal flooding will increase due to the gradual effect of global warming and the consequent rise in sea-level and increase in storminess. It is argued that because of the great cost of constructing new flood defence systems it will not be possible to protect all land areas to an equal extent from flooding. A means of ranking different land use will be necessary so that society can make a rational judgement concerning which sections of coastline will be worth protecting. This study provides a methodology that combines an objective ranking of conservation areas using non-economic indicators with a GIS model of flood potential, and permits accurate forecasts of flood losses to conservation areas of different ecological value. The conservation case study used in this paper proposes the use of an ecological weighting value based on five ecological variables each of 10 categories. Tables and maps identify the sites that have been highlighted as consisting of the most ‘valuable’ conservation sites. The methodology makes extensive use of geographical information systems (GIS) to model the predicted areas of flooding and to calculate conservation weighting values of the land areas.     

Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Assessment of herbaceous plant habitats in water-constrained environments: predicting indirect effects with fuzzy logic

Herbaceous plant production plays a key role in determining the function of rangeland ecosystems in the semi-arid and Mediterranean regions. Therefore, assessment of herbaceous plant habitats is important for understanding the ecosystem functioning in these regions and for applied purposes, such as range management and land evaluation. This paper presents a model to assess herbaceous plant habitats in a basaltic stony environment in a Mediterranean region. The model is based on geographic information systems (GIS), remote sensing and fuzzy logic, while four indirect variables, which represent major characteristics of herbaceous habitats, are modeled: rock cover fraction; wetness index (WI); soil depth; and slope orientation (aspect). A linear unmixing model was used to measure rock cover on a per pixel basis using a Landsat TM summer image. The wetness index and local aspect were determined from digital elevation data with 25 m × 25 m pixel resolution, while soil data were gathered in a field survey. The modeling approach adopted here is process-based and assumes that water availability plays a crucial role in determining herbaceous plant production in Mediterranean and semi-arid environments. The model rules are based on fuzzy logic and are written based on the hypothesized water requirements of the herbaceous vegetation. The results show that on a polygon basis there is positive agreement between the model proposed here and previous mapping of the herbaceous habitats carried out in the field using traditional methods. Intrapolygon tests show that the use of a continuous raster data model and fuzzy logic principles provide an added value to traditional mapping. Moreover, herbaceous biomass measurements at two time intervals—mid- and peak winter season—corresponded with the habitat assessment predictions achieved using a new scenario that is proposed in this research. This scenario suggests that rockiness increases herbaceous production on south-facing slopes, while in other slope aspects the rock cover has lower impact on herbaceous growth. Due to its simplicity, the model suggested here can be used by planners and managers, to adjust range activities over large areas. The process-based approach should allow adaptation of the model to other regions more effectively than models that were formulated on a purely empirical basis. The model could also be used to study the relationship between water availability and ecosystem productivity on a regional scale.     

Striking a Balance between Biodiversity Conservation and Socioeconomic Viability in the Design of Marine Protected Areas

Abstract: The establishment of marine protected areas is often viewed as a conflict between conservation and fishing. We considered consumptive and nonconsumptive interests of multiple stakeholders (i.e., fishers, scuba divers, conservationists, managers, scientists) in the systematic design of a network of marine protected areas along California's central coast in the context of the Marine Life Protection Act Initiative. With advice from managers, administrators, and scientists, a representative group of stakeholders defined biodiversity conservation and socioeconomic goals that accommodated social needs and conserved marine ecosystems, consistent with legal requirements. To satisfy biodiversity goals, we targeted 11 marine habitats across 5 depth zones, areas of high species diversity, and areas containing species of special status. We minimized adverse socioeconomic impacts by minimizing negative effects on fishers. We included fine‐scale fishing data from the recreational and commercial fishing sectors across 24 fisheries. Protected areas designed with consideration of commercial and recreational fisheries reduced potential impact to the fisheries approximately 21% more than protected areas designed without consideration of fishing effort and resulted in a small increase in the total area protected (approximately 3.4%). We incorporated confidential fishing data without revealing the identity of specific fisheries or individual fishing grounds. We sited a portion of the protected areas near land parks, marine laboratories, and scientific monitoring sites to address nonconsumptive socioeconomic goals. Our results show that a stakeholder‐driven design process can use systematic conservation‐planning methods to successfully produce options for network design that satisfy multiple conservation and socioeconomic objectives. Marine protected areas that incorporate multiple stakeholder interests without compromising biodiversity conservation goals are more likely to protect marine ecosystems.     

Prioritizing forest management actions to benefit marine habitats in data-poor regions

Land-use change is considered one of the greatest human threats to marine ecosystems globally. Given limited resources for conservation, we adapted and scaled up a spatially explicit, linked land–sea decision support tool using open access global geospatial data sets and software to inform the prioritization of future forest management interventions that can have the greatest benefit on marine conservation in Vanuatu. We leveraged and compared outputs from two global marine habitat maps to prioritize land areas for forest conservation and restoration that can maximize sediment retention, water quality, and healthy coastal/marine ecosystems. By combining the outputs obtained from both marine habitat maps, we incorporated elements unique to each and provided higher confidence in our prioritization results. Regardless of marine habitat data source, prioritized areas were mostly located in watersheds on the windward side of the large high islands, exposed to higher tropical rainfall, upstream from large sections of coral reef and seagrass habitats, and thus vulnerable to human-driven land use change. Forest protection and restoration in these areas will serve to maintain clean water and healthy, productive habitats through sediment retention, supporting the wellbeing of neighboring communities. The nationwide application of this linked land–sea tool can help managers prioritize watershed-based management actions based on quantitative synergies and trade-offs across terrestrial and marine ecosystems in data-poor regions. The framework developed here will guide the implementation of ridge-to-reef management across the Pacific region and beyond.     

Evaluation of Biogeographic Classification Schemes for Conservation Planning: Application to New Zealand's Coastal Marine Environment

Abstract:  For many regions worldwide, multiple and often contrasting biogeographic classifications exist that are derived from a variety of taxa and techniques. This presents a challenge for managers who must choose appropriate large-scale spatial frameworks for systematic conservation planning. We demonstrate how systematically collected community data can be used to evaluate existing biogeographic classifications, identify the most appropriate metric for biogeographic patterns seen in other taxonomic groups, and develop an independent biogeographic classification scheme for systematic conservation planning. We evaluated 6 existing biogeographic classifications for New Zealand's nearshore marine environment with community-similarity metrics derived from abundance and presence–absence data for macroalgae (107 species) and mobile macroinvertebrates (44 species). The concordance between community metrics and the previous classifications was high, as indicated by a high multivariate classification success (CS) (74.3–98.3%). Subsequently, we carried out an independent classification analysis on each community metric to identify biogeographic units within a hierarchical spatial framework. The classification derived from macroalgal presence–absence data achieved the highest CS and could be used as a mesoscale classification scheme in which 11 regional groupings (i.e., bioregions) (CS = 73.8–84.8%) are nested within northern and southern biogeographic provinces (CS = 90.3–98.7%). These techniques can be used in systematic conservation planning to inform the design of representative and comprehensive networks of marine protected areas through evaluation of the current coverage of marine reserves in each bioregion. Currently, 0.22% of the territorial sea around mainland New Zealand is protected in no-take marine protected areas in which 0–1.5% of each bioregion represented.     

Wildlife corridors under water: an approach to preserve marine biodiversity in heavily modified water bodies

Coastal areas commonly consist of an environment of intense economic uses and are thus exposed to conflicts between anthropogenic activities and biodiversity. While several approaches of nature protection have been applied to the terrestrial domain, aquatic biotopes frequently still lack a good ecological state as required by EU policies (WFD and MSFD). For numerous years, the underwater world has been considered as one sphere and was neglected in the development of distinctive concepts of conservation for its variety of biotopes. This paper’s objective is the enhancement of ecological connectivity within the study area through the design of benthic wildlife corridors and a consequent sublittoral biotope network. A step-by-step approach is presented for the optimization of ecological potential in heavily modified coastal water bodies, using Kiel Fjord (Western Baltic Sea) as a case study. The procedure for the development of wildlife corridors includes defining and mapping of existing biotope types, the identification of key species for each biotope type and delineating their mobility range, the reconstruction of near-natural / pre-industrial conditions and deriving the protection priorities by comparing past with current / modified conditions. By harmonizing these scientific insights with the local land use of human society, proposals for biotope restoration and improvements can be made. In Kiel Fjord, compensation measures, obligatory for human interventions, such as construction work in the marine environment in this case, have been implemented and present an opportunity to enhance the connectivity of biotopes, thus creating wildlife corridors for their inhabitants. The composition of benthic wildlife corridors, forming a sublittoral biotope network in accordance with the present anthropogenic uses, holds potential for implementation in comparably altered coastal water bodies and integration into national and international frameworks, in anticipation of its functionality.     

ReefBahia, an integrated GIS approach for coral reef conservation in Bahia, Brazil

Coral reefs around the world are facing serious threats. These fragile ecosystems are in need for conservation. The coastal state of Bahia hosts the most extensive and richest area of coral reefs in the South Atlantic Ocean. Assessment, planning and management of coral reef ecosystems are particularly challenging tasks. This work shows how the creation of a GIS improves the process of management, monitoring and conservation of the Bahian reef environments The initial data input started by the vectorization of 1) bathymetric data from the Bureau of Hydrography and Navigation (DHN), 2) shoreline and mangrove areas from Landsat 7 ETM + images, 3) near surface reefs from Quickbird images, and 4) coastal and marine protected areas of federal, state and local administrations. Geological, physical, biological and social information was then included in order to create a suitable marine GIS for conservation aims. The data includes information on sediment granulometry and transport patterns, rocky substrate outcrops, sea surface temperature, wave direction, rain precipitation, major contributing river discharge, artisanal fishery, benthic cover and bleaching data. ReefBahia GIS has provided essential information for a better understanding of coral reefs of the state of Bahia geological and ecological characteristics such as mapping, representation, connectivity and biodiversity of coral reefs, geological facies, Quaternary sedimentation, numeric modeling of wave refraction and monitoring of bleaching events.     

Effects of seascape connectivity on reserve performance along exposed coastlines

Seascape connectivity (landscape connectivity in the sea) can modify reserve performance in low-energy marine ecosystems (e.g., coral reefs, mangroves, and seagrass), but it is not clear whether similar spatial linkages also shape reserve effectiveness on high-energy, exposed coastlines. We used the surf zones of ocean beaches in eastern Australia as a model system to test how seascape connectivity and reserve attributes combine to shape conservation outcomes. Spatial patterns in fish assemblages were measured using baited remote underwater video stations in 12 marine reserves and 15 fished beaches across 2000 km of exposed coastline. Reserve performance was shaped by both the characteristics of reserves and the spatial properties of the coastal seascapes in which reserves were embedded. Number of fish species and abundance of harvested fishes were highest in surf-zone reserves that encompassed >1.5 km of the surf zone; were located < 100 m to rocky headlands; and included pocket beaches in a heterogeneous seascape. Conservation outcomes for exposed coastlines may, therefore, be enhanced by prioritizing sufficiently large areas of seascapes that are strongly linked to abutting complementary habitats. Our findings have broader implications for coastal conservation planning. Empirical data to describe how the ecological features of high-energy shorelines influence conservation outcomes are lacking, and we suggest that seascape connectivity may have similar ecological effects on reserve performance on both sheltered and exposed coastlines.     

Refining Biodiversity Conservation Priorities

Abstract:  Although there is widespread agreement about conservation priorities at large scales (i.e., biodiversity hotspots), their boundaries remain too coarse for setting practical conservation goals. Refining hotspot conservation means identifying specific locations (individual habitat patches) of realistic size and scale for managers to protect and politicians to support. Because hotspots have lost most of their original habitat, species endemic to them rely on what remains. The issue now becomes identifying where this habitat is and these species are. We accomplished this by using straightforward remote sensing and GIS techniques, identifying specific locations in Brazil's Atlantic Forest hotspot important for bird conservation. Our method requires a regional map of current forest cover, so we explored six popular products for mapping and quantifying forest: MODIS continuous fields and a MODIS land cover (preclassified products), AVHRR, SPOT VGT, MODIS (satellite images), and a GeoCover Landsat thematic mapper mosaic (jpg). We compared subsets of these forest covers against a forest map based on a Landsat enhanced thematic mapper. The SPOT VGT forest cover predicted forest area and location well, so we combined it with elevation data to refine coarse distribution maps for forest endemic birds. Stacking these species distribution maps enabled identification of the subregion richest in threatened birds—the lowland forests of Rio de Janeiro State. We highlighted eight priority fragments, focusing on one with finer resolved imagery for detailed study. This method allows prioritization of areas for conservation from a region >1 million km² to forest fragments of tens of square kilometers. To set priorities for biodiversity conservation, coarse biological information is sufficient. Hence, our method is attractive for tropical and biologically rich locations, where species location information is sparse.