Accounting for functional connectivity in cross-realm conservation planning in a data poor context: The Cyprus case

In the past years, efforts have been made to include connectivity metrics in conservation planning in order to promote and enhance well-connected systems of protected areas. Connectivity is particularly important for species that rely on more than one realm during their daily or life cycle (multi-realm species). However, conservation plans for the protection of multi-realm species usually involve a single realm, excluding other realms from the prioritization process. Here, we demonstrate an example of cross-realm conservation planning application for the island of Cyprus by taking into account the terrestrial and marine realms and their interface (i.e. coast). Operating within a data-poor context, we use functional connectivity metrics to identify priority areas for the conservation of six multi-realm species, by setting conservation targets simultaneously for the terrestrial and marine realms. MARXAN decision-support tool was used for the identification of the priority areas.Four scenarios were developed to evaluate the impacts of including connectivity in the prioritization process and the effectiveness of the existing coastal/marine protected areas in the achievement of the conservation targets set for the species. All scenarios considered land and sea anthropogenic uses as surrogate costs to influence the prioritization process.Our findings show an increase in the area of the reserve network and, therefore, the cost, when connectivity is included, whilst reducing the total boundary length. Furthermore, the current reserve network fails to achieve conservation targets, particularly for the marine part, which has a substantially smaller protection coverage than the terrestrial part.We conclude that focus should be given in the expansion of the current coastal/marine reserve network following a cross-realm conservation approach. This approach is not only relevant for the conservation of multi-realm species, but also for islandscapes, in particular, where the interdependence between the hinterland and the coast is larger and therefore the magnitude of the impacts generated in one realm and affects the other.     

Identifying high value areas for conservation: Accounting for connections among terrestrial,freshwater, and marine habitats in a tropical island system

Functional ecosystems depend on biotic and abiotic connections among different environmental realms, including terrestrial, freshwater, and marine habitats. Accounting for such connections is increasingly recognized as critical for conservation of ecosystems, especially given growing understanding of the way in which anthropogenic landscape disturbances can degrade both freshwater and marine habitats. This need may be paramount in conservation planning for tropical island ecosystems, as habitats across realms are often in close proximity, and because endemic organisms utilize multiple habitats to complete life histories. In this study, we used Marxan analysis to develop conservation planning scenarios across the five largest islands of Hawaii, in one instance accounting for and in another excluding habitat connectivity between inland and coastal habitats. Native vegetation, perennial streams, and areas of biological significance along the coast were used as conservation targets in analysis. Cost, or the amount of effort required for conservation, was estimated using an index that integrated degree and intensity of anthropogenic landscape disturbances. Our results showed that when connectivity is accounted for among terrestrial, freshwater, and marine habitats, areas identified as having high conservation value are substantially different compared to results when connectivity across realms is not considered. We also showed that the trade-off of planning conservation across realms was minimal and that cross-realm planning had the unexpected benefit of selecting areas with less habitat degradation, suggesting less effort for conservation. Our cross-realm planning approach considers biophysical interactions and complexity within and across ecosystems, as well as anthropogenic factors that may influence habitats outside of their physical boundaries, and we recommend implementing similar approaches to achieve integrated conservation efforts.     

Incorporating zoning and socioeconomic costs in planning for bird conservation

New systematic conservation approaches have high potential in evaluation of different conservation scenarios and can be used as decision support tools for managers and planners with multiple goals. The present study focused on two major issues in conservation planning including socioeconomic costs and zoning procedure. The goal was to prioritize and identify representative areas for bird conservation, while minimizing the economic cost for the silvicultural sector and resolve conflicts with recreational activities. The study was conducted in forest areas of Golestan Province as part of Hyrcanian mixed forests, located along the southern coasts of the Caspian Sea and northern slopes of the Alborz Mountains, northern Iran. We used systematic conservation software Marxan with Zones to select candidate areas for conservation. Two types of conservation networks were defined, one with high and partial protection zones and the other with high protection zones only. We focused on four conservation scenarios varying in targets, costs, and multiple zones. The results showed that incorporation of socioeconomic costs significantly decreases the potential impacts on the silvicultural and recreational sectors without significant change in the area of protection zones. Furthermore, we found that design of multiple zone conservation areas facilitates evaluation of a wider range of conservation scenarios that can reduce potential socioeconomic impacts on other interests.     

Using prioritisation tools to strategically restore vegetation communities in fragmented agricultural landscapes

Restoring native habitats in heavily cleared and fragmented areas such as agricultural landscapes is important to maintain and increase remaining native floral and faunal communities. Identifying priority vegetation types for restoration – as well as the parcels of land where this restoration could take place at a landscape scale – may assist in strategically protecting these biodiversity assets. To prioritise the restoration of terrestrial habitats around an ecologically and culturally significant Ramsar‐listed wetland in South Australia, we used the spatial prioritisation tool Marxan. Originally designed for prioritising the protection of reserve areas, Marxan can also be used to identify parcels of land for restoration purposes. We tested how Marxan prioritised the restoration of four distinct vegetation types around the Coorong and Lower Lakes region of South Australia using the inverse of habitat remnancy as a cost and soil type and distance to ecologically significant bird species as a conservation feature. By prioritising restoration activities around certain landscape features, such as remnant areas, our results indicate that we would be able to strategically restore parcels of native habitat that would maximise biodiversity outcomes. This study highlights the need for robust input data, such as priority vegetation types and bird species associated with these habitats, to ensure informative modelling outputs. It also suggests that other measures, such as the cost of different land types, should be included in future restoration planning. Finally, we illustrate how prioritisation tools such as Marxan can be used by natural resource managers to restore areas within fragmented agricultural landscapes.     

Use of optimization algorithms to prioritize protected areas in Mazandaran Province of Iran

A systematic approach for prioritization of protected areas is the use of artificial intelligence. This approach employs computer algorithms based on an objective function to identify the best network of areas to be protected. Site selection algorithms are commonly used to identify areas of high conservation value. This study used three types of heuristic algorithms (simulated annealing, greedy, rarity) to prioritize areas for protection in Mazandaran Province of Iran using Marxan software. The goal was to select a conservation network with the smallest possible area in which maximum protection targets are achievable. The effects of spatial scale, algorithm, and zone compactness were also examined. We found that the existing network of protected areas is inadequate to achieve conservation targets. The algorithm results provided the best areas for supplementation of the current network. The simulated annealing algorithm provided the most plausible results for all scenarios. These results can be used to modify the existing boundaries of the protected areas network and introduce new sites for protection of plant and animal species.     

Minimum data requirements for designing a set of marine protected areas, using commonly available abiotic and biotic datasets

Marine protected areas (MPAs) can be an effective tool for marine biodiversity conservation, yet decision-makers usually have limited and biased datasets with which to make decisions about where to locate MPAs. Using commonly available abiotic and biotic datasets, I asked how many datasets are necessary to achieve robust patterns of conservation importance. I applied a decision support tool for marine protected area design in two regions of British Columbia, Canada, and sequentially excluded the datasets with the most limited geographic distribution. I found that the reserve selection method was robust to some missing datasets. The removal of up to 15 of the most geographically limited datasets did not significantly change the geographic patterns of the importance of areas for conservation. Indeed, including abiotic datasets plus at least 12 biotic datasets resulted in a spatial pattern similar to including all available biotic datasets. It was best to combine abiotic and biotic datasets in order to ensure habitats and species were represented. Patterns of clustering differed according to whether I used one set alone or both combined. Biotic datasets served as better surrogates for abiotic datasets than vice versa, and both represented more biodiversity features than randomly selected reserves. These results should provide encouragement to decision-makers engaged in MPA planning with limited spatial data.     

Conservation planning and viability: problems associated with identifying priority sites in Swaziland using species list data

Conservation planning assessments based on species atlas data are known to select planning units containing ecotones because these areas are relatively species‐rich. However, this richness is often dependent on the presence of adjoining core habitat, so populations within these ecotones might not be viable. This suggests that atlas data may also fail to distinguish between planning units that are highly transformed by agriculture or urbanization with those from neighbouring untransformed units. These highly transformed units could also be identified as priority sites, based solely on the presence of species that require adjoining habitat patches to persist. This potential problem was investigated using bird and mammal atlas data from Swaziland and a landcover map and found that: (i) there was no correlation between planning unit species richness and proportion of natural landcover for both taxa; (ii) the priority areas that were identified for both birds and mammals were no less transformed than if the units had been chosen at random and (iii) an approach that aimed to meet conservation targets and minimize transformation levels failed to identify more viable priority areas. This third result probably arose because 4.8% of the bird species and 22% of the mammal species were recorded in only one planning unit, reducing the opportunity to choose between units when aiming to represent each species. Therefore, it is suggested that using species lists to design protected area networks at a fine spatial scale may not conserve species effectively unless population viability data are explicitly included in the analysis.     

Prioritizing refugia for freshwater biodiversity conservation in highly seasonal ecosystems

Aim

Refugia play a key ecological role for the persistence of biodiversity in areas subject to natural or human disturbance. Temporary freshwater ecosystems regularly experience dry periods, which constrain the availability of suitable habitats. Current and future threats (e.g. water extraction and climate change) can exacerbate the negative effects of drying conditions. This could compromise the persistence of a large proportion of global freshwater biodiversity, so the identification and protection of refugia seems an urgent task.

Location

Northern Australia.

Methods

We demonstrate a new approach to identify and prioritize the selection of refugia and apply it to the conservation of freshwater fish biodiversity. We identified refugia using estimates of water residency time derived from satellite imagery and used a systematic approach to prioritize areas that provide all the fish species inhabiting the catchment with access to a minimum number of refugia while maximizing the length of stream potentially accessible for recolonization after the dry period. These priority refugia were locked into a broader systematic conservation plan with area‐based targets and direct connectivity. We accounted for current threats during the prioritization process to ensure degraded areas were avoided, thus maximizing the ecological role of priority refugia.

Results

Priority refugia were located in lowland reaches, where the incidence of threats was less prominent in our study area and headwaters in good condition. An additional set of 106 planning units (6500 km²) were required to represent 10% of each species' distribution in the broad conservation plan. A hierarchical management zoning scheme was applied to demonstrate how these key ecological features could be effectively protected from the major threats caused by aquatic invasive species and grazing.

Main conclusions

This new approach to identifying priority refugia and incorporating them into the conservation planning process in a systematic way would help enhance the resilience of freshwater biodiversity in temporary systems.

     

Improving bioregional frameworks for conservation by including mammal distributions

Large identifiable landscape units, such as ecoregions, are used to prioritize global and continental conservation efforts, particularly where biodiversity knowledge is inadequate. Setting biodiversity representation targets using coarse large‐scale biogeographic boundaries, can be inefficient and under‐representative. Even when using fine‐scale biodiversity data, representation deficiencies can occur through misalignment of target distributions with such prioritization frameworks. While this pattern has been recognized, quantitative approaches highlighting misalignments have been lacking, particularly for assemblages of mammal species. We tested the efficacy of Australia's bioregions as a spatial prioritization framework for representing mammal species, within protected areas, in New South Wales. We produced an approach based on mammal assemblages and assessed its performance in representing mammal distributions. Substantial spatial misalignment between New South Wales's bioregions and mammal assemblages was revealed, reflecting deficiencies in the representation of more than half of identified mammal assemblages. Using a systematic approach driven by fine‐scale mammalian data, we compared the efficacy of these two frameworks in securing mammalian representation within protected areas. Of the 61 species, 38 were better represented by the mammalian framework, with remaining species only marginally better represented when guided by bioregions. Overall, the rate at which mammal species were incorporated into the protected area network was higher (5.1% ± 0.6 sd) when guided by mammal assemblages. Guided by bioregions, systematic conservation planning of protected areas may be constrained in realizing its full potential in securing representation for all of Australia's biodiversity. Adapting the boundaries of prioritization frameworks by incorporating amassed information from a broad range of taxa should be of conservation significance.