Reserve Design Research Articles

Movement behaviour of fish, harvesting-induced habitat degradation and the optimal size of marine reserves

Many models have assessed how marine reserves protect fish populations and—under certain conditions—simultaneously increase yield. Only recently have models considered the effects of fishing-induced habitat damage by assuming reduced population growth in fishing areas. Even though it is understood that fish movement patterns affect the functioning and design of marine reserves, fishing-induced changes in movement patterns, as a response to decreased habitat quality, have not been studied in this context. Our work explores how harvesting-induced movement behaviour of fish can affect optimal yield and size of a marine reserve. Our model is based on reaction-diffusion equations and recent advances in their application to strongly heterogeneous environments with sharp transitions in environmental conditions. We model movement behaviour in response to harvesting and habitat destruction via increased diffusion rates and increased preference for protected areas, and implement reduced reproduction as an effect of habitat degradation. We find an alternative mechanistic explanation for the empirical observation that high fish mobility may not decrease fish density inside a reserve. We also find that movement-behavioural responses of fish to harvesting can decrease the economic value of protected areas and increase their conservation value. For maximum sustainable yield, we find that a low harvesting rate and small protected area are optimal when fish show a strong preference for protected areas as a response to fishing efforts. On the other hand, a high harvesting rate and a large protected area are optimal if fish respond to harvesting by a strong increase in movement rates in fishing areas.

Optimising Seagrass Conservation for Ecological Functions

Animals are central to numerous ecological processes that shape the structure and function of ecosystems. It follows that species that are strongly linked to specific functions can represent these functions spatially and hence be useful in conservation planning. Here we test this notion of ‘functional species surrogacy’ for the conservation of seagrass meadows that have been impacted by stressors. We measured algal herbivory and herbivorous fish assemblages across a range of seagrass meadows in the Moreton Bay Marine Park, Queensland, Australia. We determined the suitability of herbivorous fish to act as a surrogate for the function of algal herbivory and modelled the abundance of this surrogate, and thus herbivory, in seagrass meadows to compare the spatial distribution of this function within existing reserves. We used underwater video systems to determine the abundance of all herbivorous fish species in seagrass meadows. The abundance of the dusky rabbitfish (Siganus fuscescens) was the best predictor of algal herbivory in seagrass meadows, supporting the suitability of this species as a functional surrogate. The distribution of dusky rabbitfish, and therefore the ecological function of herbivory, was not well represented in the Moreton Bay Marine Park protected areas. Only 7% of the equivalent area of seagrass meadows protected in marine reserves were found to have high abundances of dusky rabbitfish. We demonstrate that the abundance of functionally important herbivores can be suitable as a surrogate for herbivory in seagrass conservation. Our findings show that data on the spatial distribution of ecological functions can alter priorities for reserve design, and we suggest that our functional approach to species surrogacy is likely to improve conservation performance in seagrass ecosystems.

Tropical invertebrate response to marine reserves varies with protection duration, habitat type, and exploitation history

Abstract Macroinvertebrates play a critical role in marine processes, are important in global fisheries, and make up the vast majority of ocean biodiversity, yet are largely overlooked in fisheries stock assessment and conservation. Marine reserves are a heavily advocated method for promoting recovery of marine biodiversity, but the design of reserves and the methods for evaluating their performance often neglect invertebrate taxa, instead assessing changes in fish abundance or biomass. The purpose of this study is to (1) measure the impacts of no‐take marine reserves on marine macroinvertebrates, (2) identify the correlates of changes to macroinvertebrate abundance, and (3) determine if the typical taxa used to measure reserve success (finfish) can predict changes in invertebrate abundance. Non‐coral, non‐sponge, macroinvertebrates were sampled inside and outside of 10 community‐managed marine reserves in the Central Philippines and compared with abundances found at distant fished sites. Using generalized linear mixed effects models with multimodel inference, positive reserve effects were found in exploited invertebrate taxa both inside and outside of reserves (1.5–2.3 times greater abundances), but no effect was found in unfished taxa. Habitat composition and complexity were consistently associated with higher invertebrate abundance. Most surprisingly, invertebrate abundance was not consistently predicted by that of fish. These results indicate fish, in isolation, may not be an ideal indicator for biodiversity response to reserves, and habitat considerations are important when creating reserves that support invertebrates. These results are particularly relevant to practitioners in developing regions, where community‐managed reserves are common and invertebrates are important in fisheries.

Within country targeting of agri-environment funding: A test of different methods

Many countries employ agri-environment schemes to lessen the impact of agriculture on biodiversity. Prioritisation has been a feature of schemes in terms of focussing funding on individual species, habitats or regions. For the 2014–2020 Agri-Environment and Climate Scheme Scotland decided on an alternative prioritisation method; for a number (11) of management options funding was made available for areas (10 km × 10 km grid squares) with more than a threshold of priority species present (a subset of species on the Scottish Biodiversity List likely to benefit from the management options). This approach (Simple targeting) takes no account of the different abundances of the priority species or the possibility that rare species’ distributions are not nested within the more common ones.Three alternative methods were used to assess if that targeting could be made more efficient in its coverage of species’ ranges. Rarity Weighted targeting took into account range sizes of different priority species, Uniqueness targeting focussed on maximising the beta-diversity of targeted grid squares, and Marxan targeting used a reserve selection algorithm to solve the minimum set reserve design problem. Assessment was in terms of how well each method covered the range of the priority species, both on average and on minimum representation of each species on the priority list.Rarity Weighted targeting improved the mean representation of species’ ranges across all 11 options, whereas Marxan targeting performed best of the four methods in ensuring a high minimum representation of species. Uniqueness targeting was uniformly poor. These patterns were conserved whatever the threshold of species richness used in the Simple targeting.If funding for agri-environment options is to be targeted to areas where more species can benefit, then the current Simple targeting approach employed in Scotland can be improved upon in its efficiency at channelling funding to where the priority species are found. However, a strategic choice has to be made as to whether maximising the mean coverage of priority species is the most important objective of the targeting process or whether ensuring high minimum coverage of the species is more important; ensuring that rarer species with ranges poorly nested within those of rarer species are well represented in the targeted areas.

Dual-Flow Structure to Design a Continuous and Compact Nature Reserve

Establishing the conservation reserves is an efficient approach to protect various species, in which maintaining the spatial characteristics of the habit is an important issue. A continuous and compact reserve is vital for long-term survival and reproduction of various species. However, the existing methods for nature reserve design have the problem of the selected sites which are sparse in space. The sparseness refers to the isolated regions which are the unselected (selected) sites and surrounded by the selected (unselected) sites in the designed nature reserve and thus making the management of protected areas and exchange of information between species difficult. In this paper, we propose the concept of a dual-flow mechanism which is called the dual-flow structure ( DFS ) to address the problem of sparseness in sites selected for the reserve network design. The DFS constructs two consecutive arcs: one is for selected sites and the other is for unselected sites, simultaneously. Those two arcs ensure that each site has at least one adjacent site which has the same status (selected/unselected) with the competitive mechanism. The concept of two consecutive arcs can solve the problem of sparseness and achieve spatial continuity. The DFS further utilizes the perimeter in dual-flow structure to achieve the spatial characteristic of compactness. The main contributions of this study are: (1) we design a novel mathematical model which solves the problem of sparseness in the space, including selected and un-selected sites; and (2) the DFS generates the connectivity and compactness of the reserve network with the scientific and reasonable techniques. In the experiments, we take the Daiyun Mountains as a study area to demonstrate the feasibility and effectiveness of the proposed model.

Potential of a no-take marine reserve to protect home ranges of anadromous brown trout (Salmo trutta).

The extent to which no‐take marine reserves can benefit anadromous species requires examination. Here, we used acoustic telemetry to investigate the spatial behavior of anadromous brown trout (sea trout, Salmo trutta) in relation to a small marine reserve (~1.5 km2) located inside a fjord on the Norwegian Skagerrak coast. On average, sea trout spent 42.3 % (±5.0% SE) of their time in the fjord within the reserve, a proportion similar to the area of the reserve relative to that of the fjord. On average, sea trout tagged inside the reserve received the most protection, although the level of protection decreased marginally with increasing home range size. Furthermore, individuals tagged outside the reserve received more protection with increasing home range size, potentially opposing selection toward smaller home range sizes inflicted on fish residing within reserves, or through selective fishing methods like angling. Monthly sea trout home ranges in the marine environment were on average smaller than the reserve, with a mean of 0.430 (±0.0265 SE) km2. Hence, the reserve is large enough to protect the full home range of some individuals residing in the reserve. Synthesis and applications: In general, the reserve protects sea trout to a varying degree depending on their individual behavior. These findings highlight evolutionary implications of spatial protection and can guide managers in the design of marine reserves and networks that preserve variation in target species' home range size and movement behavior.

Analyzing local opposition to biosphere reserve creation through semantic network analysis: The case of Baekdu mountain range, Korea

Biosphere reserves designate ecologically superior and sensitive areas for local biodiversity and sustainable use. Despite their promised benefits, some areas fail to be designated as biosphere reserves due to opposition by local residents. This study investigates the causes of failed biosphere reserve designation using a semantic network analysis of local resident meetings concerning designation of the Baekdudaegan mountain range as a biosphere reserve. The analysis results reveal that the main topics of discussion were legislation of the biosphere reserve, its administration, and the consultation process. The residents made strong demands on the legislative system and administrative operation, whereas the administrative agency attempted to solve this problem through the consultation process. This suggests that the agency in charge of designating biosphere reserves must first ensure transparency in the legislative and administration operation process, which may not be completely successful through the consultation process. When designating biosphere reserves in future, we recommend that authorities first establish guidelines for transparency in the legislation of regulations and the administrative operation process and obtain the trust of local people for the consultation process.

Evaluating bioeconomic tradeoffs of fishing reserves via spatial optimization

No-take marine reserves are common strategies used in spatial fisheries management. There are at least four general objectives for marine reserve design: (1) maximizing conservation, (2) minimizing total reserve area, (3) maximizing reserve compactness, and (4) minimizing socioeconomic opportunity cost (e.g., fisheries revenue). A spatial optimization model was developed to solve for reserve placements under those four objectives, while evaluating the bioeconomic tradeoffs and potential gaps of a subset of bottomfish restricted fishing areas (BRFAs) for the Hawaiian bottomfish fishery. Optimized reserve placements with minimal opportunity costs had little overlap (< 9%) with the placements of the BRFAs, opportunity cost values 50–83% less than that of the BRFAs with 40–54% higher potential conservation value. When reserve placements were optimized to provide a maximal opportunity cost, solutions had up to 49% overlap with the BRFAs, highlighting a potential drawback of the BRFA system with respect to socioeconomic impacts. When opportunity cost was instead calculated as total area, the optimized placements also had considerable overlap (up to 42%) with the BRFAs, highlighting the importance of socioeconomic data to the reserve design process. The solutions that provided maximal reserve compactness may be the most pragmatic for a reserve design team with specific area and/or conservation targets, as these solutions produced compact reserve placements that best matched those targets at a minimal opportunity cost. This analysis emphasized the use of spatial optimization models to not only guide the reserve design process, but to highlight tradeoffs of conflicting fisheries objectives in reserve design.

Reserve Design: Unintended Consequences and the Demise of Boston’s Walk Zones

We show that in the presence of admissions reserves, the effect of the precedence order (i.e., the order in which different types of seats are filled) is comparable to the effect of adjusting reserve sizes. Either lowering the precedence of reserve seats at a school or increasing the school’s reserve size weakly increases reserve-group assignment at that school. Using data from Boston Public Schools, we show that reserve and precedence adjustments have similar quantitative effects. Transparency about these issues—in particular, how precedence unintentionally undermined intended policy—led to the elimination of walk zone reserves in Boston’s public school match.

Optimizing the Geometry of Wildlife Corridors in Conservation Reserve Design

Wildlife corridors are often used to connect critical habitat for species protection. Mixed integer programming models have been used in the past to create wildlife corridors, but they lack the capacity to control corridor geometry. We propose an approach that employs path planning techniques from artificial intelligence to account for and control corridor geometry, such as width and length. By combining path planning with network optimization, our approach allows the user to control and optimize the geometric characteristics of wildlife corridors. We illustrate our approach on two realistic landscapes and present numerical results on several computer-generated landscapes. The computational results indicate that this approach is efficient and can address problems controlling corridor geometry that were previously thought intractable. The approach has potential applications in such areas as the selection of routes or barrier construction problems, an example of which is firebreak design.Data are available at https://doi.org/10.1287/opre.2018.1758 .

The integration and application of genomic information in mangrove conservation.

Article impact statement: Genomic information can help prevent species loss, facilitate reserve design and maximize adaptive potential of natural mangrove populations.

Predicting impact to assess the efficacy of community‐based marine reserve design

AbstractDuring the planning phase the efficacy of different strategies to manage marine resources should ultimately be assessed by their potential impact, or ability to make a difference to ecological and social outcomes. While community‐based and systematic approaches to establishing marine protected areas have their strengths and weaknesses, comparisons of their effectiveness often fail to explicitly address potential impact. Here, we predict conservation impact to compare recently implemented community‐based marine reserves in Tonga to a systematic configuration specifically aimed at maximizing impact. Boosted regression tree outputs indicated that fishing pressure accounted for ∼24% of variation in target species biomass. We estimate that the community‐based approach provides 84% of the recovery potential of the configuration with the greatest potential impact. This high potential impact results from community‐based reserves being located close to villages, where fishing pressure is greatest. These results provide strong support for community‐based marine management, with short‐term benefits likely to accrue even where there is little scope for systematic reserve design.

Predicting estuarine faunal assemblages using enduring environmental surrogates, with applications in systematic conservation planning

Conservation planning in estuaries has lagged behind that in terrestrial and marine areas, despite these valuable ecosystems being among the most degraded. The core of any such approach is a reliable habitat classification and inventory of target biota. These data, and particularly the latter, are often lacking at the local-regional scales most relevant to estuarine management. This study presents a quantitative approach for predicting the likely fish and benthic invertebrate assemblages at any unsampled estuarine site using readily-obtainable and enduring biophysical attributes. We apply this scheme to an urbanised estuary and predict the above faunas throughout its entire nearshore zone. These data are then used to systematically design an exploratory spatially-efficient reserve that meets representation targets for numerous faunal conservation features, and test the ability of an existing, unsystematically-derived Marine Park to do the same.Spatial patterns in the enduring biophysical attributes of local-scale habitats provided good to excellent surrogates for those in the fish and invertebrate faunas. All unsampled sites were then successfully assigned to their respective habitat and correlated fauna using biophysical measurements and a predictive decision tree. The resultant spatially-continuous ‘faunal map’ enabled quantification of 67 conservation features, from which reserves aimed at representing 10–30% of each feature were systematically derived. All reserves were highly efficient and almost always met representation targets, contrasting with the existing Marine Park which underrepresented 40–80% of features. Reserve designs were, however, spread throughout the system, highlighting the complexities in designing representative reserves for estuarine environments that capture their spatio-temporal diversity.

Designing a Protected Area to Safeguard Imperiled Species from Urbanization

AbstractReserve design is a process that can address ecological, social, and political factors to identify parcels of land needed to sustain wildlife populations and other natural resources. Acquisition of parcels for a large terrestrial reserve is difficult because it typically occurs over a long timeframe and thus invokes consideration of future conditions such as climate and urbanization changes. In central Florida, the U.S. government has authorized a new protected area, the Everglades Headwaters National Wildlife Refuge. The new refuge will host important threatened and endangered species and habitats, and will be located to allow for species adaptation from climate change impacts. For this study we combined habitat objectives defined by the U.S. Fish and Wildlife Service and projections from two urbanization models to provide guidance for Everglades Headwaters National Wildlife Refuge design. We used Marxan with Zones to find near-optimal solutions for protecting explicit amounts of five target habitats. We identified parcels for inclusion into the reserve design that the models allocated among two zones representing different methods of protection: fee-simple purchase (up to 20,234 ha authorized by the U.S. government), and conservation easement agreements (up to 40,469 ha authorized). As expected, for all scenarios we found an increase in costs as the proportion of fee-simple purchases was increased, reflecting the lesser cost of easements, but the number of parcels required for protection differed little among scenarios. The two urbanization models showed considerable agreement over which habitat patches they did not forecast to be developed, and some agreement over which parcels might be developed. The U.S. Fish and Wildlife Service may benefit from focusing on parcels that our analyses select frequently under both urban scenarios because these parcels are more likely to be in areas where there are fewer urbanization threats and a lower demand for land. The reserve designs we generated met U.S. Fish and Wildlife Service habitat goals within fee and easement zone restrictions, and we found reserve configurations that fell well below the mandated size limit.

Foraging movements of common noddies in the East Indian Ocean are dependent on breeding stage: implications for marine reserve design

Increasingly, space use by foraging seabirds is being used as an indicator of ocean condition to inform projected planning for climate change, fisheries management and marine protected areas. We tracked foraging common noddies (Anous stolidus) from a colony in the East Indian Ocean using back-mounted solar GPS trackers during incubation and chick rearing to evaluate their suitability as biomonitors of ocean condition, and the overlap of flight tracks with marine protected area boundaries. This is the first study to track this species in its eastern distribution and across different stages of the breeding cycle. Six birds were tracked for 89 days in total, describing 10089km of flight. Birds made significantly longer trips during chick rearing, which may reflect reduced availability of prey. The tracking period coincided with a particularly strong ENSO event, which may have impacted foraging behaviour, but the foraging area was found to be at least 10000km2. Foraging was associated with the end points of outward trips that were generally at the edge of the continental shelf, or within proximity of canyon-like bathymetric features or current structures on the shelf. Birds foraged over the shelf during incubation, suggesting a greater reliance on food web structures associated with Leeuwin Current structures. Home ranges and movement tracks showed limited overlap with proposed marine park boundaries, but are promising as indicators of ocean productivity, suggesting that their role in the design of marine reserve networks in the future should be maximised.

Combining molecular and landscape tools for targeting evolutionary processes in reserve design: An approach for islands.

The importance of targeting ecological and evolutionary processes in reserve design has been widely acknowledged in the literature but rarely implemented on islands. Using Socotran reptiles as models, we aim to relate richness of widespread and restricted-range species directly with landscape variables and to compare the impact of setting conservation targets for lineages versus species. Socotra Island is a UNESCO Natural World Heritage Site, containing high levels of endemism in relation to its area, especially of reptiles, the vertebrates with the most comprehensive available genetic data. We predicted the occurrences of reptile species using distribution models and used a novel approach to interpolate maps of spatial phylogenetic patterns. Patterns of intra and interspecifc diversity and differences between spatial outputs of lineage and species richness were related to eco-geographic variables. We evaluated differences in target achievement for each conservation unit within protected areas (PAs) under the current Zoning Plan (ZP) using gap and reserve design analyses. Although intraspecific richness was strongly correlated with interspecific richness, differences in their spatial distribution reached ~30% in some areas. Differences were more pronounced for wide-ranging than restricted-range taxa. Gap analysis indicates that most conservation units are under-represented in sanctuaries and that intra and interspecific richness were significantly higher outside PAs. This work will guide local-scale conservation planning as the ZP is due to be re-evaluated. This is one of the few studies on islands using genetic data from an entire class of vertebrates to incorporate lineage diversity in reserve design. This study provides an alternative methodological framework for supporting the use of landscape and genetic tools in reserve design, circumventing the use of phylogenetic distances and deterministic spatial interpolation of lineage diversity that can be widely applied to other systems.

Difficult decisions: Strategies for conservation prioritization when taxonomic, phylogenetic and functional diversity are not spatially congruent

Preventing further loss of biodiversity is the most important challenge for conservation biology. The loss of species and the functions and services they provide has negative implications for human well-being. However, conservation efforts focussed on sites with high numbers of species may inadvertently under-represent other facets of biodiversity such as phylogenetic and functional diversity. Further, because these different biodiversity facets vary in their degree of spatial congruence, methods of site selection that maximize phylogenetic, functional, and species diversity are necessary to represent biodiversity in a holistic fashion. In this paper we discuss approaches to such multi-faceted site-level prioritization. Specifically, we examine complementarity algorithms and provide strategies to weight species selection by their trait or phylogenetic distinctiveness. Further, we explore approaches that integrate diversity facets into a single measure of prioritization and incorporate complementarity such that the goal is not just optimizing the protection of biodiversity, but to prioritize the addition of sites representing unprotected biodiversity across different facets. We highlight the strengths and limitations of such an approach. These types of holistic approaches to reserve design should provide flexibility in the face of changing knowledge and priorities.

How large spatially-explicit optimal reserve design models can we solve now? An exploration of current models’ computational efficiency

Spatially-explicit optimal reserve design models select best sites from a set of candidate sites to assemble nature reserves to protect species (or habitats) and these reserves display certain spatial attributes which are desirable for species. These models are formulated with linear 0–1 programming and solved using standard optimisation software, but they were run on different platforms, resulting in discrepant or even conflicting messages with regard to their computational efficiency. A fair and accurate comparison of the convenience of these models would be important for conservation planners who use these models. In this article, we considered eight models presented in literature and tested their computational efficiency using randomly generated data sets containing up to 2000 sites. We focused on reserve contiguity and compactness which are considered crucial to species persistence. Our results showed that two of these models, namely Williams (2002) and Önal et al. (2016), stand out as the most efficient models. We also found that the relative efficiency of these models depends on the scope of analysis. Specifically, the Williams (2002) model solves more of the test problems when contiguity is the only spatial attribute and a large subset of the candidate sites needs to be selected. When compactness is considered also, the Önal et al. (2016) model generally performs better. Large scale models are found to be difficult to solve in a reasonable period of time. We discussed factors that may affect those models’ computational efficiency, including model size, share of selected sites, model structure and input data. These results provide useful insight and guidance to conservation practitioners and researchers who focus on spatial aspects and work with large-scale data sets.

Reserve design to optimize the long‐term persistence of multiple species

Protected areas form the cornerstone of global efforts to conserve biodiversity. Most current methods for designing reserve networks focus on maximizing the representation of species, but with no assurance that those species will persist in the protected landscapes into the future. We present a new strategy for reserve design that combines metapopulation theory with spatial conservation prioritization to estimate conservation solutions that minimize extinction risk across numerous species simultaneously. Our framework optimizes the spatial configuration of reserves to maximize metapopulation persistence for an entire assemblage of species by accounting for both species representation and landscape connectivity. As a case study, we design a reserve network for 114 terrestrial mammal species in Indonesian New Guinea. Our approach builds on Marxan, the flagship representation-based reserve design tool, improving estimated persistence (metapopulation capacity) by an average of 4.6-fold across species, without increasing the socioeconomic cost. We suggest that enhancing species persistence, rather than protecting arbitrary proportions of species' ranges, should be the ultimate objective of conservation planning.

Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images

Machine learning algorithms have increased tremendously in power in recent years but have yet to be fully utilized in many ecology and sustainable resource management domains such as wildlife reserve design, forest fire management and invasive species spread. One thing these domains have in common is that they contain dynamics that can be characterized as a Spatially Spreading Process (SSP) which requires many parameters to be set precisely to model the dynamics, spread rates and directional biases of the elements which are spreading. We present related work in Artificial Intelligence and Machine Learning for SSP sustainability domains including forest wildfire prediction. We then introduce a novel approach for learning in SSP domains using Reinforcement Learning (RL) where fire is the agent at any cell in the landscape and the set of actions the fire can take from a location at any point in time includes spreading North, South, East, West or not spreading. This approach inverts the usual RL setup since the dynamics of the corresponding Markov Decision Process (MDP) is a known function for immediate wildfire spread. Meanwhile, we learn an agent policy for a predictive model of the dynamics of a complex spatially-spreading process. Rewards are provided for correctly classifying which cells are on fire or not compared to satellite and other related data. We examine the behaviour of five RL algorithms on this problem: Value Iteration, Policy Iteration, Q-Learning, Monte Carlo Tree Search and Asynchronous Advantage Actor-Critic (A3C). We compare to a Gaussian process based supervised learning approach and discuss the relation of our approach to manually constructed, state-of-the-art methods from forest wildfire modelling. We also discuss the relation of our approach to manually constructed, state-of-the-art methods from forest wildfire modelling. We validate our approach with satellite image data of two massive wildfire events in Northern Alberta, Canada; the Fort McMurray fire of 2016 and the Richardson fire of 2011. The results show that we can learn predictive, agent-based policies as models of spatial dynamics using RL on readily available satellite images that other methods and have many additional advantages in terms of generalizability and interpretability.