Tool For Conservation Planning Research Articles

Predicting resilience of migratory birds to environmental change.

The pace and scale of environmental change represent major challenges to many organisms. Animals that move long distances, such as migratory birds, are especially vulnerable to change since they need chains of intact habitat along their migratory routes. Estimating the resilience of such species to environmental changes assists in targeting conservation efforts. We developed a migration modeling framework to predict past (1960s), present (2010s), and future (2060s) optimal migration strategies across five shorebird species (Scolopacidae) within the East Asian-Australasian Flyway, which has seen major habitat deterioration and loss over the last century, and compared these predictions to empirical tracks from the present. Our model captured the migration strategies of the five species and identified the changes in migrations needed to respond to habitat deterioration and climate change. Notably, the larger species, with single or few major stopover sites, need to establish new migration routes and strategies, while smaller species can buffer habitat loss by redistributing their stopover areas to novel or less-used sites. Comparing model predictions with empirical tracks also indicates that larger species with the stronger need for adaptations continue to migrate closer to the optimal routes of the past, before habitat deterioration accelerated. Our study not only quantifies the vulnerability of species in the face of global change but also explicitly reveals the extent of adaptations required to sustain their migrations. This modeling framework provides a tool for conservation planning that can accommodate the future needs of migratory species.

Forest Community Spatial Modeling Using Machine Learning and Remote Sensing Data

This study examines the application of unsupervised classification techniques in the mapping of forest vegetation, aiming to align vegetation cover with the Braun-Blanquet classification system through remote sensing. By leveraging Landsat 8 and 9 satellite imagery and advanced clustering algorithms, specifically the Weka X-Means, this research addresses the challenge of minimizing researcher subjectivity in vegetation mapping. The methodology incorporates a two-step clustering approach to accurately classify forest communities, utilizing a comprehensive set of vegetation indices to distinguish between different types of forest ecosystems. The validation of the classification model relied on a detailed analysis of over 17,000 relevés from the “Flora” database, ensuring a high degree of accuracy in matching satellite-derived vegetation classes with field observations. The study’s findings reveal the successful identification of 44 forest community types that was aggregated into seven classes of Braun-Blanquet classification system, demonstrating the efficacy of unsupervised classification in generating reliable vegetation maps. This work not only contributes to the advancement of remote sensing applications in ecological research, but also provides a valuable tool for natural resource management and conservation planning. The integration of unsupervised classification with the Braun-Blanquet system presents a novel approach to vegetation mapping, offering insights into ecological characteristics, and can be good starter point for sequestration potential of forest communities’ assessment in the Republic of Tatarstan.

Unveiling Sri Lanka’s Wilderness: GIS-Based Modelling of Wilderness Attributes

This research presents the first detailed national wilderness mapping project conducted in Sri Lanka, aiming to identify and assess the spatial distribution of wilderness areas in the country. The study utilises a GIS-based Wilderness Quality Index (WQI), incorporating three main wilderness attributes: remoteness from public roads, absence of modern human interventions, and naturalness of land cover. The resulting wilderness quality map reveals several areas of high wilderness quality distributed throughout the country, with exceptions in the highly populated western region, where roads and built structures have significant impact. The research highlights the spatial correlation between the distribution of wilderness areas and protected areas, indicating that nearly all wilderness areas in Sri Lanka fall within the boundaries of existing protected areas. However, core wilderness areas outside existing protected areas, termed de facto wilderness areas, constitute a significant portion (19.7%) of total wilderness, raising concerns about their conservation status. The study emphasises the need for further evaluation to assess the ecological and landscape value of these areas and suggests new protected area boundaries. The wilderness quality map developed here provides policymakers with a valuable tool for future conservation planning, enabling informed decision making to preserve and protect Sri Lanka’s diverse and unique wilderness areas.

Wintering raptor species distribution in a semiarid Mediterranean region: the relevance of lowlands and open habitats as stopover sites

As land-use cover types affect wintering birds’ strategies, studying their habitat suitability for species conservation is relevant. Predictive spatial models are considered excellent tools for conservation planning and improving our understanding of species distribution. Here we build models to predict the spatial distribution of raptor species that overwinter in SE Spain. We modelled the wintering raptor species distribution based on the presence-only data obtained between 2017 and 2019 and analysed their habitat preferences based on elevation and land-use cover variables. Our results show that altitude and distance to the coastline are the most important environmental factors to affect most species’ habitat suitability. Habitat type-related factors are other important predictors, and raptors subject of this study prefer lowlands and areas close to the coastline for overwintering by selecting open habitats, which include wetlands and irrigated and rainfed crops. This study highlights the importance of the habitat heterogeneity generated by wetlands and herbaceous crops within a low-altitude range as the optimal environment for wintering raptors. Such information should be considered for raptor conservation planning in human-altered landscapes.

Lack of local genetic representation in one of the regions with the highest bird species richness, the Peruvian Amazonia.

Peru ranks among the three countries with the highest bird species diversity globally and a majority of those species are found in the Peruvian Amazon. However, birds in this area are currently facing serious anthropogenic threats. Genetic and genomic methods are becoming important tools for avian biodiversity monitoring and conservation planning. Comprehensive molecular libraries that are publicly available are key to the effective deployment of these tools. We analyze the information gaps for four molecular markers in the most important genetic sequence databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, for bird species of the Peruvian Amazonia. We found that 64% of Peruvian Amazonian bird species have gene sequences for COI, 59.5% have CYTB sequences, 16.4% have 12S sequences, and only 0.6% have 18S sequences. However, these numbers decrease drastically to 4.3% for COI sequences when we only consider specimens sampled in Peru. Our data also showed that 43.8% of Peruvian Amazonian endemic species (n = 32) are missing sequences of any screened marker uploaded to GenBank or BOLD. Our results will encourage and guide efforts of the scientific community to complete reference libraries for Peruvian avian species that will be useful for future DNA-based monitoring projects that include birds.

Using aerial LiDAR to assess regional availability of potential habitat for a conservation dependent forest bird

Remotely-sensed data can inform conservation efforts that target forest wildlife, however, few spatial data products are able to quantify fine-scale aspects of structural variation within forests. Increased availability of Light Detection and Ranging (LiDAR) datasets that cover broad spatial extents and ownership types (e.g., entire states) provide useful information regarding canopy and understory structure within forested landscapes. The fusion of LiDAR data with field-based species surveys can advance our understanding of species-habitat relationships and improve the effectiveness of conservation programs to recover habitat-limited species. The Golden-winged Warbler (Vermivora chrysoptera) is a forest-dependent songbird that nests in structurally-complex young forest across eastern North America. As with many early-successional obligates, this species has been declining for decades due, in part, to the steady loss of young forest/shrubland nesting habitat. Although conservation programs have begun restoring Golden-winged Warbler habitat, these efforts are currently limited by the inability to identify existing habitat across large spatial extents and diverse ownership patterns. Recent availability of state-wide LiDAR data for Pennsylvania provides an opportunity to overcome this limitation. From 2019 to 20, we surveyed for Golden-winged Warblers and structural vegetation at 837 sites across six forest blocks in eastern Pennsylvania. We combined these data with LiDAR derived forest structural metrics to develop statistical models to predict patterns of occupancy. Golden-winged Warbler occupancy probability was explained by models containing several LiDAR-derived structural metrics (e.g., percentage of first returns between 1 and 5 m in height, structural complexity, etc.). Moreover, models fit with LiDAR-derived covariates predicted occupancy much better than those using only field-measured vegetation covariates (ΔAICc = 53.27). Mapped predictions of Golden-winged Warbler occupancy revealed potential habitat (especially regenerating timber harvests) on both private and public lands. These results demonstrate the efficacy of LiDAR for modeling forest bird habitat associations, and how such data sources can provide a valuable tool for conservation planning.

Waterfowl distribution and productivity in the Prairie Pothole Region of Canada: tools for conservation planning

AbstractSpecies conservation requires an understanding of the factors and interactions affecting species distribution and behavior, habitat availability and use, and corresponding vital rates at multiple temporal and spatial scales. Opportunities to investigate these relationships across broad geographic regions are rare. We combined long‐term waterfowl population surveys, and studies of habitat use and breeding success, to develop models that identify and incorporate these interactions for upland‐nesting waterfowl in the Prairie Pothole Region (PPR) of Canada. Specifically, we used data from the annual Waterfowl Breeding Population and Habitat Survey (1961–2009) at the survey segment level and associated habitat covariates to model and map the long‐term average duck density across the Canadian PPR. We analyzed nest location and fate data from approximately 25,000 duck nests found during 3 multi‐year nesting studies (1994–2011) to model factors associated with nest survival and habitat selection through the nesting season for the 5 most common upland nesting duck species: mallard (Anas platyrhynchos), gadwall (Mareca strepera), blue‐winged teal (Spatula discors), northern shoveler (Spatula clypeata), and northern pintail (Anas acuta). Duck density was highly variable across the Canadian PPR, reflecting positive responses to local wetland area and count, and amounts of cropland and grassland, a regional positive response to latitude, and a negative response to local amounts of tree cover. Nest survival was affected by temporal and spatial variables at multiple scales. Specifically, nest survival demonstrated interactive effects among species, nest initiation date, and nesting cover type and was influenced by relative annual wetness, population density, and surrounding landscape composition at landscape scales, and broad geographic gradients (east‐west and north‐south). Likewise, species‐specific probability of nest habitat selection was influenced by timing of nest initiation, population density, relative annual wetness, herbaceous cover, and tree cover in the surrounding landscape, and location within the Canadian PPR. We combined these models, with estimates of breeding effort (nesting, renesting, and nest attempts) from existing literature, in a stochastic conservation planning model that estimates nest distribution and success given spatiotemporal variation in duck density, habitat availability, and influential covariates. We demonstrate the use of this model by examining various conservation planning scenarios. These models allow estimation of local, landscape, and regional influence of conservation investments and other landscape changes on the productivity of breeding duck populations across the PPR of Canada. These models lay the groundwork for the incorporation of conservation delivery costs for full return‐on‐investment analyses and scenario analyses of climate, habitat, and land use change in regional and continental population models.

Expanding protected areas in a Neotropical hotspot

ABSTRACT The region of central Veracruz is considered a biodiversity hotspot due to its high species richness and environmental heterogeneity, but only 2% of this region is currently protected. This study aimed to assess the current protected area system’s effectiveness and to identify priority conservation areas for expanding the existing protected area system. We used the distribution models of 1186 species from three kingdoms (Animalia, Plantae, and Fungi) together with ZONATION software, a conservation planning tool, to determine areas that could help expand the current network of protected areas. We applied three different parametrizations (including only species, using the boundary quality penalty, and using corridor connectivity). We found that protecting an additional 15% of the area would increase, between 16.2% and 19.3%, the protection of the distribution area of all species. We propose that the regions with a consensus of the three parametrizations should be declared as new protected areas to expand 374 km2 to the 216 km2 already protected. Doing so would double the protected surface in central Veracruz. The priority areas identified in this study have more species richness, carbon stock values, natural vegetation cover, and less human impact index than the existing protected areas. If our identified priority areas are declared protected, we could expect a future recovery of endangered species populations for Veracruz. The proposed new protected areas are planned and designed as corridors connecting currently isolated protected areas to promote biodiversity protection.

Identifying multiple wildlife species-crop interactions using network analysis

Managing crop damage by wildlife is a complex challenge in agrarian-wildlife landscapes. Losses to farmers and their negative attitude towards crop-raiding wildlife, compromise wildlife conservation and farmer-wildlife coexistence. Priority crop types, crop-raiding wildlife and socio-ecological factors are highly integrated. Here we use cross-sectional network analysis as a conservation planning tool to simultaneously identify the croptypes used by crop-raiding wildlife, and evaluate the importance of these crop-wildlife interactions relative to the socio-ecological factors that affect these interactions. The most vulnerable crops were maize, millet and fruit trees, while the most problematic crop-raiding wildlife were African elephant, bushpig, hippo, warthog and red-billed quelea. Crop damage declined with countermeasure effectiveness, farm size, and distance from river to farm, but increased with richness of attractive crops. Undamaged crops included cash crops, such as chili, onion, ginger, lemon grass and garlic. Applying network analysis to different crops and damage scenarios enables identification of the most important and influential crops, crop-raiding wildlife and socio-ecological factors needed to develop effective crop protection strategies.

Biocultural aspects of species extinctions

AbstractPredicting whether a species is likely to go extinct (or not) is one of the fundamental objectives of conservation biology, and extinction risk classifications have become an essential tool for conservation policy, planning and research. This sort of prediction is feasible because the extinction processes follow a familiar pattern of population decline, range collapse and fragmentation, and, finally, extirpation of sub-populations through a combination of genetic, demographic and environmental stochasticity. Though less well understood and rarely quantified, the way in which science and society respond to population decline, extirpation and species extinction can also have a profound influence, either negative or positive, on whether a species goes extinct. For example, species that are highly sought after by collectors and hobbyists can become more desirable and valuable as they become rarer, leading to increased demand and greater incentives for illegal trade – known as the anthropogenic Allee effect. Conversely, species that are strongly linked to cultural identity are more likely to benefit from sustainable management, high public support for conservation actions and fund-raising, and, by extension, may be partially safeguarded from extinction. More generally, human responses to impending extinctions are extremely complex, are highly dependent on cultural and socioeconomic context, and have typically been far less studied than the ecological and genetic aspects of extinction. Here, we identify and discuss biocultural aspects of extinction and outline how recent advances in our ability to measure and monitor cultural trends with big data are, despite their intrinsic limitations and biases, providing new opportunities for incorporating biocultural factors into extinction risk assessment.

Checklist of the Birds of the Gaza Strip—Palestine

Bird fauna checklists are important tools in ecology, biology, and conservation planning for scientists, stakeholders, and decision-makers. Despite its small area, the Gaza Strip (365 km2) has a relatively large variety of resident and migratory bird fauna. Therefore, the current study aimed to provide an updated checklist of all bird fauna living in or inhabiting the Gaza Strip. Direct field observations using binoculars, continuous visits to zoos, pet stores and biology museums, discussion with bird hunters, follow-up of news and social networking sites, review of scientific publications and photography were the main tools to satisfy the purpose of the study. At least 250 bird species collected from different sources occur in the Gaza Strip and are included in the checklist. This list will not be static, but is inevitably subject to additions and changes in the face of times. The current 250 bird species of the Gaza Strip represent 45.4% of the 551 species of birds living in Palestine. The bird species were found to belong to 21 orders and 61 families. The Passeriformes (passerines) represented the largest order with 96 species of birds (38.4%), followed by the Charadriiformes 54 (21.6%), the Accipitriformes 18 (7.2%), Anseriformes 17 (6.8%) and Pelecaniformes 14 (5.6%), while the other orders represented the remaining percentage (20.4%). With regard to families, the Scolopacidae represented the largest family with 22 species of birds (8.8%), followed by the Anatidae and Accipitridae 17 for each (6.8%), the Muscicapidae 16 (6.4%) and Chariidridae and Fringillidae 11 for each (4.4%), while the other families represented the remaining percentage (62.4%). According to the IUCN regional threat categories, 226 species (90.4%) were Least Concern (LC), 12 (4.8%) were Near Threatened (NT), 6 (2.4%) were Vulnerable (VU), 4 (1.6%) were Endangered (EN) and 2 (0.8%) were Critically Endangered (CR). In conclusion, the study recommends a sustainable control of bird hunting and trafficking in addition to building prestigious centers and museums for studying and documenting birds in the Gaza Strip.

Anthropogenic risk assessment of riverine habitat using geospatial modelling tools for conservation and restoration planning: a case study from a tropical river Pranhita, India.

The riverine ecosystem provides multiple benefits to human community and contributes to the sustainable development of the ecoregion. The growing dependency on these ecosystems has largely contributed to aggravating the ecological risks, habitat degradation, and loss of ecosystem services. The present study evaluates the ecological risk emanating from nine anthropogenic stressors including river use, hydro-morphology, catchment pollution, and biological stressor on river Pranhita in Godavari Basin of Peninsular India using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Habitat Risk Assessment model. The primary field survey, remote sensing, and secondary data-assisted spatial modelling results revealed low ecological risk (R = 0.65 of 3) in river Pranhita due to anthropogenic activities. Sediment loading, the inflow of nitrogen, and habitat fragmentation were the major stressors with relatively higher risk score (> 1); influence on a sizeable portion of riverine habitat (29-75% of the total area under high-risk zone) indicates the mounting threat from catchment activities. The low-risk value observed in protected river reaches as compared to unprotected areas is likely to be influenced by the abundant presence of intact riparian vegetation which mitigate the catchment stressors and minimal anthropogenic activity within protected areas. This study demonstrates the application of InVEST HRA model for ecological risk assessment of riverine ecosystems and fish assemblages along with their input data generation framework. This has the potential for prioritization of sensitive habitats based on computed ecological risk and stressor identification based on their exposure and consequences for developing appropriate mitigation measures. This model is spatially explicit and accommodates user-defined criteria for ecosystem-level assessment at a regional and national scale to facilitate the resource managers and policymakers for conservation and restoration planning and implementation of targeted management measures for sustainable development.

Living on the edge: The use of fruit‐feeding butterflies to evaluate edge effect on subtropical assemblages

AbstractThis study evaluated how the edge effect influences the structuration of fruit‐feeding butterfly assemblages in swamp forest fragments of the subtropical Atlantic Forest, Southern Brazil. Sampling was carried out twice in 10 fragments using baited traps placed in sampling units both at the forest edge and 50 m within the forest interior, with the habitats being defined by a set of environmental variables. Richness and abundance were higher for edge habitats with an effect of temperature depending on humidity and luminosity. The subfamily/tribe composition of fruit‐feeding butterflies was segregated between edge and interior and was predicted by wind speed and the interaction between humidity and luminosity. Fifty meters within the forest interior is not sufficient to cause homogenization of butterfly composition between the edge and interior of swamp forest fragments, indicating distinct assemblages in each habitat. The interior harboured forest‐loving butterfly groups while the edge harboured generalist sun‐loving and common butterflies associated with disturbed areas, suggesting resistance to the effects of habitat fragmentation. We highlight the importance of using fruit‐feeding butterfly groups, instead of species, to evaluate edge effects. We also suggest that a heterogeneous matrix with native habitats and distinct semi‐natural land‐use systems be maintained to manage subtropical areas by increasing connectivity within the landscape. Considering the impacts that the Atlantic Forest suffers, increased knowledge of modifications caused at small and regional scales is crucial for the maintenance of ecological processes and represents a tool for conservation planning and environmental agendas.

Grizzly bear habitat selection across the Northern Continental Divide Ecosystem

Understanding habitat selection is challenging but key for species of conservation concern, including grizzly bears (Ursus arctos). Here we demonstrate an approach for understanding and predicting habitat use over multiple stages that test hypotheses of animal behavior, use newly gained knowledge to mechanistically simulate individual movements, translate results to predictive habitat maps, and test their predictive power across a large spatiotemporal scale. Grizzly bears in the Northern Continental Divide Ecosystem of northwest Montana served as our study system. Mechanistically modeling grizzly bear movements demonstrated that grizzly bears have highly individualistic spatial behaviors. Some individuals avoided whereas others preferred areas of vegetation green-up, terrain ruggedness, forest edge, riparian areas, building densities, and secure habitat. Such individualism supported the need for an individual-based modeling approach to understand and predict grizzly bear behavior. External validation using >375,000 GPS locations for 261 individuals over nearly 2 decades demonstrated mean Spearman rank scores of >0.90 across seasons and years, and overall scores of 1.0. The top 5 classes of our predictive habitat maps contained 73.5 % of female fixes and 83.6 % of male fixes, and the top class (comprising 10 % of mapped area) contained 25.6 % and 41.7 % of female and male fixes, respectively. Results of this research provide tools for conservation planning and serve as the basis for future grizzly bear research within our study system and beyond. Our multi-stage approach for understanding and predicting habitat use has high utility for conservation of myriad threatened species around the globe.

Spatial density pattern of Himalayan Ibex (Capra sibirica) in Pakistan

Mountain ungulates perform a key role in maintaining the balance of ecosystems as they are the primary consumers of vegetation and prey for large predators. The mountain ranges of northern Pakistan are home to six species of mountain ungulates, and the Himalayan ibex (Capra sibirica), hereafter ibex, is the most abundant among them. This study was conducted in three administrative regions of northern Pakistan, viz. Gilgit-Baltistan (GB), Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP), to generate a range-wide density pattern map of ibex. A double-observer survey was conducted in 25 study sites during 2018–2021 across the ibex distribution range, covering an area of about 35,307 km 2 , by walking transects totaling 1647 km. Within the ibex range where the survey was not conducted due to financial and logistical constraints, we obtained species population information from local wildlife departments’ most recent annual survey data. The aim was to generate a density map for the entire ibex range. Using the BBRecapture package in program R, we estimated an ibex population of 7639 (95 % CI) with a mean density of 0.21/km 2 in the surveyed area. Combining with the secondary data from un-surveyed areas, the total population estimate for the country came to 10,242 ibex. The largest population densities were observed in four valleys (Shimshal, Gulkin-Hussaini, Khyber, and Khunjerab) of the Karakoram-Pamir range, followed by the Hindu Kush range (Chitral Wildlife Division [WD]). The central and eastern parts of the Karakoram range had moderate to low densities, while the Himalayan range (e.g., Astore Valley) supported a small population. The mean herd size was 15 individuals (range: 5–41), and the average detection probability of observers A and B was 0.69 and 0.48, respectively. The average male and young ratios per 100 females were estimated to be 75 and 81, respectively. The range-wide density map developed during the study provided an evidence for the impact of trophy hunting programs and an objective tool for range-wide conservation planning of the species.

FRESF model: An ArcGIS toolbox for rapid assessment of the supply, demand, and flow of flood regulation ecosystem services

• An ArcGIS toolbox and FRESF model can measures flood related indices. • It is a practical tool for ecosystem services conservation planning. • The study provided here show the usability and credibility of proposed toolbox. River floods are globally the most damaging and costliest natural disasters. The functions of nonstructural flood mitigation measures (e.g., water retention by vegetation and soil) provide critical regulation ecosystem services to human beings. For example, the Sponge Cities are national watershed management projects in China to increase the nonstructural flood regulation services, aiming to enable the urban ecosystem to absorb, infiltrate, and retain storm water to mitigate pluvial flooding. Decision-makers need to acquire critical areas for the supply, demand, and flow of flood regulation ecosystem services, which would affect the delivery of services and the distribution of any benefits among stakeholders. However, relatively few empirical studies present this information. One reason is the lack of appropriate methods and tools for a rapid assessment of flood regulation ecosystem services that do not require substantial resources or rely heavily on hydrological process data. This article presents the Flood Regulation Ecosystem Service Flow (FRESF) model to address this gap. FRESF is an open-access and open-source ArcGIS script toolbox for an integrated evaluation of flood regulation ecosystem services' supply, demand, and flow. Based on a land surface process model and a generic framework quantifying ecosystem services flow, FRESF provides a rapid and serviceable assessment framework for the relevant ecosystem services at a relatively low cost and effort. The validation results suggest that the outputs are moderately consistent with the actual flood conditions, compared with the flood disaster of the Yangtze River in 2020. Its open codes and flexible inputs imply that ecologists, planners, decision-makers, and developers involved in ecosystem services would have the opportunity to test and apply the FRESF model in several contexts and even contribute further improvements.

Use of high-resolution ground conductivity measurements for denitrifying conservation practice placement.

Accurate field-scale maps of soil properties including features such as texture, soil organic matter (SOM) content, and hydraulic conductivity are essential for proper placement of conservation practices that utilize anoxic soil environments for denitrification. However, in many cases, soil maps inaccurately represent subsoil properties and can mislead managers about where to install new practices. Non-invasive methods of subsoil property analysis including electromagnetic induction techniques are a potentially efficient method for improving existing field-scale soil maps. In this study, we quantified the accuracy of existing soil maps in an agricultural field in north-central Iowa. Of 60 soil cores collected and reclassified, 19 were identified as taxadjunct at the soil series level primarily due to hydrologic indicators and soil particle size. We assessed the correlation among physical and chemical soil properties measured in-lab and geophysical responses measured in-field. We identified significant correlation of SOM and sand to electrical conductivity for individual core and mean soil series data. From this analysis, we developed a conservation practice suitability map and evaluated the potential for field-scale geophysical investigations to serve as a new tool for agricultural conservation planning and placement of site-specific denitrifying conservation practices. Study results suggest that incorporating a geophysical conductivity investigation into conservation planning may improve understanding of critical soil properties beyond those ascertained with limited soil borings.

Benefits of collaboration between indigenous fishery management and data-driven spatial planning approaches: the case of a Polynesian traditional design (rāhui)

Traditional fishery management schemes have gained increasing recognition worldwide. It can be explained by a better compliance to ancient cultural practices, still rooted in present-day coastal communities despite globalization and modern livelihoods. This revival is widespread and welcome by policy makers, scientists, and the communities themselves. However, current environmental and socio-economic contexts are often not conform to ancient-time situations. Baselines are different. Effective adjustments of traditional practices may be advocated. Re-establishment of traditional schemes ‘as such’ warrants further investigations and modern quantitative assessment and management approaches can help. A demonstration is provided here for a rural Polynesian island that faces declining marine resources. Recently, local fishers discussed the implementation of a traditional system (called rāhui) to preserve the island lagoon resources, based on the rotational closure of an arbitrary 50% of each lagoon subdivision. Upon the fishers’ request who questioned a traditional scheme that has not been applied for decades and seeked some scientific approval, we used systematic conservation planning (SCP) tools to explore potential optimisation pathways. All quantitative conservation objectives being equal, SCP suggested reserve sizes and opportunity costs on average 7 and 5 times lower than the traditional design. Traditional management federates communities and is strongly encouraged, but fishers are now aware that effective alternative designs are possible. A hybrid design mixing traditional practices and data-based optimizations is advocated. Similar findings and recommendations can be expected in other regions.

Measuring conservation priorities: A simple tool for conservation planning in poorly sampled areas

Global conservation resources are limited and as a result donors and funders are forced to make difficult decisions as to which areas are in most urgent need of support. Biodiversity can play a key role in these choices, but many other factors must be considered. In order to assist with such decisions we present a simple index that can be employed by non-scientists in poorly sampled countries, using the reptile fauna of 55 protected and two unprotected areas of Paraguay as a case study. This index can be applied at multiple taxonomic and geographic levels to minimize biases generated by uneven sampling. We offer words of caution on unsupported claims of high biodiversity, and highlight how the use of inaccurate terminology, although well-intentioned, can be detrimental to national or local conservation efforts. Results show that the top two areas of conservation priority in Paraguay are currently unprotected, and current investment of resources is ineffective and insufficient for long term protection of Paraguay’s globally and nationally threatened reptiles.

Exploiting HBIM for Historical Mud Architecture: The Huaca Arco Iris in Chan Chan (Peru)

The construction technique of raw earth, which has always been in use in most of the world, has left large monuments or architectural complexes to cultural heritage that need special attention due to the notable vulnerability of the material. A convenient way to deal this threat, besides physical intervention, is by using an information system, such as HBIM (Heritage Building Information Modeling), as a tool for damage assessment and conservation planning. This paper reports on its application in an archaeological setting, in particular, on the Huaca Arco Iris, a religious building of the old city of Chan Chan (Peru), the largest monumental complex in mud on the American continent. The study is part of the bilateral international project between the Consiglio Nazionale delle Ricerche (CNR) and the Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica (CONCYTEC) in the use of HBIM for the prediction of possible natural or anthropogenic damages to buildings in raw mud. Exploiting the data coming from the direct and indirect analyses, a dedicated ontology is built to guide the management of these data within the information system. The creation of an HBIM system for the archaeological domain, based on the trinomial data–information–knowledge, is presented and validated. Following this approach, a customizable HBIM has been created with the 3D model of the spatial entities of the Huaca. As a result, the semantic relationship of an external wall, taken as the benchmark test of our experiment, with the contained bas-relief and the conservation cover is tested.