Efficiency,costs and trade-offs in marine reserve system design

With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (<3%) and boundary length (<10%), the economic impact of marine reserves on the commercial rock lobster fishery was reduced by more than a third. We considered also how a reserve planner might prioritise conservation areas using information on a planning units selection frequency. We found that selection frequencies alone were not a reliable guide for the selection of marine reserve systems, but could be used with approaches such as summed irreplaceability to direct conservation effort for efficient marine reserve design.     

Integrating Land Market Feedbacks into Conservation Planning—A Mathematical Programming Approach

Nature reserves are often designated ad hoc. Despite increasing conservation efforts, loss of biodiversity is still accelerating. Considering land scarcity and demand for alternative uses, efficiency in conservation strongly correlates with efficiency in land allocation. Systematic conservation planning can effectively prioritize conservation activities. Previous studies minimize opportunity costs for given conservation targets. However, these studies assume constant marginal costs of habitat protection. We extend this cost minimization approach by also considering a dynamic representation of marginal costs. The more land is allocated to nature reserves, the higher are opportunity costs, i.e., costs of forgone agricultural production. This increase in costs results from changes in the prices of agricultural commodities. We employ a deterministic, spatially explicit mathematical optimization model to allocate species habitats by minimizing opportunity costs for setting aside land for conservation purposes. The model is designed as a mixed integer programming problem and solved with GAMS/CPLEX. Our results show the need for integrating land market feedbacks into conservation planning. We find that ignoring land rent adjustments can lead to highly cost-ineffective solutions in reserve selection.     

Economic and Spatial Impacts of an Existing Reserve Network on Future Augmentation

An optimization model for land reservation was developed that explicitly selects parcels in the most compact or contiguous manner possible while meeting habitat requirements and a budget limitation. The model was used to compare the effects of an existing reserve network on future parcel spatial locations and total cost. Using habitat and land value data from Josephine County, Oregon, it was found that a system of existing reserves created by various policies and overseen by different agencies can decrease future reserve compactness and contiguity, and increase total cost. This work suggests that coordinated planning can result in more efficient conservation efforts for less cost.     

Reserve Design to Maximize Species Persistence

We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and determining the best of the promising solutions using a multiple-comparison statistical test. We use the strategy to address a problem of allocating limited resources to new and existing reserves. The best reserve design depends on emigration, dispersal mortality, and probabilities of movement between reserves. When movement probabilities are symmetric, the best design is to expand a subset of reserves to equal size to exhaust the habitat budget. When movement probabilities are not symmetric, the best design does not expand reserves to equal size and is strongly affected by movement probabilities and emigration rates. We use commercial simulation software to obtain our results.     

Delineating protected wildlife corridors with multi‐objective programming

Protected wildlife corridors can help counteract habitat fragmentation and link isolated reserve “islands” into connected reserve systems. The need for wildlife corridors will grow as expanding human populations place increasing pressure on remaining undeveloped land. A two‐objective zero–one programming model is formulated for the problem of selecting land for a system of wildlife corridors that must connect a known set of existing reserves or critical habitat areas. This problem is modeled as a network Steiner tree problem, under the objectives of minimizing corridor land costs and minimizing the amount of unsuitable land within the corridor system. Linear programming is used to find exact solutions with little or no branching and bounding, and the multi‐objective weighting method is used to generate non‐inferior alternatives. Two hypothetical examples demonstrate the model and solution procedure. Results can help inform planning and decision making for protected area land acquisition and habitat restoration.     

The SITES reserve selection system: A critical review

Numerous models have been put forth to help with the growing demand for the establishment of biodiversity reserves. One site selection model that has been used in several recent studies is SITES [S.J. Andelman, I. Ball, F.W. Davis and D.M. Stoms, SITES V 1.0: an analytical toolbox for designing ecoregional conservation portfolios, Unpublished manual prepared for the nature conservancy, 1999, 1–43. (available at )]. SITES includes two heuristic solvers: based on Greedy and Simulated Annealing. We discuss the formulation of the SITES model, present a new formulation for that problem, and solve a number of test problems optimally using off-the-shelf software. We compared our optimal results with the SITES Simulated Annealing heuristic and found that SITES frequently returns significantly suboptimal solutions. Our results add further support to the argument, started by Underhill [L.G. Underhill, Optimal and suboptimal reserve selection algorithms, Biol. Conserv. 70 (1994) 85–87], continuing through Rodrigues and Gaston [A.S.L. Rodrigues and K.J. Gaston, Optimization in reserve selection procedures – why not?, Biol. Conserv. 107 (2002) 123–129], for greater integration of optimal methods in the reserve design/selection literature.     

Spatial attributes and reserve design models: A review

A variety of decision models have been formulated for the optimal selection of nature reserve sites to represent a diversity of species or other conservation features. Unfortunately, many of these models tend to select scattered sites and do not take into account important spatial attributes such as reserve shape and connectivity. These attributes are likely to affect not only the persistence of species but also the general ecological functioning of reserves and the ability to effectively manage them. In response, researchers have begun formulating reserve design models that improve spatial coherence by controlling spatial attributes. We review the spatial attributes that are thought to be important in reserve design and also review reserve design models that incorporate one or more of these attributes. Spatial modeling issues, computational issues, and the trade-offs among competing optimization objectives are discussed. Directions for future research are identified. Ultimately, an argument is made for the development of models that capture the dynamic interdependencies among sites and species populations and thus incorporate the reasons why spatial attributes are important.     

Optimal Carbon Capture and Storage Policies

The IPCC recommends the use of carbon capture and sequestration (CCS) technologies in order to achieve the Kyoto environmental goals. This paper sheds light on this issue by assessing the optimal strategy regarding the long-term use of CCS technologies. The aim is to analyze the optimal CCS policy when the sequestration rate is endogenous, being therefore one specific tool of the environmental policy. We develop a simple growth model to identify the main driving forces that should determine the optimal CCS policy. We show that, under some conditions on the cost of extractions, CCS may be a long-term solution to curb carbon emissions. We also show that over time the social planner will choose to decrease the rate of capture and sequestration. We then derive the decentralized equilibrium outcome by considering the programs of the fossil resource-holder and of the representative consumer. Finally, we determine the optimal environmental policy, i.e. the carbon tax scheme, as well as the dynamics of the fossil fuel price needed to implement it.     

Limitations of habitats as biodiversity surrogates for conservation planning in estuaries

Increasing pressures on global biodiversity and lack of data on the number and abundance of species have motivated conservation planners and researchers to use more readily available information as proxies or surrogates for biodiversity. “Habitat” is one of the most frequently used surrogates but its assumed value in marine conservation planning is not often tested. The present study developed and tested three alternative habitat classification schemes of increasing complexity for a large estuary in south-east Australia and tested their effectiveness in predicting spatial variation in macroinvertebrate biodiversity and selecting estuarine protected areas to represent species. The three habitat classification schemes were: (1) broad-scale habitats (e.g., mangroves and seagrass), (2) subdivision of each broad-scale habitat by a suite of environmental variables that varied significantly throughout the estuary, and (3) subdivision of each broad-scale habitat by the subset of environmental variables that best explained spatial variation in macroinvertebrate biodiversity. Macroinvertebrate assemblages differed significantly among the habitats in each classification scheme. For each classification scheme, habitat richness was significantly correlated with species richness, total density of macroinvertebrates, assemblage dissimilarity, and summed irreplaceability. However, in a reserve selection process designed to represent examples of each habitat, no habitat classification scheme represented species significantly better than a random selection of sites. Habitat classification schemes may represent variation in estuarine biodiversity; however, the results of this study suggest they are inefficient in designing representative networks of estuarine protected areas.     

Coral assemblages in Tonga: spatial patterns, replenishment capacities, and implications for conservation strategies

Coral reefs in Tonga have been confronted by multiple threats of various origins, including large-scale disturbances and human-induced stressors. These reef communities have been poorly studied, and efficient conservation actions are urgently needed. The aim of this study was to: (1) examine the spatial distribution of coral assemblages in the lagoon of Tongatapu; (2) determine the degree to which spatial heterogeneity of adult corals is influenced by recruitment processes; and (3) examine the implications of these results in terms of conservation actions. We recorded a total of 37 adult and 28 juvenile coral genera, a mean density of 11.6 adult and 5.5 juvenile colonies m^?2, and a dominance of Montipora, Acropora, and Porites. For seven of the 10 dominant genera, spatial patterns of adults were linked to the short-term recruitment pattern history. Despite a reduced diversity and abundance of adult corals in some areas, the lagoon of Tongatapu retains the potential for replenishment through recruitment of young corals. Consequently, we suggest that conservation actions should focus on reducing factors causing coral mortality and maintain suitable conditions for the establishment and growth of juvenile corals, thus increasing the probability that they will reach maturity and participate to the maintenance of local populations. Rather than establishing a large marine protected area, which will almost certainly suffer from a lack of control and poor enforcement, alternative conservation measures could be successfully implemented through the establishment of several small village-based marine reserves, as has been undertaken in other South Pacific islands with promising results.     

Representational success: A new paradigm for achieving species protection by reserve site selection

Models for designing habitat reserve networks have focused on minimizing the number of sites necessary to cover each species one or more times. A solution to this problem is usually one from among a large number of alternative optimal configurations of sites. This paper develops an iterative method for building reserve networks that produces an optimal solution to the species set covering problem (SSCP) and also maximizes the number of species covered two or more times, three or more times, and so on, conditional on the solution to the previous iteration. We refer to this as representational success. Thus, a pareto optimal species set covering is achieved that is preferable to an arbitrary optimal solution to the SSCP.     

Designing a conservation reserve network with minimal fragmentation: A linear integer programming approach

In the biological conservation literature, the optimum reserve site selection problem has often been addressed by using the prototype set covering and maximal covering formulations, assuming that representation of species is the only criterion in site selection. This approach usually results in a small but highly fragmented reserve, which is not useful for practical conservation planning. To improve the chances of species' persistence, it may be desirable to reduce habitat fragmentation. This paper presents a linear integer programming formulation to minimize spatial gaps between selected sites in a reserve network, which is applied to a data set on breeding birds. The authors express their willingness to share the database used in this study. Those readers who wish to have access to the data may contact Robert A. Briers at r.briers@napier.ac.uk.     

Geospatial assessment and monitoring of historical forest cover changes (1920–2012) in Nilgiri Biosphere Reserve,Western Ghats,India

Deforestation in the biosphere reserves, which are key Protected Areas has negative impacts on biodiversity, climate, carbon fluxes and livelihoods. Comprehensive study of deforestation in biosphere reserves is required to assess the impact of the management effectiveness. This article assesses the changes in forest cover in various zones and protected areas of Nilgiri Biosphere Reserve, the first declared biosphere reserve in India which forms part of Western Ghats-a global biodiversity hotspot. In this study, we have mapped the forests from earliest available topographical maps and multi-temporal satellite data spanning from 1920’s to 2012 period. Mapping of spatial extent of forest cover, vegetation types and land cover was carried out using visual interpretation technique. A grid cell of 1 km?×?1 km was generated for time series change analysis to understand the patterns in spatial distribution of forest cover (1920–1973–1989–1999–2006–2012). The total forest area of biosphere reserve was found to be 5,806.5 km² (93.8 % of total geographical area) in 1920. Overall loss of forest cover was estimated as 1,423.6 km² (24.5 % of the total forest) with reference to 1920. Among the six Protected Areas, annual deforestation rate of >0.5 was found in Wayanad wildlife sanctuary during 1920–1973. The deforestation in Nilgiri Biosphere Reserve is mainly attributed to conversion of forests to plantations and agriculture along with submergence due to construction of dams during 1920 to 1989. Grid wise analysis indicates that 851 grids have undergone large-scale negative changes of >75 ha of forest loss during 1920–1973 while, only 15 grids have shown >75 ha loss during 1973–1989. Annual net rate of deforestation for the period of 1920 to 1973 was calculated as 0.5 followed by 0.1 for 1973 to 1989. Our analysis shows that there was large-scale deforestation before the declaration of area as biosphere reserve in 1986; however, the deforestation has drastically reduced after the declaration due to high degree of protection, thus indicating the secure future of reserve in the long term under the current forest management practices. The present work will stand as the most up-to-date assessment on the forest cover of the Nilgiri Biosphere Reserve with immediate applications in monitoring and management of forest biodiversity.     

Effects of the Conservation Reserve Program on northern bobwhite and grassland birds

The Conservation Reserve Program (CRP) has converted just over 36 million acres of cropland into potential wildlife habitat, primarily grassland. Thus, the CRP should benefit grassland songbirds, a group of species that is declining across the United States and is of conservation concern. Additionally, the CRP is an important part of multi-agency, regional efforts to restore northern bobwhite populations. However, comprehensive assessments of the wildlife benefits of CRP at regional scales are lacking. We used Breeding Bird Survey and National Resources Inventory data to assess the potential for the CRP to benefit northern bobwhite and other grassland birds with overlapping ranges and similar habitat associations. We built regression models for 15 species in seven different ecological regions. Forty-nine of 108 total models contained significant CRP effects (P < 0.05), and 48 of the 49 contained positive effects. Responses to CRP varied across ecological regions. Only eastern meadowlark was positively-related to CRP in all the ecological regions, and western meadowlark was the only species never related to CRP. CRP was a strong predictor of bird abundance compared to other land cover types. The potential for CRP habitat as a regional conservation tool to benefit declining grassland bird populations should continue to be assessed at a variety of spatial scales. We caution that bird-CRP relations varied from region to region and among species. Because the NRI provides relatively coarse resolution information on CRP, more detailed information about CRP habitats (spatial arrangement, age of the habitat (time since planting), specific conservation practices used) should be included in future assessments to fully understand where and to what extent CRP can benefit grassland birds.     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.     

Restoring habitat corridors in fragmented landscapes using optimization and percolation models

Landscape fragmentation and habitat loss are significant threats to the conservation of biological diversity. Creating and restoring corridors between isolated habitat patches can help mitigate or reverse the impacts of fragmentation. It is important that restoration and protection efforts be undertaken in the most efficient and effective way possible because conservation budgets are often severely limited. We address the question of where restoration should take place to efficiently reconnect habitat with a landscape-spanning corridor. Building upon findings in percolation theory, we develop a shortest-path optimization methodology for assessing the minimum amount of restoration needed to establish such corridors. This methodology is applied to large numbers of simulated fragmented landscapes to generate mean and variance statistics for the amount of restoration needed. The results provide new information about the expected level of resources needed to realize different corridor configurations under different degrees of fragmentation and different characterizations of habitat connectivity (“neighbor rules”). These results are expected to be of interest to conservation planners and managers in the allocation of conservation resources to restoration projects.     

Design to monitor trend in abundance and presence of American beaver (Castor canadensis) at the national forest scale

Wildlife conservationists design monitoring programs to assess population dynamics, project future population states, and evaluate the impacts of management actions on populations. Because agency mandates and conservation laws call for monitoring data to elicit management responses, it is imperative to design programs that match the administrative scale for which management decisions are made. We describe a program to monitor population trends in American beaver (Castor canadensis) on the US Department of Agriculture, Black Hills National Forest (BHNF) in southwestern South Dakota and northeastern Wyoming, USA. Beaver have been designated as a management indicator species on the BHNF because of their association with riparian and aquatic habitats and its status as a keystone species. We designed our program to monitor the density of beaver food caches (abundance) within sampling units with beaver and the proportion of sampling units with beavers present at the scale of a national forest. We designated watersheds as sampling units in a stratified random sampling design that we developed based on habitat modeling results. Habitat modeling indicated that the most suitable beaver habitat was near perennial water, near aspen (Populus tremuloides) and willow (Salix spp.), and in low gradient streams at lower elevations. Results from the initial monitoring period in October 2007 allowed us to assess costs and logistical considerations, validate our habitat model, and conduct power analyses to assess whether our sampling design could detect the level of declines in beaver stated in the monitoring objectives. Beaver food caches were located in 20 of 52 sampled watersheds. Monitoring 20 to 25 watersheds with beaver should provide sufficient power to detect 15–40% declines in the beaver food cache index as well as a twofold decline in the odds of beaver being present in watersheds. Indices of abundance, such as the beaver food cache index, provide a practical measure of population status to conduct long-term monitoring across broad landscapes such as national forests.     

A habitat-based microscale forest classification system for zoning wood production areas to conserve a rare species threatened by logging operations in south-eastern Australia

The production of timber from native forests is presently one of the most controversial land management issues in Australia. Part of this controversy results from the potential impacts of forestry practices on forest-dependent fauna, particularly those that are rare and endangered, such as Leadbeater's Possum Gymnobelideus leadbeateri McCoy, in the forests of central Victoria, south-eastern Australia. A significant proportion of the highly limited distribution of this species overlaps with some of the most valuable wood production forests in Australia within which extensive clearfelling operations are employed to produce timber and pulpwood. These operations can destroy the habitat of G. leadbeateri. The Victoria government agency that is responsible for forest and wildlife management has devised a forest zoning system as part of the management strategies to conserve G. leadbeateri within timber production areas. This is designed to partition the forest into three types of areas: (1) where the conservation of G. leadbeateri is a priority, (2) where wood production is a priority, and, (3) where both land uses are a joint priority. The classification of areas of forest where the conservation of G. leadbeateri is the primary land use is based on an understanding of the habitat requirements of the species. The results of recent field studies, where statistical models of the habitat requirements of G. leadbeateri have been developed and their performance subsequently tested using a new dataset, highlights the need for a new basis to guide the classification of areas for the conservation of the species within wood production forests. We describe a method for devising a forest management zoning system that is based on a statistical model of the habitat requirements of G. leadbeateri and which will better integrate wood production and the conservation of the species. This procedure accounts for the uncertainty in the statistical model and, in turn, reduces the risk that areas where G. leadbeateri occurs are logged, whilst ensuring that other areas are not unnecessarily excluded from timber harvesting.     

The areal extent of brown shrimp habitat suitability in Mobile Bay, Alabama, USA: targeting vegetated habitat restoration

The availability of wetlands and shallow water habitats significantly influences Gulf of Mexico (GOM) penaeid shrimp fishery productivity. However, the GOM region has the highest rate of wetland loss in the USA. Protection and management of these vital GOM habitats are critical to sustainable shrimp fisheries. Brown shrimp (Farfantepenaeus aztecus) are a major component of GOM fisheries. We present an approach for estimating the areal extent of suitable habitat for post-larval and juvenile brown shrimp in Mobile Bay, Alabama, using an existing habitat suitability index model for the northern GOM calculated from probabilistic survey of water quality and sediment data, land cover data, and submerged aquatic vegetation coverages. This estuarine scale approach is intended to support targeted protection and restoration of these habitats. These analyses indicate that approximately 60% of the area of Mobile Bay is categorized as suitable to near optimal for post-larval and juvenile shrimp and 38% of the area is marginally to minimally suitable. We identify potential units within Mobile Bay for targeted restoration to improve habitat suitability.     

Evaluating Habitat as a Surrogate for Population Viability Using a Spatially Explicit Population Model

Because data for conservation planning are always limited, surrogates are often substituted for intractable measurements such as species richness or population viability. We examined the ability of habitat quality to act as a surrogate for population performance for both Red-shouldered Hawks (Buteo lineatus) and Northern Goshawks (Accipiter gentilis). We compared simple measures of habitat quality to estimates of population growth rates obtained from a spatially explicit model of population dynamics. We found that habitat quality was a relatively poor predictor of simulated population growth rates for several reasons. First, a relatively small proportion of the potential habitat for each species served as population sources in our simulations--15% for Red-shouldered Hawks and 2% for Goshawks. Second, when habitat quality correctly predicted demographic sources on the landscape, it consistently underestimated the contribution of these areas to the population. In areas where habitat quality correctly anticipated the presence of demographic sinks, we found no useful quantitative relationship between the two measures. Our simulation model captured the influence of habitat quality on the hawk populations, but it also incorporated interactions between dispersing individuals and landscape patterns. Thus, the discrepancies we observed likely reflected the influence of forest fragmentation and the spatial arrangement of forest patches on the populations. We conclude that simple measures of habitat quality will often be poor surrogates for population persistence, but that spatially explicit population models can help inform the development of better indices.