Priority Areas For Conservation Action Research Articles

Reassessment of the risks of climate change for terrestrial ecosystems

Forecasting the risks of climate change for species and ecosystems is necessary for developing targeted conservation strategies. Previous risk assessments mapped the exposure of the global land surface to changes in climate. However, this procedure is unlikely to robustly identify priority areas for conservation actions because nonlinear physiological responses and colimitation processes ensure that ecological changes will not map perfectly to the forecast climatic changes. Here, we combine ecophysiological growth models of 135,153 vascular plant species and plant growth-form information to transform ambient and future climatologies into phytoclimates, which describe the ability of climates to support the plant growth forms that characterize terrestrial ecosystems. We forecast that 33% to 68% of the global land surface will experience a significant change in phytoclimate by 2070 under representative concentration pathways RCP 2.6 and RCP 8.5, respectively. Phytoclimates without present-day analogue are forecast to emerge on 0.3–2.2% of the land surface and 0.1–1.3% of currently realized phytoclimates are forecast to disappear. Notably, the geographic pattern of change, disappearance and novelty of phytoclimates differs markedly from the pattern of analogous trends in climates detected by previous studies, thereby defining new priorities for conservation actions and highlighting the limits of using untransformed climate change exposure indices in ecological risk assessments. Our findings suggest that a profound transformation of the biosphere is underway and emphasize the need for a timely adaptation of biodiversity management practices.

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa

BackgroundSpatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be accounted for during the prioritisation process. We quantified the sensitivity of an SCP application (using software Zonation) to possible sources of uncertainty in data-poor situations, including the use of different surrogate options; correction for sampling bias; how to integrate connectivity; the choice of species distribution modelling (SDM) algorithm; how cells are removed from the landscape; and two methods of assigning weights to species (red-list status or prediction uncertainty). Further, we evaluated the effectiveness of the Egyptian protected areas for conservation, and spatially allocated the top priority sites for further on-the-ground evaluation as potential areas for protected areas expansion.ResultsFocal taxon (butterflies, reptiles, and mammals), sampling bias, connectivity and the choice of SDM algorithm were the most sensitive parameters; collectively these reflect data quality issues. In contrast, cell removal rule and species weights contributed much less to overall variability. Using currently available species data, we found the current effectiveness of Egypt’s protected areas for conserving fauna was low.ConclusionsFor SCP to be useful, there is a lower limit on data quality, requiring data-poor countries to improve sampling strategies and data quality to obtain unbiased data for as many taxa as possible. Since our sensitivity analysis may not generalise, conservation planners should use sensitivity analyses more routinely, particularly relying on more than one combination of SDM algorithm and surrogate group, consider correction for sampling bias, and compare the spatial patterns of predicted priority sites using a variety of settings. The sensitivity of SCP to connectivity parameters means that the responses of each species to habitat loss are important knowledge gaps.

Diversity and richness of avian community in Ekonde and Owala dams, Osun State, Nigeria

Birds have been shown to be an effective means of identifying priority areas for conservation action and mitigation measures. A field survey of birds at Ekonde and Owala dams in Osun State, Nigeria was conducted between March and June 2018 to determine the species diversity, abundance and feeding guilds. Data were collected using line transect method. The birds sighted during the survey were categorized based on their species, migratory/ non-migratory status, and feeding guild. Mean bird density within the two dams was determined and compared using t-test, and species diversity indices were analyzed using PAST software. A total of 2,152 birds from 67 species (33 families and 12 orders) were recorded where Ekonde dam had 1,286 birds (59.76%) and Owala dam had 866 (40.24%). In Ekonde dam, Vanellus spinosus was the most abundant species (n = 72, 8.31%), while at Owala dam, Oriolus nigripennis was the most abundant (n = 204, 15.86%). Bird density was apparently higher at Ekonde dam (51.44 birds/km2) than Owala dam (30.95 birds/km2), yet there was no significant difference (t value=1.679; p= 0.097). At Ekonde dam, Black-winged oriole had the highest density (8.16 birds/km2) while at Owala dam Spur-winged lapwing had the highest density (72 birds/km2). Shannon diversity index and evenness were higher at Ekonde dam (3.702 and 0.862) than at Owala dam (3.102 and 0.654). The birds were categorized into 10 and 8 feeding guilds in Owala and Ekonde dam respectively. Most reported species were insectivores (27, 33%) and carnivores (15, 19%). It can be suggested that as two dams have high avian richness, these can be sites for avian conservation and avitourism if properly managed. It is therefore recommended that strategy for avian conservation be incorporated into the dam management program for sustainability of the ecosystem. Keywords: Avian conservation, avitourism, bird density, feeding guilds.

Conservation gaps and priorities in the Tropical Andes biodiversity hotspot: Implications for the expansion of protected areas

The Tropical Andes (TA) contain some of the most important and threatened areas for biodiversity conservation on earth. Despite the proportion of protected areas (PAs) that currently cover the TA, it is unknown if these areas are adequately protecting the biodiversity throughout the region and where the expansion of PAs is most needed to preserve biodiversity in the future. Here, we examine the conservation status of 1743 vertebrate species endemic to the TA (including mammals, birds, amphibians and reptiles), for which conservation actions should be prioritized within the region itself. Using species' geographical range maps, refined by their known elevational and habitat requirements, we carry out a gap analysis to examine to what degree endemic vertebrate species in the TA are represented by PAs. Then, using the irreplaceability-vulnerability framework, we localize first and second priority areas for conservation action, where important ecological features are subjected to severe anthropogenic disturbance. Our results show that 72% of all species and 90% of all threatened species are insufficiently covered by PAs. Furthermore, 73% of the first priority sites and 84% of the second priority sites are not covered by current PAs. These areas are predominantly located in the surroundings of major population centers in Ecuador and Colombia. To prevent species from extinction in the near future, actions to conserve their remaining habitat in prioritized areas are urgently required.

Spatial characteristics of species distributions as drivers in conservation prioritization

Abstract Spatial prioritization, based on the biogeographical identification of priority areas for conservation actions, is an important aspect of conservation planning. Although the influence of factors such as costs, threats or use of surrogates on the resulting priorities has been studied extensively, relatively little is known about how the spatial characteristics of species distributions drive the spatial pattern of priorities in multi‐species conservation plans. Using datasets from Australia and Finland, we explore how excluding or including a given species changes spatial priorities in a multi‐species prioritization. We develop three metrics to quantify changes in priorities, and explore how these changes depend on the total number of species used in the prioritization, the spatial characteristics of the given species distribution, and how species share their space with other species used in the prioritization. We randomly selected 12 set of 10 species from each dataset, and explore the influence of each of these species in prioritizations done for a total of 10, 20, 50 or 100 species. We show that spatial priorities become increasingly stable as the number of species is increased, and that the stability of highest and lowest priority areas behave differently. When less than 50 species were used in a prioritization, intermediately rare species that occupy mostly species‐poor habitats tend to have the greatest influence on priorities, whereas very rare and common species that co‐occur with many other species tend to have a small influence. Our results present a systematic method to explore the stability of spatial priorities to changes in the species pool used for a conservation plan. Although the analysed two datasets differed in data type, location, scale and species composition, they both showed how using a small number of species leads to unstable spatial solutions, where the choice to include or exclude an individual species can strongly influence the conservation outcome. Our results also show that conservation planners should carefully assess the use of spatial prioritizations for identifying least important areas (e.g. for development) as these can be particularly unstable when the prioritization is based on a small number of species.

Synergistic effects of climate and land-use change on representation of African bats in priority conservation areas

Bats are considered important bioindicators and deliver key ecosystem services to humans. However, it is not clear how the individual and combined effects of climate change and land-use change will affect their conservation in the future. We used a spatial conservation prioritization framework to determine future shifts in the priority areas for the conservation of 169 bat species under projected climate and land-use change scenarios across Africa. Specifically, we modelled species distribution models under four different climate change scenarios at the 2050 horizon. We used land-use change scenarios within the spatial conservation prioritization framework to assess habitat quality in areas where bats may shift their distributions. Overall, bats’ representation within already existing protected areas in Africa was low (∼5% of their suitable habitat in protected areas which cover ∼7% of Africa). Accounting for future land-use change resulted in the largest shift in spatial priority areas for conservation actions, and species representation within priority areas for conservation actions decreased by ∼9%. A large proportion of spatial conservation priorities will shift from forested areas with little disturbance under present conditions to agricultural areas in the future. Planning land use to reduce impacts on bats in priority areas outside protected areas where bats will be shifting their ranges in the future is crucial to enhance their conservation and maintain the important ecosystem services they provide to humans.

Modelling the spatial distribution of species-rich farmland to identify priority areas for conservation actions

Spatial targeting of conservation actions is indispensable to protect and maintain farmland biodiversity and associated ecosystem services. To implement region-specific conservation actions, information on the spatial distribution of farmland biodiversity and its major drivers is a prerequisite. Here, we model the spatial distribution of species-rich farmland (defined by a minimum number of indicator plant species) and landscape elements (e.g. hedgerows, ditches, patches of woodland or scrub) at the national level by combining field-based survey data from a biological monitoring programme with agri-environmental variables. Adopting factor analysis and mixed effect models, we show that the percentage cover of species-rich farmland and landscape elements can be predicted by a combination of factors describing the intensity of arable farming, topography, low-input grassland farming, landscape structure and the intensity of livestock farming. Our results demonstrate that the relative importance of these factors differed between species-rich farmland and landscape elements. The share of species-rich farmland was highest in upland and structurally complex grassland-dominated regions where extensive livestock production is practised; whereas landscape elements were most likely to occur within flat regions where edge density tends to be high.In a policy context, our generated maps contribute to identifying priority regions for conservation actions. It is proposed that in regions with high coverage of species-rich farmland priority should be given to sustaining low-input grassland farming by keeping farmers in business and preventing farmland abandonment. We conclude that this modelling approach could be adapted for application in other European countries to facilitate spatial targeting of conservation actions.

Modelling semi-natural habitat area on lowland farms in western Ireland

A significant policy objective is the need for protection of biodiversity not just within designated Natura 2000 sites, but also in areas that occur outside of these sites. However there is a lack of information on existing semi-natural habitat cover on EU farms, making it difficult to assess whether targets for halting the loss of agricultural biodiversity are being met. To achieve these targets, reliable yet easy-to-use methods are needed for accurately identifying priority areas for conservation actions and monitoring biodiversity on a large spatial scale. Remote sensing, farmland statistics and species data have been used in some EU countries to create maps to estimate the extent of semi-natural habitat cover but these are acknowledged as being too broad scale. In this study, we examined a method of fine-scale prediction of the spatial coverage of semi-natural habitats in lowland farms. A generalized additive model (GAM) was used to investigate the relationships between landscape and farm management variables and the lowland farmland habitat biodiversity on 32 farms outside of conservation designations, in a region of western Ireland. Semi-natural habitat cover on lowland farms could be predicted with a model using stocking density, soil diversity and river and stream length. It is proposed that this model could be used to predict the coverage of semi-natural habitats on farms in other regions of Ireland with similar land-use and landscape. A similar modelling approach could be adapted for application in other regions of Ireland and across Europe with different landscapes to predict semi-natural habitat coverage.

Conservation Priorities for the Peruvian Yellow-Tailed Woolly Monkey (Oreonax flavicauda): A GIS Risk Assessment and Gap Analysis

An inductive GIS (Geographical Information System) process was used to create a realistic Habitat Suitability Model (HSM) for the current distributional range of the Peruvian yellow-tailed woolly monkey (Oreonax flavicauda) to aid current conservation initiatives and to help set future conservation priorities for the species. In combination with this, we produced an ecological risk assessment model of the study region to assist in site selection for priority areas for conservation actions, which included the expansion of the existing protected area system and the creation of new reserves in areas forming natural biological corridors in the northeastern Peruvian departments of Amazonas and San Martin. This study incorporates information regarding the threat of hunting and other anthropogenic pressures on the species into the site selection process. Oreonax flavicauda, currently on the IUCN Red List of Threatened Species as Critically Endangered, was once thought to be extinct. Since its rediscovery in 1974, however, there has been little research on this species due to its small population size, restricted distribution, and the difficulty of access to its mountainous habitat. A gap analysis showed that the current protected area network was inadequate to conserve the yellow-tailed woolly monkey's current suitable habitat. This finding underlines the urgency of upgrading the protected area network as well as implementing other conservation initiatives. The selection of sites suitable for the creation of new protected areas was based on habitat composition, altitudinal and geographical limits, and proximity to human influences, using an inductive process of extracting information from locations where O. flavicauda is known to occur, from existing demographic information on human populations, and by qualitative judgments. We recommend urgent action to protect this species before population numbers decrease further.

Finding threatened forest areas in the central volcanic mountain range conservation area in Costa Rica

The degree at which tropical forests are exposed to human pressure is spatially dependent. Population density, proximity to roads, terrain slope, logging activities and land distribution projects are well known factors inducing deforestation and forest degradation in Latin America. Using expert knowledge to weight these threat factors and a Geographical Information System for spatial modeling, a multi-criteria analysis procedure is presented, that allows stratifying a study region in categories of deforestation threat. The procedure was implemented in the Central Volcanic Mountain Range Conservation Area (CVMRCA) in Costa Rica with the purpose of finding areas with a combination of physical and socioeconomic characteristics that is particularly predisposing to a high probability of deforestation. To validate the map, the CVMRCA was stratified in categories of deforestation risk, and the result was superposed to historical deforestation data of the period 1986-1996. The good correlation between risk category and historical deforestation (r = 0.91, p < 0.001) indicates that the map can be used as a decision support tool for defining priority areas for conservation action.

Assessment of the decapod crustacean diversity in the Guayana Shield region aiming at conservation decisions

The current state of knowledge of freshwater decapod crustacean diversity of the Guayana Shield Region is briefly assessed, based upon information gathered from the scientific literature as well as unpublished data from academic theses, technical reports, and carcinological collections. The decapod fauna of the region is presently known to include 64 species and subspecies within six families and 17 genera. Diversity by countries, basins, and rivers is listed, comments on endemic, rare or threatened species are made, and information about relevant taxonomic literature is presented. Seven priority areas for conservation actions concerning crustacean decapods are suggested and related to the 25 priority areas defined by the Fishes and Freshwater Working Group at the Guayana Shield Conservation Priority Setting Workshop, held at Paramaribo (Suriname) in April 2002.

Identifying priority areas for conservation action in agricultural landscapes

Farming for food, fibre and other products for human consumption is a dominant land-use throughout the world. Rural landscapes are also critical to the conservation of flora and fauna, and the maintenance of ecological processes on which all of life depends. In Australia, excessive clearing of native vegetation in the most productive agricultural landscapes has had profound environmental and social consequences. Restoration of these landscapes is an enormous challenge that offers the opportunity to shape the future of Australia, environmentally, socially and economically. In this paper we address the issue of identifying priority areas for conservation in agricultural landscapes. The spatial location of conservation actions in rural landscapes is important because it affects the degree of representation of the biota, the level of protection for rare and threatened species, the adequacy of habitats for species and communities and their future viability, the maintenance of ecological processes, and the integrity of habitats. However, because most land in agricultural regions is privately owned, effective implementation of restoration goals in preferred locations requires understanding of social processes, recognition of pragmatic issues in land management and financial commitment by the wider Australian society. We briefly review the strengths and limitations of some current approaches to determining priority locations for conservation action, including the use of general principles, species-based approaches, quantitative approaches for assessing representativeness, and "bottom-up" approaches based on landholder action. There is no single ?best? solution: the most effective approach or combination of approaches depends on the objectives for restoration and the circumstances in the area where restoration will occur. An important consideration is the quality of the data available for the area, particularly detailed vegetation maps and knowledge of the status and habitat requirements of species that occur there. We summarize five stages that form a logical sequence in restoration programmes and highlight some of the issues at each stage. As the outcomes of the present continent-wide experiment in restoration cannot be fully evaluated for many decades, it is prudent that a range of alternatives are trialed and monitored for their effectiveness and success.

Taxic richness patterns and conservation evaluation of Madagascan tiger beetles (Coleoptera: Cicindelidae)

Distributional ranges of 17 genera and 172 species of Malagasy tiger beetles (Coleoptera, Cicindelidae) have been compiled to determine patterns of species richness and endemism. These patterns reveal large sampling gaps, and potential priority areas for conservation action. Northern and south-western parts of the island are richer in genera, whereas eastern and especially northern parts of the rainforest show higher species richness, due to extensive radiations within the genera Pogonostoma and Physodeutera. A set of 23 areas are identified in this study as priority foci for tiger beetle conservation, and six general regions are bioinventory priorities.

Using higher-taxon richness as a surrogate for species richness: II. Local applications

Recent analyses confirm that urgent attempts to catalogue the distribution of biological diversity may be facilitated by focusing at the level of genera or families rather than species. However, questions remain over the application of higher-taxon surveys to identify networks of priority areas for conservation action. Is the close spatial match between species and higher-taxon richness at global and regional scales re-iterated when sites are locally distributed? How much money is saved by the higher-taxon approach? And how does using genus or family information affect the efficiency with which spatial priorities for conservation are identified? We examined these issues using data on the diversity of woody plants in Sri Lankan forests. We found that at this local scale, the family and particularly generic richness of sites was closely linked to their species richness, independently of variation in site size. Moreover, fieldwork in an additional forest showed that targeting woody plant genera and families rather than species reduced survey costs by a minimum of 60% and 85% respectively. Most importantly, while using family data in site-selection algorithms led to the loss from reserve networks of around 7-10% of woody plant species, using genera rather than species had virtually no effect on the representation of species in priority sites. These results thus confirm that judicious use of the higher-taxon approach is indeed a valuable technique for improving the cost effectiveness of field surveys for local conservation planning in the tropics.