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Investigation of a novel approach for aquaculture site selection
Abstract
This study investigated the potential use of two “species distribution models” (SDMs), Mahalanobis Typicality and Maxent, for aquaculture site selection. SDMs are used in ecological studies to predict the spatial distribution of species based on analysis of conditions at locations of known presence or absence. Here the input points are aquaculture sites, rather than species occurrence, thus the models evaluate the parameters at the sites and identify similar areas across the rest of the study area. This is a novel approach that avoids the need for data reclassification and weighting which can be a source of conflict and uncertainty within the commonly used multi-criteria evaluation (MCE) technique. Using pangasius culture in the Mekong Delta, Vietnam, as a case study, Mahalanobis Typicality and Maxent SDMs were evaluated against two models developed using the MCE approach. Mahalanobis Typicality and Maxent assess suitability based on similarity to existing farms, while the MCE approach assesses suitability using optimal values for culture. Mahalanobis Typicality considers the variables to have equal importance whereas Maxent analyses the variables to determine those which influence the distribution of the input data. All of the models indicate there are suitable areas for culture along the two main channels of the Mekong River which are currently used to farm pangasius and also inland in the north and east of the study area. The results show the Mahalanobis Typicality model had more high scoring areas and greater overall similarity than Maxent to the MCE outputs, suggesting, for this case study, it was the most appropriate SDM for aquaculture site selection. With suitable input data, a combined SDM and MCE model would overcome limitations of the individual approaches, allowing more robust planning and management decisions for aquaculture, other stakeholders and the environment.
... The process of weighting and scoring criteria entails assigning a weight to each criterion in accordance with its relative significance, followed by scoring each criterion based on its suitability [7,14]. Finally, spatial analysis and suitability mapping involve the integration of weighted and scored criteria to generate a suitability map that highlights areas suitable for aquaculture [7,15]. ...
... These studies have identified potential sites for a variety fish species, including Sparus aurata [22,27,28], a warm-water fish native to the Mediterranean Sea that is highly valued in the aquaculture industry due to its fast growth rate, high market demand, and adaptability to different environments. Other fish species for which potential farming sites have been identified include Rainbow trout (Oncorhynchus mykiss) [19], pangasius [15], carp [21], sturgeon [29], seabass (Dicentrarchus labrax) [22,27] and Tilapia, the latter of which has been the subject of three different studies [23,30,31]. Tilapia is a freshwater fish species that is widely farmed due to its fast growth rate and high adaptability. ...
... Moreover, the selection of aquaculture sites in various other ecosystems has been the subject of several reviewed papers. These include estuarine ecosystem aquaculture (3 studies) [20,35,36], as well as aquaculture in lakes [17], brackish water [26], lagoons [12], urban water bodies [21], and rivers [15]. ...
With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, geographic information system (GIS)-based multi-criteria evaluation (MCE) methods have emerged as the most widely utilized approach to identifying potential aquaculture sites. Following the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA), this paper presents a systematic review and meta-analysis of GIS-based MCE methods used in aquaculture sites selection. The objective of this study is to offer a comprehensive overview of existing research in this field and develop a general model for selecting sites for fish and shellfish aquaculture. The main findings indicate a growing number of studies utilizing GIS-based MCE in aquaculture site selection in recent years, with Asia being the leading continent in terms of publications in this domain. Among the journals publishing in this field, the Aquaculture journal stands out as the top publisher. Using consistent criteria across the reviewed studies, two models have been generated, each consisting of four sub-models: water quality, soil quality, infrastructure, and socioeconomic factors; and topography, environment, and physical parameters. These models can aid future researchers and assist decision-makers in identifying optimal locations for aquaculture development.
... Previously, Hossain et al. (2007Hossain et al. ( , 2009 , Hossain & Das (2010), and Nayak et al. (2014Nayak et al. ( , 2018 had used a threepoint scale to classify suitability, not including the "moderately suitable" category. On the other hand, Falconer et al. (2016) used a broader, five-point scale that included the "highly unsuitable" class. ...
... Giap et al. (2005) and Nayak et al. (2014Nayak et al. ( , 2018 considered highly suitable areas with a clay content superior to 35%, as suitable those with a clay content between 18 and 35%, and as slightly suitable or unsuitable as those sites with a clay content of less than 18%. The remaining studies proposed different scales of soil suitability based on the percentage of clay content (Ssegane et al. 2012, Nayak et al. 2014, 2018, Falconer et al. 2016, Assefa & Abebe 2018. ...
... The slope is a decisive and limiting factor for successfully implementing aquaculture ponds, influen-cing pond construction, drainage, retention, water runoff, soil movement, and erosion (Ono & Kubitza 2005, Hossain et al. 2007, Falconer et al. 2016. Flat, softly waved terrains (<5% slope) are usually preferred to avoid heavy excavation and construction works, facilitate pond drainage, and lower the risk of erosion (Ono & Kubitza 2005, Pereira & Silva 2012, Ssegane et al. 2012. ...
Remote sensing (RS) and geographic information systems (GIS) have been used to guide the selection of suitable areas for aquaculture. This systematic review synthesizes the key suitability factors and constraints reported in the literature for establishing inland pond aquaculture. We searched for primary studies on Scopus and Web of Science according to preferred reporting items for systemic reviews and meta-analysis (PRISMA) guidelines. Between 1991 and 2020, 354 articles were published in 104 academic journals. The maximum annual number of publications occurred in 2020, with 22 publications, and there is an increasing trend in studies published over the past 30 years. From 12 selected studies, we identified 48 suitability factors, 11 related to soil suitability, 19 to socioeconomic and infrastructure suitability, and 18 to water quality and availability. The most frequently used suitability factors were road proximity, local market center distance, soil texture, soil slope, and water temperature. We listed 15 constraints that restrict or limit the selection of specific geographic locations for inland aquaculture. Urbanized areas, roads, and forests were the most frequently restricted areas. Geotechnologies provide powerful tools for spatial planning and management of aquaculture. Availability, quality, and access to spatial data are critical for the use of geotechnologies in the process of aquaculture site selection.
... Therefore, we performed a literature review on frequently used criteria for aquaculture operation and siting. While most studies showed a clear focus on environmental criteria, some also incorporated social and economic parameters [34][35][36][37]. ...
... Proximity to water source [34,[36][37][38][39][40][41][42] Available area [38] Elevation [26,38,43] Slope [34][35][36][37]40,43,44] Geology and related criteria (e.g., pH) [34,36,40,45] Special river types (e.g., glacial river) [45,46] Land use/cover Land use [26,34,36,[40][41][42][43] Soil characteristics [26,[35][36][37]40,43,44] Legal constraints/ risks Protected areas [34,40,43,47] Competing uses [38,40,47] Natural hazards [43,47] Water quality/ quantity Water quality [37,40,43,45,47] Water temperature [34][35][36]40,45] Water quantity/availability [35,36,43,44] ...
... Proximity to water source [34,[36][37][38][39][40][41][42] Available area [38] Elevation [26,38,43] Slope [34][35][36][37]40,43,44] Geology and related criteria (e.g., pH) [34,36,40,45] Special river types (e.g., glacial river) [45,46] Land use/cover Land use [26,34,36,[40][41][42][43] Soil characteristics [26,[35][36][37]40,43,44] Legal constraints/ risks Protected areas [34,40,43,47] Competing uses [38,40,47] Natural hazards [43,47] Water quality/ quantity Water quality [37,40,43,45,47] Water temperature [34][35][36]40,45] Water quantity/availability [35,36,43,44] ...
Aquaculture is the fastest-growing animal food production sector and is expected to become increasingly important to meet future food demands. As a landlocked country, Austria’s self-sufficiency rate for fish is rather low with 6% in total and 48% for freshwater fish. Therefore, and in order to enable sustainable growth of the sector while avoiding negative impacts on the aquatic ecosystem and other uses, we developed aquaZone, a decision support tool for sustainable trout farm zoning. Thereby, 30 spatially explicit criteria related to environmental prerequisites, land use, legal constraints and water quality/quantity were defined, collected and classified according to their suitability for sustainable trout production. Criteria were combined in an integrative GIS-based modelling approach in order to perform the first countrywide and spatially-explicit zonation of suitable areas for aquaculture in Austria. Thereby, 7920 suitable areas with a mean size of 8.2 ha located in 1129 out of 5011 sub-basins (23%) were identified. The decision tree assigned the highest variable importance to water temperature, slope, agricultural unit, geology, nitrate retention capacity, fish region, minimum flow and pollution risk. These results should support decision making of investors and authorities in order to avoid conflicts and stranded investments at an early stage.
... Identifying available areas that are suitable has thus become a critical concern for supporting and expanding aquaculture [4]. Indeed, the importance of the site selection process has been widely recognized in recent reports and research publications [5,6]. ...
... Numerous studies have used geographic information systems (GIS) and multi-criteria evaluation (MCE) for aquaculture siting and demonstrate the integration of many different data layers covering the spectrum from physical to economic to social factors [6][7][8][9][10][11][12][13]. The majority of these studies approach siting as a one-time analysis that specifies fixed areas as suitable for aquaculture. ...
... GIS-based models that support the integration of multiple geospatial data sets have become goto tools for the analysis and identification of suitable site conditions. Nath et al. [7] were early advocates of GIS analysis for aquaculture siting and the use of GIS for aquaculture siting has continued to grow [6,8,[10][11][12][13][14][15]. These studies demonstrate the combination of a range of data sets reflecting the requirements of different species, culture systems, and local context compiled as spatial layers. ...
Aquaculture site selection, like most site suitability analyses, requires the assembly and combination of multiple variables. Geographic information systems GIS and multi-criteria evaluation (MCE) based approaches are commonly used for aquaculture site selection and demonstrate the integration of various information sources relevant for siting aquaculture. These analyses, however, tend to be one-time and result in a fixed site suitability plan. Within a dynamic marine environment experiencing potential regime shifts, a siting support tool that integrates new and evolving spatio-temporal data has benefits. This paper presents a flexible Voronoi cell-based GIS model for marine aquaculture siting. Rather than a one-time specification of suitable locations, the approach uses similarity measures on the characteristics of Voronoi cells to find cells with similar characteristics. We calculate a weighted aquaculture site tenure value for Voronoi cells that have been or are occupied by aquaculture farm sites. High scoring cells suggest suitable sites and serve as targets for similarity queries. We apply the approach to a case study on the coast of Maine using an R Shiny application to demonstrate the use of the framework for finding sites with similar characteristics.
... The identification of the potential area for aquaculture should be based on favorable criteria to allow the growth of species of interest [5]. These criteria were established by considering rainbow trout breeding manuals from Peru [36] and FAO [37], land suitability studies for rainbow trout aquaculture [17,18], aquaculture of other species [8,16,19,[24][25][26], and the criteria for aquaculture zoning set by the FAO [5,13]. The same ones that were validated for the planning process by a group of experts, made up of five fish farmers in the study area and six aquaculture specialists from the DIREPRO-A of the PRODUCE. ...
... The key advantages of MCE techniques are that they are well established for aquaculture zoning, they can combine multiple criteria (many more than those used in this study; [19,20,55]), and may develop models under different hierarchies, priorities, and scenarios [8]. However, the main problem in the analysis of land suitability for aquaculture in ponds dug in the soil, and in general for any activity, lies in the lack of spatial data of the criteria [16]. ...
... In Peru, and specifically in the region of Amazonas, these computing resources are scarce, even more so when it comes to specific studies of biological, environmental, and social criteria at detailed local scales. In view of this, it has been proposed to complement MCE techniques with Species Distribution Models (SDM) [8], such as Mahalanobis Typicity and MaxEnt [68]. Despite this being stated, no such approach was applied, because it depends on the georeferenced locations of the fish farms, and even though SDM such as MaxEnt has an extremely small sample size tolerance [69], it was considered inappropriate to use only the five farms, as it could affect the performance of the model. ...
Peruvian aquaculture, specifically trout production, has had significant growth over the past ten years. However, the establishment and expansion of small-scale aquaculture have been carried out without considering the suitability of the land. In Peru, such land suitability studies have yet to be reported. Therefore, a methodological framework is presented for inland aquaculture, which may be replicated, with the necessary complements, for the entire Fisheries and Aquaculture sector in Peru. This work modeled the suitability of land for sustainable rainbow trout aquaculture in the Molinopampa district (Peru). Fifteen key criteria (socioeconomic, environmental and physicochemical) were identified for the proper development of fish activity. These were mapped using Remote Sensing (RS) and Geographic Information Systems (GIS). The Analytical Hierarchy Process (AHP) was applied to build peer-to-peer comparison matrices and weight the importance of the criteria. The weighted overlay of maps (criteria) made it possible to determine that 4.26%, 23.03% and 69.73% of the territory is “very suitable”, “moderately suitable” and “marginally suitable”, respectively, for the development of aquaculture. The implementation of this methodology will contribute to more effective investment planning and efforts, both by the government and by private initiative.
... The identification of the potential area for aquaculture should be based on favorable criteria to allow the growth of species of interest [5]. These criteria were established by considering rainbow trout breeding manuals from Peru [36] and FAO [37], land suitability studies for rainbow trout aquaculture [17,18], aquaculture of other species [8,16,19,[24][25][26], and the criteria for aquaculture zoning set by the FAO [5,13]. The same ones that were validated for the planning process by a group of experts, made up of five fish farmers in the study area and six aquaculture specialists from the DIREPRO-A of the PRODUCE. ...
... The key advantages of MCE techniques are that they are well established for aquaculture zoning, they can combine multiple criteria (many more than those used in this study; [19,20,55]), and may develop models under different hierarchies, priorities, and scenarios [8]. However, the main problem in the analysis of land suitability for aquaculture in ponds dug in the soil, and in general for any activity, lies in the lack of spatial data of the criteria [16]. ...
... In Peru, and specifically in the region of Amazonas, these computing resources are scarce, even more so when it comes to specific studies of biological, environmental, and social criteria at detailed local scales. In view of this, it has been proposed to complement MCE techniques with Species Distribution Models (SDM) [8], such as Mahalanobis Typicity and MaxEnt [68]. Despite this being stated, no such approach was applied, because it depends on the georeferenced locations of the fish farms, and even though SDM such as MaxEnt has an extremely small sample size tolerance [69], it was considered inappropriate to use only the five farms, as it could affect the performance of the model. ...
Peruvian aquaculture, specifically trout production, has had significant growth over the past ten years. However, the establishment and expansion of small-scale aquaculture have been carried out without considering the suitability of the land. In Peru, such land suitability studies have yet to be reported. Therefore, a methodological framework is presented for inland aquaculture, which may be replicated, with the necessary complements, for the entire Fisheries and Aquaculture sector in Peru. This work modeled the suitability of land for sustainable rainbow trout aquaculture in the Molinopampa district (Peru). Fifteen key criteria (socioeconomic, environmental and physicochemical) were identified for the proper development of fish activity. These were mapped using Remote Sensing (RS) and Geographic Information Systems (GIS). The Analytical Hierarchy Process (AHP) was applied to build peer-to-peer comparison matrices and weight the importance of the criteria. The weighted overlay of maps (criteria) made it possible to determine that 4.26%, 23.03% and 69.73% of the territory is “very suitable”, “moderately suitable” and “marginally suitable”, respectively, for the development of aquaculture. The implementation of this methodology will contribute to more effective investment planning and efforts, both by the government and by private initiative.
... Following participatory and ecosystem approaches, based on environmental, economic and social factors, it is possible to select the most suitable sites for aquaculture, optimized for recruitment and growth and allow maximizing cost-efficiency of production, while minimizing environmental threats and avoiding potential conflicts with other ecosystem users (Dapueto et al., 2015;Aguilar-Manjarrez et al., 2017;Gentry et al., 2017). Application of GIS-based approaches for aquaculture planning has been discussed in a number of studies (Arnold et al., 2000;Nath et al., 2000;Longdill et al., 2008;Radiarta et al., 2008;Hossain and Das, 2010;Silva et al., 2011;Cho et al., 2012;Liu et al., 2014;Dapueto et al., 2015;Falconer et al., 2013Falconer et al., , 2016Gimpel et al., 2015), some specifically addressing bioremediation-oriented aquaculture (e.g. Silva et al., 2012). ...
... Dapueto et al., 2015;Sanchez-Jerez et al., 2016) it should be a subject of marine spatial planning for designating suitable sites. The key advantage of the applied GIS and MCE approach for this purpose is a combination of multiple biological, environmental and socio-economic criteria within the same site selection framework and ability to define spatial models with specified priorities and scenarios to support decision makers and stakeholders (Falconer et al., 2016). The specific novelty of the approach presented here is in application of spatial suitability modeling to utilize selected biological traits of established and well-studied invasive species for water quality remediation. ...
... In the course of MCE, a number of sequential steps requiring data reclassification, weighting and defining overall model structure can affect the outcomes of the analyses. Although based on scientific evidence and expert knowledge, assigned classes and weighting values often remain subjective, therefore universal accepted scores and weights rarely exist (Falconer et al., 2016). In this study, criteria evaluation by four experts always resulted in a larger weight attributed to one or two criteria (out of 3-4) included into the model. ...
Farming of shellfish and seaweeds is a tested tool for mitigating eutrophication consequences in coastal environments, however as many other marine economic activities it should be a subject of marine spatial planning for designating suitable sites. The present study proposes site selection framework for provisional zebra mussel farming in a eutrophic lagoon ecosystem, aimed primarily at remediation purposes. GIS-based multi-criteria approach was applied, combining data from empirical maps, numerical models and remote sensing to estimate suitability parameters. Site selection and prioritisation of suitable areas considered 15 environmental and socio-economic criteria, which contributed to 4 optimisation models (settlement, growth and survival of mussels, environmental and socio-economic) and 3 predefined scenarios representing provisional goals of mussel cultivation: spat production, biomass production and bioremediation. The relative importance of each criterion was assessed utilizing the Analytical Hierarchy Process. Site suitability index was calculated and the final result of the site selection analysis was summarized for 3 scenarios and overall suitability map. Four suitability classes (unsuitable, least, moderately and most suitable) were applied, and 3 most suitable zones for provisional zebra mussel cultivation with 12 candidate sites were selected accordingly. The integrated approach presented in this study can be adjusted for designating zebra mussel farming sites in other estuarine lagoon ecosystems, or cultivation of other mussel species for bioremediation purposes. The analytical framework and the workflow designed in this study are also adoptable for addressing other aquaculture-related spatial planning issues.
... Some GIS software have modules dedicated to MCE, which also include modules to calculate weights. The MCE approach is commonly used for aquaculture site selection studies (e.g., Nath et al., 2000;Pérez et al., 2005;Ross et al., 2011;Falconer et al., 2016). GIS can be used to support assessment and management of all four categories of carrying capacity (Aguilar-Manjarrez et al., 2010; Ross et al., 2013). ...
... Spatial site selection models are extremely useful in such circumstances as they can be used to assess the suitability of the entire catchment, identifying the most suitable areas, which can be then targeted for more site-specific assessment of carrying capacity. Falconer et al. (2016) evaluated the suitability of the Mekong Delta for pangasius ponds while comparing two different approaches to site selection within a GIS. ...
... However, the MCE approach requires data reclassification and weighting within a model structure, which can often be a source of conflict and uncertainty as there is not always a "correct" way to do this. Falconer et al. (2016) investigated another approach, using "species distribution models" (SDMs), which are used in ecology to predict the probable spatial distribution of a species across a study area. SDMs assess the selected variables at the location of the input points and then interpolate the analysis across the whole study area to identify further areas that have similar conditions. ...
There has been a rapid development and deployment of geographical information systems (GIS) in recent years in response to a burgeoning range of increasingly complex spatial management questions. Although GIS has been investigated for aquaculture support and actively promoted over the last 30 years, its use in the sector has been taken up rather slowly. However, its adoption has now increased to the point where agencies expect it to be used in project planning, and it often takes a central role in scenario modeling. GIS models can be used to great advantage for both management and research within the sector, and this article shows how GIS models and model assemblies are essentially expert systems based around a spatial database which provides a virtual environment. A wide range of modeling approaches that can be applied to aquaculture problems are illustrated.
... Along with the innovation of sustainable aquaculture technology and artificial breeding, aquaculture mapping, as an important part of industry management, is urgently needed. (Falconer et al. 2016). The GIS-based multi-criteria evolution (MCE) combines multiple variables into a structured model and can provide a holistic overview of multiple criteria (Fig. 14.4). ...
... For example, SDM was applied to investigate whether the Gulf of Maine is suitable for the edible brown algae Alaria esculenta, and these regions identified as environmentally suitable provided fundamental information for the next socioeconomic analysis (Resnick 2020). Falconer et al. (2016) found that the method combining SDM with MCE models would be more reliable. For examining the potential suitable habitats of Manila clam (Ruditapes philippinarum) in Moon Lake, China, an ensemble-modeling approach was implemented in the biomod2 platform. ...
The development of aquaculture is facing unprecedented pressures from climate change, resource constraints, environmental pollution, energy consumption, and other factors. For coping with these challenges and for ensuring sustainable development of aquaculture, spatial planning in aquaculture activities become more and more important. An ecosystem-based approach for aquaculture mapping is needed to strategically and comprehensively balance the location, aquaculture type, and stakeholders’ interests. In this chapter, we aim to describe the definition, key steps, and methods of aquaculture zoning, especially in the context of climate change (e.g., global warming, ocean acidification, hypoxia/anoxia, sea level rising, and extreme events). We also provide two case studies of aquaculture mapping in China.
... Along with the innovation of sustainable aquaculture technology and artificial breeding, aquaculture mapping, as an important part of industry management, is urgently needed. (Falconer et al. 2016). The GIS-based multi-criteria evolution (MCE) combines multiple variables into a structured model and can provide a holistic overview of multiple criteria (Fig. 14.4). ...
... For example, SDM was applied to investigate whether the Gulf of Maine is suitable for the edible brown algae Alaria esculenta, and these regions identified as environmentally suitable provided fundamental information for the next socioeconomic analysis (Resnick 2020). Falconer et al. (2016) found that the method combining SDM with MCE models would be more reliable. For examining the potential suitable habitats of Manila clam (Ruditapes philippinarum) in Moon Lake, China, an ensemble-modeling approach was implemented in the biomod2 platform. ...
Agricultural practice of the world in last decades has proved that simplistic intensification of agriculture systems has paid high prices while increasing crop production and production efficiency. Therefore, sustainable intensification should be a pattern for the development of aquaculture. The goal of sustainable development of aquaculture systems can be achieved through the ecological intensification, that is, integrating anthropogenic inputs with aquaculture ecosystem services. This chapter will introduce the multidimensionality of aquaculture systems, and the relationships of intensification degree with economic efficiency and ecological footprints, so that we can better understand the sustainability of aquaculture systems and the future development pattern of aquaculture industry.
... Site suitability selection was conducted using MCDM derived from the Elimination by Aspects method (see Tversky 1972 andHwang andYoon 1981). MCDM has been employed in several aquaculture/agriculture site selection studies (e.g., Perez, Telfer, and Ross 2005;Falconer, Telfer, and Ross 2016;Talukder et al. 2017;Bagdanavičiūtė et al. 2018) though not necessarily using Elimination by Aspects. For instance, Perez, Telfer, and Ross 2005 used "weighted linear combination" methods (see Barredo 1996) for offshore site selection around Tenerife, Canary Islands for the farming of seabream (Sparus aurata) in floating pens. ...
... Many of the other examples also differentially weigh criteria in their MCDM approach such as the use of Analytic Hierarchy Process (Saaty 1980) and Weighted Linear Combination (Malczewski 2000) in Bagdanavičiūtė et al. (2018)'s site assessment for Zebra Mussels (Dreissena polymorpha) in the Baltic Sea. Analytic Hierarchy Process was again used by Falconer, Telfer, and Ross (2016) for site selection of Pangasius farms in the Mekong Delta. The use of Elimination and Choice Translating Reality (ELECTRE) methods were used by Abdullah et al. (2022) for general aquaculture site selection in peninsular Malaysia. ...
Site selection is the foundation of sustainable finfish culture, and in the tropics, there are vast offshore areas where this is needed. This study is the first to identify areas for marine finfish culture along the North Borneo West Coast using outputs from hydrodynamic modeling coupled with GIS and Multiple-Criteria Decision Making Analysis. Site selection criteria included: water depth, current speed, significant wave height, sensitive habitats, reported fishing grounds, government-based exclusion zones, oil & gas consents, and navigation routes. Of an initial 2.55 million ha, 1.05 million ha was eliminated from consideration based on physical characteristics alone. Of the 1.50 million ha identified to satisfy physical and hydrodynamic criteria for surface-oriented farms, a further 0.06 million ha was eliminated due to sensitive habitat and government exclusion zones. The remaining 1.44 million ha was found suitable for surface pen farming and 0.61 million ha for submerged pen farming. Much of this potential area is shared with capture fishery grounds, oil & gas consents, and navigation routes that will require further assessments (e.g. EIAs) to determine specific impacts to those industries. Those areas not in multi-user conflict makes up 0.57 million ha and 0.28 million ha for surface and submerged farms respectively.
... The criteria for SFM are determined by a combination of the mangrove rehabilitation conditions and affected factors of shrimp growth. Based on a literature survey (Assefa & Abebe, 2018;Calle Yunis et al., 2020;Falconer et al., 2020;Falconer et al., 2016;Francisco et al., 2019;Khiem et al., 2020), three criteria and 19 sub-criteria are selected for the assessment of conditions. These conditions include geographical locations, water quality, soil characteristics, tide and climate, soil salinity, land use-land cover and social factors (Hossain et al., 2009). ...
... The suitability of the criteria is classified as per FAO method in four levels: highly suitable, moderately suitable, marginally suitable, and not suitable with the score of 4, 3, 2, 1, respectively (Aguilar-Manjarrez et al., 2010;Assefa & Abebe, 2018;Ross et al., 2013;Tuyen et al., 2019). Independent evaluations of each criterion/sub-criterion contribution that has been applied and developed have been done in many studies by researchers (Calle Yunis et al., 2020;Falconer et al., 2013;Falconer et al., 2016;Sari et al., 2020;Teixeira et al., 2018). In this study, two hierarchies and a pair of criteria were compared, and sub-criteria were implemented. ...
This study was conducted to identify suitable sites for shrimp farming combined with the mangrove development (SFM) in the coastal area of central Vietnam. An integrated approach using GIS with weighted Multi-Criteria Evaluation (MCE) by Analytic Hierarchy Process (AHP) was adopted for the selection of sites. In this study, fifteen sub-criteria belonging to three main criteria (geographical conditions, water quality and infrastructure availability) were selected as evaluation parameters in the GIS model. The study indicated that the geographical factors are the most important for the SFM development with 0.44 weight. However, the availability of such areas is limited. Results of the integrated study indicated that SFM area for development is highly suitable: 1127.82 ha (15.57%), moderately suitable: 2056.87 ha (28.4%), marginally suitable: 2835.52 ha (39.16 %) and not suitable: 3204.36 ha (17.0 %) in the Hau basin, Vietnam. In this study, we have also used GIS-AHP-MCE methods for developing organic shrimp farming and mangrove rehabilitation.
... In bathymetry, a fuzzy image in indexes 6764 and 6763 had the lowest utility levels of 45 and 62. Bathymetry results correspond with the results of distance to the coastline and seabed slope. The maximum amount of wave height and wind speed were, respectively, 4 to 5 m and 16 to 27 m/s according to the studies by References [26,33]. The east and west coast indexes had less suitability since the wave height and wind speed were more than optimal in central indexes 6263, 6364, and 6463. ...
... The east and west coast indexes had less suitability since the wave height and wind speed were more than optimal in central indexes 6263, 6364, and 6463. Based on previous studies, the optimal seabed slope for marine aquaculture was 0.5% to 2% [16,25,26]. In indexes 6663, 6664, 6763, and 6764, the seabed slope was less than 0.2% on the east coast and Gorgan Bay and it began to increase toward the west coast. ...
Fish consumption is on the increase due to the increase in growth of the global population. Therefore, taking advantage of new methods such as marine aquaculture can be a reliable source for the production of fish in the world. It is necessary to allocate suitable sites from environmental, economic, and social points of view in the decision-making process. In this study, in order to specify suitable areas for marine aquaculture by the Ordered Weighted Averaging (OWA) methodology in the Caspian Sea (Iran), efforts were made to incorporate the concept of risk into the GIS-based analysis. By using the OWA-based method, a model was provided which can generate marine aquaculture maps with various pessimistic or optimistic strategies. Eighteen modeling criteria (14 factors and 4 constraints) were considered to determine the appropriate areas for marine aquaculture. This was done in 6 scenarios using multi-criteria evaluation (MCE) and ordered weighted average (OWA) methodologies. The results of the sensitivity analysis showed that most of the parameters affecting the marine aquaculture location in the region were as follows: Social-Economic, Water Quality, and Physical-Environmental parameters. In addition, based on Cramer's V coefficient values for each parameter, bathymetry and distance from the coastline with the most effective and maximum temperature had the least impact on site selection of marine aquaculture. Finally, the final aggregated suitability image (FASI) of weighted linear combination (WLC) scenario was compared with existing sites for cage culture on the southern part of the Caspian Sea and the ROC (Relative Operating Characteristics) value turned out to be equal to 0.69. Although the existing sites (9 farms) were almost compatible with the results of the study, their locations can be transferred to more favorable areas with less risk and the mapping risk level can be controlled and low-or high-risk sites for marine aquaculture could be determined by using the OWA method.
... Distance to the city and distance to roads are important for any successful aquaculture operation, ensuring access, supply, and marketing markets (Falconer et al. 2013;Falconer et al. 2016). They are determined based on the distance calculation (Falconer et al. 2016;Gimpel et al. 2018;Vianna and Filho 2018), particularly the Euclidean distance (Vianna and Filho 2018). ...
... Distance to the city and distance to roads are important for any successful aquaculture operation, ensuring access, supply, and marketing markets (Falconer et al. 2013;Falconer et al. 2016). They are determined based on the distance calculation (Falconer et al. 2016;Gimpel et al. 2018;Vianna and Filho 2018), particularly the Euclidean distance (Vianna and Filho 2018). ...
The development of marine fish farming on the Algerian coast is facing a number of environmental and logistical constraints. In a multi-disciplinary approach, based on aquaculture activity planning and field validation, the aim of this study is to target suitable areas for the setting of floating cages for Sparus aurata breeding at the Bay of Souahlia, Algeria. Multi-criteria evaluation via GIS was applied, combining 3 sub-models (environmental, socioeconomic, and constraint sub-models). The field verification was carried out on El Mokretar Aqua farm, by comparing its position with the result of the multi-criteria evaluation and by studying the growth performance indicators, thermal unit growth coefficient, specific growth rate, and feed conversion ratio and biomass. The regeneration of the final suitability map allowed for the delimitation of the favorable area for the implantation of the floating cages, which corresponds to 32% of the total area, with 3 classes of suitability. The El Mokretar Aqua farm is located at station S11, with a significant relevance index of 0.69. The gilthead seabream reflects a good growth performance. It grows with an average weight of 5 to 305 g over a 306-day rearing period, due to the environmental conditions and the good management of the farm.
... Site selection is a crucial process that is "not only for economic benefit, but also the sustainability, reputation and longevity of an… industry as a whole" [3]. Therefore, the process not only supports the long-term sustainability of radioactive waste management activities, but also nuclear power generating programs. ...
... Stochastic simulations of regional scale advective transport in fractured rock masses using block upscaled hydro-mechanical rock property data. Journal of Hydrology (Amsterdam), 369 (3)(4), 318-325;Chen, et. al., (2015) propose a new rock mass classification system named "QHLW" system for evaluating the suitability of the host rock for HLW disposal. ...
The report may be accessed via: https://www.gov.uk/government/publications/accelerating-implementation-of-a-geological-disposal-facility-in-the-united-kingdom
... To date, models of aquaculture impacts have focused primarily on the processes of waste generation, deposition, and accumulation ( [5,12,[14][15][16][17][18]; see also a recent review by Falconer et al., [17]). Much less effort has gone into modeling the decomposition and remineralization of fish farm waste, and the impacts of fish farm emissions on biogeochemical cycles (e.g., eutrophication) either in the sediments (e.g., Reference [18]) or in the water column [19][20][21]. ...
... To date, models of aquaculture impacts have focused primarily on the processes of waste generation, deposition, and accumulation ( [5,12,[14][15][16][17][18]; see also a recent review by Falconer et al., [17]). Much less effort has gone into modeling the decomposition and remineralization of fish farm waste, and the impacts of fish farm emissions on biogeochemical cycles (e.g., eutrophication) either in the sediments (e.g., Reference [18]) or in the water column [19][20][21]. ...
Sustainable development of the salmon farming industry requires knowledge of the biogeochemical impacts of fish farm emissions. To investigate the spatial and temporal scales of farm impacts on the water column and benthic biogeochemistry, we coupled the C-N-P-Si-O-S-Mn-Fe transformation model BROM with a 2-dimensional benthic-pelagic transport model (2DBP), considering vertical and horizontal transport in the water and upper 5 cm of sediments along a 10 km transect centered on a fish farm. The 2DBP model was forced by hydrophysical model data for the Hardangerfjord in western Norway. Model simulations showed reasonable agreement with field data from the Hardangerfjord in August 2016 (correlations between the model and observations were significant for most variables, and model biases were mostly <35%). The model predicted significant impacts on seafloor biogeochemistry up to 1 km from the fish farm (e.g., increased organic matter in sediments, oxygen depletion in bottom water and sediments, denitrification, metal and sulfur reduction), as well as detectable decreases in oxygen and increases in ammonium, phosphate and organic matter in the surface water near to the fish farm.
... According to De Oliveira et al. (2016), earthmoving costs and adaptation of areas are some of the biggest obstacles for producers in small municipalities to implement a fish farming system in excavated ponds. The municipality of Pato Bragado has a relatively undulating slope, which makes up a large part of its territory (51.88%) and does not require high costs for the implementation of excavated ponds due to the low slope because in addition to the influence it exerts on the construction of improvements also affects drainage, water runoff, soil movement/erosion and the water retention rate (Falconer et al. 2016) tampering with natural drainage and placing the site under the direct effect of erosion according to Pereira & Silva (2012) and Ssegane et al. (2012). The study area has a flat slope and does not require heavy machinery to implement structures for aquaculture activities. ...
Using geotechnologies has become fundamental for planning the sustainable expansion of agricultural activities, especially fish farming. The objective of this work was to map and carry out the morphological characterization of the hydrographic micro-basins and their physical aspects, such as slope, altimetry, and land use and occupation, and also to quantify and locate the existing excavated ponds in the municipality of Pato Bragado, in Paraná State. Geotechnology tools and images generated by the free software QGIS and Google Earth were used to create maps of the excavated ponds' physical aspects, quantification, classification, and location. The predominant slope in the municipality is gently undulating, and soy plantation uses 42.99% of the municipality's entire area. The mapping located 190 excavated ponds. Depth measurement was not carried out, but rather mapping concerning water depths representing a total area of 47.86 ha of water blade and nine micro-basins within the municipality of Pato Bragado, with only the Arroio Fundo micro-basin covering 47.37% of all existing excavated ponds. The morphometric indicators concluded that the micro-basins present a minimum risk of flooding, which is ideal for use in fish farming. Making the results of this work available to public managers and fish farmers aims to demonstrate the importance of using geotechnologies for sustainable planning to expand aquaculture activities, which, in this case, are focused on fish farming.
... O método de análise hierárquica multicritério (AHP) foi utilizado no presente trabalho, pois permite ao usuário atribuir pesos para múltiplos atributos ou que seja atribuído múltiplas alternativas a um determinado atributo ao mesmo tempo que ocorre uma comparação pareada entre eles (Saaty, 1990). Assim, os critérios foram ponderados a partir da criação de um procedimento de pontuação e reclassificação, possibilitando estabelecer e avaliar cada critério na abordagem de estudo, conforme as seguintes indicações: 4 = totalmente adequado, 3 = adequado, 2 = pouco adequado e 1 = muito pouco adequado (Falconer et al., 2016). Na Tabela 2 é possível visualizar cada critério com suas respectivas pontuações. ...
Para subsidiar a gestão o uso sustentável de uma área, a identificação dos ambientes naturais e suas fragilidades potenciais e emergentes, contribuem para uma melhor definição das diretrizes e ações a serem efetivadas no espaço físico-territorial. O objetivo deste trabalho é avaliar o potencial de adequação das terras em região do nordeste do Estado do Pará para a implantação de empreendimentos de piscicultura com a utilização de viveiros escavados, a partir da definição de cinco critérios: declividade, altitude, solos, proximidade de estradas e uso e cobertura da terra. Os dados foram adquiridos de fontes oficiais e integrados em um ambiente de Sistema de Informações Geográficas (SIG). Com a utilização da Análise Hierárquica Multicritério (AHP) foi possível atribuir pontuações para os critérios e integrá-los em uma matriz de comparação pareada para obtenção dos pesos de cada um dos critérios definidos.
... The physio-chemical parameters of water affecting shrimp diseases include Chemical Oxygen Demand (COD) (Fig. 2a), Dissolved Oxygen (DO) (Fig. 2b), temperature (Khiem et al. 2020). In addition, salinity (Fig. 2c) has a great impact on the health and growth of the shrimp (Falconer et al. 2016). Besides, spatial factors such as distance to the roads (access and transport networks) (Fig. 2h) and distance to factory (including hatchery and medicine) influence the shrimp farming (Fig. 2d) (Giap et al. 2005). ...
Recently, the spread of white spot disease in shrimps has a major impact on the aquaculture activity worldwide affecting the economy of the countries, especially SouthEast Asian countries like Vietnam. This deadly disease in shrimps is caused by the White Spot Syndrome Virus (WSSV). Researchers are trying to understand the spread and control of this disease by doing field and laboratory studies considering effect of environmental conditions on shrimps affected by WSSV. Generally, they have not considered spatial factors in their study. Therefore, in the present study, we have used spatial (distances to roads and factories) as well as physio-chemical factors of water: Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), Salinity, NO 3 , P 3 O 4 and pH, for developing WSSV susceptibility maps of the area using Decision Tree (DT)-based Machine Learning (ML) models namely Random Tree (RT), Extra Tree (ET), and J48. Model's performance was evaluated using standard statistical measures including Area Under the Curve (AUC). The results indicated that ET model has the highest accuracy (AUC: 0.713) in predicting disease susceptibility in comparison to other two models (RT: 0.701 and J48: 0.641). The WSSV susceptibility maps developed by the ML technique, using DT (ET) method, will help decision makers in better planning and control of spatial spread of WSSV disease in shrimps.
... In order to meet the demand for scrumptious fish produce, dependency on capture fisheries will not only overburden the resource but also have deleterious impact on the environment (Falconer et al., 2016;Gimpel et al., 2018;Gameiro et al., 2022). Inland fisheries and aquaculture are growing tremendously in the last two decades due to the diverse nature of fisheries resources (Aura et al., , 2019. ...
The study aimed to assess land suitability for sustainable aquaculture development in Muzaffarpur, Bihar, India, utilising a multi-criteria decision analysis (MCDA) and GIS-based approach. In India, issues such as water and soil degradation, insufficient infrastructure and inadequate maintenance pose significant challenges to aquaculture growth. The research employed 15 base layers, including water quality, soil characteristics, engineering parameters and high-resolution satellite imagery, analysed through the Analytical hierarchy process (AHP) and GIS-based multi-criteria evaluation. Results revealed 9.85% highly suitable and 35.09% unsuitable areas for fish farming, achieving an 80% overall accuracy through validation with satellite images and field visits. The study provides valuable insights for policy makers, farmers, and resource managers in selecting suitable sites for sustainable aquaculture, enhancing resource management in the region.
... The physio-chemical parameters of water affecting shrimp diseases include Chemical Oxygen Demand (COD) (Fig. 2a), Dissolved Oxygen (DO) (Fig. 2b), temperature (Khiem et al. 2020). In addition, salinity (Fig. 2c) has a great impact on the health and growth of the shrimp (Falconer et al. 2016). Besides, spatial factors such as distance to the roads (access and transport networks) (Fig. 2h) and distance to factory (including hatchery and medicine) influence the shrimp farming (Fig. 2d) (Giap et al. 2005). ...
Recently, the spread of white spot disease in shrimps has a major impact on the aquaculture activity worldwide affecting the economy of the countries, especially SouthEast Asian countries like Vietnam. This deadly disease in shrimps is caused by the White Spot Syndrome Virus (WSSV). Researchers are trying to understand the spread and control of this disease by doing field and laboratory studies considering effect of environmental conditions on shrimps affected by WSSV. Generally, they have not considered spatial factors in their study. Therefore, in the present study, we have used spatial (distances to roads and factories) as well as physio-chemical factors of water: Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), Salinity, NO 3 , P 3 O 4 and pH, for developing WSSV susceptibility maps of the area using Decision Tree (DT)-based Machine Learning (ML) models namely Random Tree (RT), Extra Tree (ET), and J48. Model's performance was evaluated using standard statistical measures including Area Under the Curve (AUC). The results indicated that ET model has the highest accuracy (AUC: 0.713) in predicting disease susceptibility in comparison to other two models (RT: 0.701 and J48: 0.641). The WSSV susceptibility maps developed by the ML technique, using DT (ET) method, will help decision makers in better planning and control of spatial spread of WSSV disease in shrimps.
... The sustainable planning of aquaculture must necessarily take into account many factors useful for an adequate zoning of this activity in coastal-marine environment. In this sense, the amount and heterogeneity of information that needs to be integrated to assess the suitability of a marine area require the use of tools that support the analysis of the several layers, such as geographic information systems (GIS) (Falconer et al., 2016;Ghobadi et al., 2021;Hossain et al., 2007;Jayanthi et al., 2022;Shunmugapriya et al., 2021;Silva et al., 2011;Wu et al., 2020;Yunis et al., 2020). ...
An efficient and adaptive strategy within the EU Marine Spatial Planning Directive has to manage the existing and increasing conflicts between human uses and habitat conservation in coastal-marine areas. Among the different human activities developed along the coasts, aquaculture occupies a primary role. In this context, the aims of this research have been: (1) to propose a conceptual model suitable for aquaculture marine spatial planning; (2) to collect and integrate indicators useful for the characterization of the study area in terms of socio-ecological-economic sensitivities and pressures; and (3) to identify and map the most suitable areas for the development of new fish and shellfish farms. The study area is the Apulia Region (Southern Italy) with a coastline of about 1,000 km, in the Adriatic and Ionian Seas, and characterized by several economic activities within a high value natural context. The evaluation of area’s suitability for fish and shellfish farms have been carried out through the ecological characterization of the coastal areas, the identification of the socio-economic, ecological, cultural, and legal-military constraints and the estimate of the “Suitability Index” that, through a Weighted Linear Combination, integrates environmental variables and allows to classify areas as “Highly Suitable”, “Suitable” or “Unsuitable”. The “highly suitable areas” for new fish and shellfish farms are mainly located in northernmost of the Southern Adriatic Sea along the Gargano coast and in the Gulf of Manfredonia, whilst concerning the Northern Ionian Sea they are at a mean distance of 5 Km from the shoreline. The suitability maps have shown that existing fish farms are in line with their suitable areas but, surprisingly, this has seemed not to be true for shellfish farms. This can be explained by the fact that these aquaculture activities have traditionally been present in some areas (e.g., Taranto Seas), currently strongly impacted by human activities. This research has highlighted that despite aquaculture is generally conceived as an environmental impacting activity, it could be also impacted by other environmental and/or anthropic stressors (i.e., industrial ports, sewage discharges). Considering all these elements, the present research addresses decision-makers, providing information and tools necessary to plan in a more aware way, and also stakeholders interested in investing in the aquaculture sector, who could benefit from the proposed suitability maps for fish and shellfish farms for a sustainable development of this sector.
... As one of the most common methods for site selection, the GIS-based Multi-Criteria Evaluation (MCE) can provide a comprehensive overview of suitable areas for macroalgae aquaculture by combining physical, economic, and socio-ecological factors (Galappaththi et al., 2020;Padmanaban and Sudalaimuthu, 2012). In addition, the correlative species distribution models (SDMs) are regarded as a reliable method for site selection by integrating observations of species occurrence with environmental variables (Falconer et al., 2016;Yu et al., 2022). Recently, the combination of correlative SDMs and physiological traits can provide more robust predictions Martínez et al., 2015) . ...
Macroalgae aquaculture faces grand challenges from extreme temperature events in the context of global warming. For mapping aquaculture areas and assessing potential risks, it is urgent to evaluate the thermal sensitivity of commercially and ecologically important macroalgae. In the present study, thermal tolerance of
commercial macroalgae species in China and sea surface temperature (SST) under current conditions and three Shared Socioeconomic Pathways (SSP1–2.6, SSP3–7.0, SSP5–8.5) scenarios in 2050 were collected for calculating thermal safety margin (TSM), an index of thermal sensitivity, for each species in the aquaculture area. Our results indicated that a few species were particularly sensitive to current conditions, and the kelp Saccharina japonica and Ulva pertusa were the most sensitive species to heat and cold stress, respectively. As indicated by the
regional thermal sensitivity (RTS) (i.e., the mean of TSMs for all species in each grid cell), the commercial macroalgae located in southern China (20–25◦N) were more sensitive to heat stress, while the commercial macroalgae located in the regions of 27–40◦N was more sensitive to cold stress. Commercial macroalgae nearby the Yangtze River Estuary (~30◦N) were sensitive to both heat and cold stress. Under the three SSP scenarios,
macroalgae aquaculture would be more sensitive to heat stress, and the impacts from cold stress would relatively weaken in 2050. Our findings provide crucial information for the management of macroalgae aquaculture and for climate change mitigation and adaptation in China.
... In short, the whole site selection process depends on three basic points viz., species to be farmed, the scale of production and supporting infrastructure. Site selection methodology for costal shrimp farming using several tools have been studied in the past by several authors and can be employed for selection of suitable coastal sites (Islam et al., 1987, Salam andRoss, 2000;Mahalakshmi and Ganesan, 2009;Falconer et al., 2016). ...
Shrimp farming is a major economic activity in India that is contributing immensely to the foreign exchange earnings. However, shrimp farming is science based and technical knowledge is imperative for successful operation.
... Due to this, we have determined the weights by thinking logically, debating scientifically and applying our acquired experiences and expertise on different parameters while judging the various criteria. In most cases, the weights and scores given to the factors were not unanimously agreed upon (Falconer et al. 2016). Thus, onsite feasibility was taken into account while finalising the weighing system. ...
In light of India's extensive cold-water resource base, cold-water fish farming, particularly for rainbow trout, is one of the country's most promising industries. The output potential has not yet been fully realised, despite the recent increase in production. To expand horizontally, the conventional technique is used, which opens up the possibility for more cross-sectoral conflicts to escalate. Thus, a geographic information system (GIS)-based model has been designed for rainbow trout aquaculture in Tawang, Arunachal Pradesh, India, considering the wise and sustainable utilisation of cold-water resources. Fourteen critical criteria were identified for site selection based on topography, water quality, and infrastructure facilities. Analytical hierarchical process (AHP) was used to create sensitive enough peer-to-peer comparison matrices for the selection process, allowing each criterion to be given a specific weight. Data from the Shuttle Radar Topography Mission (SRTM DEM-30 m) satellite were analysed for elevation and slope characteristics. Landsat 8 (OLI) data were employed to classify the current land use pattern. Based on a field survey and secondary data, the GPS locations of infrastructure facilities, like marketplaces, hatcheries, etc., were marked to delineate them. Using a geographical information system–multi-criteria evaluation (GIS–MCE) approach based on a weighted map overlay, we found that 0.14% (340.21 ha), 0.77% (1810.98 ha) and 0.02% (50.70 ha) of the region is most suitable, moderately suitable and least suitable, respectively, for rainbow trout farming. This model will facilitate the equitable distribution of available resources and give policymakers and other interested parties a common ground to build practical plans for the growth of cold-water aquaculture in the region.
... In the literature, MCE and SDM have been integrated to determine suitable areas for sustainable aquaculture [24], priority areas for archaeological site protection [25], priority areas for species conservation [26] and vulnerable areas within a protected area [23]. However, there is no evidence of integrated modeling (AHP and MaxEnt) on land suitability for sustainable cocoa or other agricultural crop farming [27]. ...
Peru is one of the world’s leading exporters of cocoa beans, which directly impacts the household economy of millions of small farmers. Currently, the expansion and modernization of the cocoa-growing area require the zoning of the territory with suitable biophysical and infrastructural conditions to facilitate optimizing productivity factors. Therefore, we analyzed land suitability for cocoa (Theobroma cacao L.) production on the Peruvian mainland as a support measure for sustainable agriculture. To this end, the climatological, edaphological, orographic, and socioeconomic criteria determining sustainable cocoa cultivation were identified and mapped. Three modeling approaches (Analytic Hierarchy Process—AHP, Maximum Entropy—MaxEnt, and AHP—MaxEnt combined) were further used to hierarchize the importance of the criteria and to model the potential territory for sustainable cocoa cultivation. In all three modeling approaches, climatological criteria stood out among the five most important criteria. Elevation (orographic criteria) is also featured in this group. On the other hand, San Martin and Amazonas emerged as the five regions with the largest area ‘Highly suitable’ for cocoa cultivation in all three modeling approaches, followed by Loreto, Ucayali, Madre de Dios, Cusco, Junín, and Puno, which alternated according to modeling approach. From most to least restrictive, the AHP, MaxEnt, and AHP–MaxEnt modeling approaches indicate that 1.5%, 5.3%, and 23.0% of the Peruvian territory is ‘Highly suitable’ for cocoa cultivation, respectively.
... SDMs can be reliable tools for selecting potential offshore aquaculture areas (Beard et al. 2020;Falconer et al. 2016). Previous studies have confirmed that SDMs were useful for identifying suitable aquaculture sites for farming Manila clam (Ruditapes philippinarum) (Dong et al. 2020) and for identifying the suitable locations for seaweeds aquaculture in the Spencer Gulf, South Australia (Wiltshire and Tanner 2020). ...
Unlabelled:
Mariculture has been one of the fastest-growing global food production sectors over the past three decades. With the congestion of space and deterioration of the environment in coastal regions, offshore aquaculture has gained increasing attention. Atlantic salmon (Salmo salar) and rainbow trout (Oncorhynchus mykiss) are two important aquaculture species and contribute to 6.1% of world aquaculture production of finfish. In the present study, we established species distribution models (SDMs) to identify the potential areas for offshore aquaculture of these two cold-water fish species considering the mesoscale spatio-temporal thermal heterogeneity of the Yellow Sea. The values of the area under the curve (AUC) and the true skill statistic (TSS) showed good model performance. The suitability index (SI), which was used in this study to quantitatively assess potential offshore aquaculture sites, was highly dynamic at the surface water layer. However, high SI values occurred throughout the year at deeper water layers. The potential aquaculture areas for S. salar and O. mykiss in the Yellow Sea were estimated as 52,270 ± 3275 (95% confidence interval, CI) and 146,831 ± 15,023 km2, respectively. Our results highlighted the use of SDMs in identifying potential aquaculture areas based on environmental variables. Considering the thermal heterogeneity of the environment, this study suggested that offshore aquaculture for Atlantic salmon and rainbow trout was feasible in the Yellow Sea by adopting new technologies (e.g., sinking cages into deep water) to avoid damage from high temperatures in summer.
Supplementary information:
The online version contains supplementary material available at 10.1007/s42995-022-00141-2.
... High levels of inequality in South Africa necessitate attention to socio-economic factors. These may range from primary logistical considerations (the availability of harbours, road connectivity and a nearby workforce), to the presence of other marine users, to national development goals like poverty alleviation and job creation in priority economic development areas (Falconer et al., 2016;Vianna et al., 2018). ...
The combined use of satellite-derived environmental data and a dynamic energy budget (DEB) model to determine Pacific oyster growth potential was adapted for the South African marine environment. Study areas consisted of the West Coast (high-chlorophyll, low temperature) and the South Coast (variable chlorophyll, higher temperature) ecoregions. Chlorophyll-a and sea surface temperature products from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to simulate yearly growth for 18 years. Average growth performance at the end of the culture period was mapped and compared for prominent sectors. Industry-relevant growth indicators, “days to reach commercial weight” and “optimal culture period length” were also established.
High growth potential was found in eastern nearshore sectors of the South Coast, particularly Plettenberg Bay, where oysters reached a median total weight (TW) of 271 g within 9 months. Other sectors in the region yielded Large commercial size within 150 days. However, South Coast growth hotspots were found to be highly variable, with transient unfavourable growth conditions leading to low flesh mass relative to TW. Growth potential was favourable in northern sectors of the West Coast, where oysters reached a median TW of up to 148 g in 9 months, Large commercial size within 200 days, and contained high flesh mass relative to TW.
Current oyster production sites were not found to be optimal for growth. Higher-growth sites coincide with areas in economic decline or with high levels of poverty. However, due to constraints of applying DEB models over large spatial scales, these results are considered preliminary and await in situ verification, as well as a spatial multi-criteria analysis, before investment and development.
... As multiple factors are to be related to aquaculture planning, Geographical Information System (GIS) techniques have been widely used in aquaculture zonation. Studies have been carried out to select the sites for aquaculture using land, soil, water, and infrastructure in China [29], India [23], Iran [9], Peru [30], Vietnam [8]; Thailand [24], Bangladesh [13], but the implementation of spatial restrictions as per the existing aquaculture policy has not been applied in general. The remunerations of aquaculture are surpassed by the ecological fears raised due to its unplanned development. ...
Unplanned aquaculture led to the destruction of important ecosystems
worldwide. A multi-criteria land suitability model (MLSM)
was developed to locate the suitable regions for aquaculture
using satellite images, AHP and Monte Carlo simulation, spatial
analysis, resource characteristics, and regulations. Twenty-one variables
within four subgroups (land use, water quality, soil characteristics,
and infrastructure support) have been integrated for the
site suitability. Land availability was the major limiting factor. The
area available for aquaculture was 4310 ha in Ramanathapuram
District, which consists of 33.3% of most appropriate, 23.1% of
appropriate, and 43.6% of moderately appropriate regions. The
carrying capacity of rivers indicated that all rivers had sufficient
nutrient assimilation capacity, except the Kottagudi River, where
the aquaculture planning is to be within the carrying capacity of
the river. The sensitivity analysis confirmed that integrated MLSM
and carrying capacity approach could be adopted to identify
suitable zones to develop aquaculture and save productive
ecosystems.
... As multiple factors are to be related to aquaculture planning, Geographical Information System (GIS) techniques have been widely used in aquaculture zonation. Studies have been carried out to select the sites for aquaculture using land, soil, water, and infrastructure in China [29], India [23], Iran [9], Peru [30], Vietnam [8]; Thailand [24], Bangladesh [13], but the implementation of spatial restrictions as per the existing aquaculture policy has not been applied in general. The remunerations of aquaculture are surpassed by the ecological fears raised due to its unplanned development. ...
The aquaculture development has raised many environmental concerns worldwide due to its unregulated and unplanned expansion and outshined the advantages of increasing fish production by utilizing unused lands. The present study aimed to identify suitable sites for aquaculture by integrating land resources availability, source water bodies characteristics, unproductive lands soil quality, and infrastructure support into existing national aquaculture developmental laws using a spatial decision support system at Puducherry Union Territory, India. The seventeen influencing factors have been measured, mapped, quantified, and integrated through pairwise matrix based sensitive analysis and Geographical Information System (GIS). The spatial regulations of the Coastal Aquaculture Authority Act (2005) of India were applied to remove restricted regions such as mangroves, agricultural lands, lands used for other purposes, lands up to 200 m from high tide lines. Also, suitable buffer zones were established between the productive resources before delineating the potential aquaculture zones. The results showed that 416 ha was available for aquaculture, including 244 ha in most suitable, 81 ha in suitable, and 91 ha in moderately suitable classification levels. Combining sensitivity analysis and spatial model into resource characteristics, land availability, and aquaculture regulation laws will direct aquaculture sustainably and responsibly while protecting the other productive ecosystems characteristics.
... En la actualidad se ha llevado a cabo un tenaz esfuerzo para disminuir dicha problemática mejorando los enfoques de manejo de la acuacultura, así como con la expansión de proyectos de índole acuícola en los cuerpos de agua, tanto con el objetivo de producir alimentos, como también para la utilización en la repoblación de ecosistemas (Ross et al. 2011). Uno de los aspectos más importantes para desarrollo apropiado de proyectos acuícolas es la selección del sitio, ya que proporciona las bases, no sólo para el beneficio económico, sino también para la sustentabilidad, la reputación y la permanencia de largo plazo, tanto de productores acuícolas de pequeña escala, como de la industria en su conjunto (Lawson 1998, Falconer et al. 2016. ...
La seguridad alimentaria y nutricional mundial es el gran desafío que enfrentan las nuevas generaciones, ya que el suministro de alimentos que provienen del mar y de las aguas continentales se encuentra amenazado por la sobreexplotación, modificación de ecosistemas, pérdidas económicas en el sector y considerables conflictos sociales; estas presiones sobre los recursos pesqueros y los efectos que tienen en los ecosistemas, así como la demanda de alimentos provenientes de la pesca, han estimulado un espectro de crecimiento e innovación en la industria acuícola.. Sin embargo, es importante reconocer la necesidad inherente de equilibrar adecuadamente los factores de capacidad de cargas ambiental y socioeconómica que pueden garantizar el desarrollo sostenible de la acuacultura.
... Not all factors will be of equal importance, as some will have more influence over production than others, affecting the overall suitability. Within the MCE approach, factors are weighted based on their importance, with analytical hierarchy process (AHP) (Saaty, 1988) being the most commonly and increasingly used method for determining these weights (Nath et al., 2000;Buitrago et al., 2005;Longdill et al., 2008;Radiarta et al., 2008;Silva et al., 2011;Micael et al., 2015;Falconer et al., 2016). ...
In this study, we have developed an approach to classify the suitability of shallow coastal lagoons for pacific oyster aquaculture as the first step in a site selection process. Historical bio-physical data and local knowledge were combined to produce overall scores for biological and logistical criteria relevant for oyster farming which were then combined using Multi-Criteria Analysis (MCA) for an overall lagoon suitability score. A Dynamic Energy Budget growth model was also used to identify and rank suitability of shallow coastal lagoons to host Pacific oysters farming sites. Furthermore, modelled growth data were used to estimate the production cycle length and the potential productivity of the newly identified sites. The results indicated that biological and logistic factors were suitable for Pacific oyster farming in eleven out of twelve of the lagoons considered. However, acquiring water classification for shellfish farming and maintaining high water quality standards will be critical for any sustainable development of culture areas. Potential production figures and logistic scores, clearly indicates in which lagoons investments should be focused and what output could be realised from these very productive ecosystems. The results can be used to indicate where more detailed assessment should take place. As remote-sensing technologies continue to develop and algorithms for the interpretation of ocean colour in coastal areas keep improving, this multidisciplinary approach will increase our ability to estimate aquaculture production in complex aquatic systems. This approach will provide stakeholders, policy makers and regulators with a new and powerful decision-making tool for site selection of sustainable oyster farming activities and the management of the surrounding coastal areas.
... In MCE, multiple spatial variables of biological, environmental, and socio-economic components are weighted according to their importance for the selection of an aquaculture site. Numerical models such as "species distribution models" were also used for site selection in which probable species distribution is predicted from the data of species occurrence and other environmental variables (Elith and Leathwick, 2009 ;Falconer et al., 2016). These numerical models are, however, not used directly to calculate the hydrodynamic and water quality conditions that predict the physical environment suitable for aquaculture. ...
Three-dimensional modeling was performed in Tongyeong, South Korea to identify a space suitable for Yesso scallop farming that may not be successful if seawater temperature remains above 22 °C. In the research area, an underwater basin was found at a depth of 70 m; the depth outside the basin was not deeper than 30 m. It was expected that the water temperature in the interior of the basin might be low enough for farming during summer. The present study was then designed to investigate the temperature distribution in this basin area to verify if a water layer with consistently low temperature existed below the surface layer, using a MOHID (MOdelo HIDrodinámico) three-dimensional numerical model. The model applied mixed vertical coordinates so that the difficulties in modeling near the basin, where water depth sharply changes, could be overcome. In addition, a multi-level nesting system was developed based on the 72 -h forecasting system of the sea status around South Korea, which increased the modeling accuracy using updated boundary conditions. The model was validated by the measured tide and temperature data. The results showed that a strong thermocline was formed at depth of 15 m and a sub-surface space existed at depths deeper than 30 m, where seawater temperature was lower than 22 °C even in summer, which indicates the possibility of successful farming in the research area. The measurements also supported this result because dissolved oxygen and chlorophyll-a were not scarce in the sub-surface space probably due to the strong tidal mixing that could bring the surface seawater properties down below the thermocline. It was also found that the model was effective in resolving the thin thermocline and the sub-surface space below it due to the mixed vertical coordinate system.
... Spatial Multi-Criteria Evaluation (SMCE) is a hierarchical process commonly used in spatial planning and management, notably for aquaculture site selection (Brigolin et al., 2015(Brigolin et al., , 2017Falconer et al., 2016;Longdill et al., 2008;Radiarta et al., 2008). SMCE aims to first identify areas within which aquaculture would not be feasible at all, excluding those areas within which precluding conflicts exist, and to subsequently identify optimal areas where aquaculture would be feasible using a suitability index. ...
Oyster production has historically taken place in intertidal zones, and shellfish farms already occupy large
extents of the French intertidal space. The expansion of French shellfish aquaculture within intertidal areas is
therefore spatially limited, and moving production to the subtidal offshore environment is considered to be a
possible solution to this problem. Finding new sites along the French Atlantic coast was studied here from the
perspective of small oyster companies run by young farmers, who are interested in offshore bivalve aquaculture
expansion compatible with their investment capacity. In assessing the feasibility of such offshore production, we
considered three main issues: (1) bivalve growth potential and (2) technical feasibility and conflicting uses, both
within a spatial framework, as well as (3) the steps and barriers of the administrative licensing process. Oyster
spat in an experimental offshore cage showed significantly faster growth, in terms of both weight and length,
compared to those in an intertidal cage, mainly due to lower turbidity and full-time feeding capacity (i.e.,
constant immersion in the water). A combination of Earth Observation data and bivalve ecophysiological
modelling was then used to obtain spatial distribution maps of growth potential, which confirmed that offshore
sites have better potential for oyster growth than the traditionally oyster-farmed intertidal sites overall, but that
this is highly spatially variable. Small-scale producers indicated two technical factors constraining where farms
could be located: bathymetry must be between 5 and 20m and the distance from a harbor no more than five
nautical miles. These were included along with maps of various environmental and socio-economic constraints in
a Spatial Multi-Criteria Evaluation (SMCE). Touristic traffic and bottom trawling by fisherman were found to be
the two other most restrictive variables. The GIS-based SMCE developed in this study showed that there is almost
400 km2 of highly- to very highly-suitable area within which to develop offshore aquaculture using simple, lowcost
bottom-cage techniques, and can be used to assist the shellfish industry in the Marine Spatial Planning
decision-making process, still in progress in this coastal area. However, the complexity of the administrative
processes necessary to obtain an offshore license is perceived as a stronger barrier by farmers owning small
companies than site selection, technical feasibility, and required investments, and will be crucial to address in
order to realistically proceed to offshore cultivation. The process demonstrated here, and the results are relevant
to other coastal and offshore locations throughout the world and can be adapted for other species.
... Currently, SDMs are applied broadly in the fields of life and environmental science. A variety of algorithms are available for species management and to predict climate change impacts, to understand biological invasions (Elith and Leathwick, 2009;Guillera-Arroita et al., 2015;Thuiller et al., 2009) identify key marine protected areas (Pereira et al., 2018), or to select siting aquaculture farms (Falconer et al., 2016). Most studies, however, are terrestrial and marine-based studies are scarce (Robinson et al., 2011;Singer et al., 2017;Thuiller et al., 2009). ...
... A procedure was created to establish a score for each criterion in the model. These criteria were reclassified and scored, as shown in Table 1, similar to the method used by Falconer et al. [28], in which a categorical scale was adopted. On this four-point scale, a 1 was "largely unsuitable," a 2 was "slightly suitable," a 3 was "suitable," and a 4 was "highly suitable." ...
This study proposed a method for identifying areas appropriate for fish farming in ground-excavated ponds using data obtained from public institutions. The method was applied to three cities located in the central-southern region of Paraná State, Brazil. In order to select appropriate areas, a geographic information system (GIS) was created using data from a digital elevation model (DEM), as well as data on soil occupation and type. A variable reclassification model (VRM) was created, and the analytic hierarchy process (AHP) method was applied to establish weights for a multi-criteria assessment of the factors. Non-classifiable areas and areas with constraints were identified and removed from the analysis. The sites classified as highly suitable or suitable represented 33.270.79 ha (18.71% of the total area), while the restricted areas represented 54,427.91 ha (30.60% of the total area). This method may represent a useful tool for decision making in the context of regional planning and may be used in the establishment of public policy and in the allocation of resources for aquaculture development.
... Modeling can inform trade-offs between aquaculture and biodiversity (Kluger et al., 2017) and inform assessments of ecological carrying capacity (Sequeira et al., 2007). Models can also be merged with GIS decision support tools to inform sustainable site selection based on the underlying ecosystem characteristics (Bricker, Getchis, Chadwick, Rose, & Rose, 2016;Falconer, Telfer, & Ross, 2016). A combination of diagnostic tools, surveillance, and forecasting tools (modeling) can complement stringent biosecurity measures and are important for reducing the impacts of disease (Groner et al., 2016). ...
... Despite its pitfalls the method is suitable for individual and group decision making (Yavuz and Baycan, 2013;Sutadian et al., 2017;Morgan, 2017) and has been applied in many research fields, including nature, economy and society (Saaty, 1996;Latinopoulos et al., 2012;Chen et al., 2014;Zhang et al., 2014;Li et al., 2016;Ying et al., 2007). In particular, the AHP method has been applied in aquaculture site selection studies (Falconer et al., 2016), frequently coupled with geographic information systems (Hossain et al., 2009;Radiarta et al., 2008;Rekha et al., 2015). ...
Keywords: Ecosystem approach to aquaculture Spatial planning Site selection Physical carrying capacity Saltworks Mondego estuary Portugal A B S T R A C T The European Commission has identified competition for space as one of the main factors contributing to the stagnation of EU aquaculture production and has recommended coordinated spatial planning, as a mean to identify sites with favorable operational characteristics for aquaculture and lower potential for conflict with other activities. In coastal areas of the Mediterranean, pond aquaculture has emerged as an alternative to salt production in abandoned artisanal Salinas, compromising the delivery of Ecosystem Services in wetland areas. To establish a methodology to estimate the physical carrying capacity for coastal pond aquaculture, and the contribution of the ecosystem to the value of provisioning services from aquaculture, while minimizing the competition for space with solar salt production, we applied a multicriteria-decision making tool (AHP method) to identify priority areas for extensive and semi-intensive aquaculture development in solar saltscapes, taking into account physical factors of ecological and social nature. The study presents spatial allocation scenarios for aquaculture development in the saltscapes of the Figueira da Foz, in the Atlantic coastal zone of Portugal. The physical carrying capacity for the two scenarios presented indicates a potential increase of the area occupied by aquaculture farms in ponds previously occupied by inactive farms and flooded/land filled salterns, whose sites tend to minimize conflict with salt production through avoiding the same water input location and being adjacent to active farms. In conclusion, the approach applied has proven to be successful to manage space competition between aquaculture and salt production, contributing to a sustainable increase of the value of the provisioning of ecosystem services from aquaculture. In future studies, estimation of the social carrying capacity should be combined with the approach followed in this study to improve the definition of the acceptable social limits for aquaculture development in saltscapes.
Aquaculture is one of the most rapidly expanding industries in the world. It plays a central role in global food production and serves as the primary source of protein for human consumption. To navigate and excel in this dynamic field, a deep understanding of the fundamental principles of aquaculture is essential to ensure long-term success and sustainability. This book chapter provides an overview that presents the essence of aquaculture through ten key pillars. From strategic site selection to careful feeding strategies, each pillar contributes to a holistic understanding and provides the foundation for success in this ever-evolving industry. The global perspective emphasizes aquaculture’s adaptability in different landscapes, from small pond systems to extensive and intensive methods. Despite its inherent challenges, aquaculture is emerging as a cornerstone in the global food security edifice, receiving support and cooperation from national and international organizations. In addition to its primary role in food production, aquaculture actively contributes to economic growth, job creation, and resource management. Adherence to ethical practices and implementing responsible policies are essential to avoid social conflict, with the “planet-first” approach at the forefront of decision-making. The harmonious interplay of these ten pillars forms the basis for successful and sustainable aquaculture that aligns with the overarching global goals of environmental sustainability, economic growth, and food security. This chapter serves as a guide for practitioners and emphasizes aquaculture’s pivotal role in achieving broader societal goals.
This Data Descriptor contains a dataset with the production characteristics and socioeconomic performance of small-scale carp aquaculture systems in Bangladesh. The dataset was collected through a structured household survey with 4,540 producers from 54 upazilas (analogous to counties) across Bangladesh. Study upazilas were systematically selected to represent both locations with substantial carp production currently and locations with such future potential. Respondents were randomly selected through carp producer lists in each study upazila. Information about the production characteristics includes farm/pond sizes, fish species, production technologies, feed/seed use, and aquaculture expenditures, among others. Information about the performance includes fish output and sales, as well as household income, poverty and food security, among others. This dataset can be valuable to researchers, practitioners and policy-makers that wish to explore the heterogeneity and differentiation of small-scale aquaculture production systems and the factors affect their performance in Bangladesh and other developing countries.
Fish consumption is increasing due to the global population growth. Therefore,
taking advantage of new methods such as marine aquaculture can be areliable
source for the production of fish in the world. The purpose of this study is the
spatial analysis of marine aquaculture farms in the coasts of Mazandaran
province. In this study, three categories of criteria (water quality, economic-
social and physical-environmental) were considered for spatial analysis of
aquaculture farms in the coasts of Mazandaran, which are based on the
Geographic Information System (GIS) and hierarchical analysis process (AHP),
is used according to the definition of the decision law, and at the end, the existing
aquaculture farms (9 farms) are analyzed using the Extract function. The results
show that the location of the present farms can be transferred to more favorable
areas with less risk. Among the existing farms, farms 1 and 2, located on the
coasts of Joibar and Babolsar, have the most suitable condition and the highest
amount of desirability. Also, the results of weighting between the three groups
of water quality parameters show physical and socio-economic; Due to the
importance of temperature, turbidity and chlorophyll criteria in marine
aquaculture, water quality group has more weight than other groups (0.4034)
and then the group of physical factors (0.3808) than social factors. (0.2168)
more weight is given. The findings of this study show the ability of GIS as well as
satellite imagery to locate and evaluate marine aquaculture
Zusammenfassung
Weltweit ist die Aquakultur der am schnellsten wachsende Sektor in der tierischen Lebensmittelproduktion. Dieser Sektor wird voraussichtlich immer wichtiger werden, um den zukünftigen Nahrungsmittelbedarf zu decken. Im Binnenland Österreich ist der Selbstversorgungsgrad von Fisch mit 6 % insgesamt bzw. 48 % bei Süßwasserfischen eher gering. Um ein nachhaltiges Wachstum des Sektors zu ermöglichen und gleichzeitig negative Auswirkungen auf die verwendeten aquatischen Ökosysteme und andere Nutzungen der Ressource Wasser zu vermeiden, wurde ein räumlicher Analyse-Ansatz zur nachhaltigen Zonierung von Forellenzuchtbetrieben, mit einem Schwerpunkt auf Durchflussanlagen, entwickelt. Dabei wurden 17 land- und 17 gewässerbezogene räumliche Kriterien identifiziert und hinsichtlich ihrer Eignung für die Errichtung eines Forellenzuchtbetriebs klassifiziert. Anschließend wurden die Kriterien in einem integrativen GIS-basierten Modellierungsansatz kombiniert, um eine landesweite und räumlich explizite Zonierung von Eignungsgebieten innerhalb Österreichs vorzunehmen. Von insgesamt 8113 Teileinzugsgebieten (TEZG) mit einer mittleren Größe von 10 km ² wurden so 1295 TEZG als geeignet eingestuft. Für diese TEZG wurde eine potenzielle Produktionsmenge an Fisch abgeschätzt. Mit einer mittleren Produktion von 48,7 t pro Standort könnten in Summe 63.088 t Fisch in Durchflussanlagen österreichweit produziert werden. Die Ergebnisse sollen in weiterer Folge in einem Online-Tool zu Verfügung gestellt werden und so die Entscheidungsfindung von Investoren und Behörden unterstützen. Als Schnittstelle zwischen den unterschiedlichen Anwender:innen kann das Tool dazu beitragen, eine nachhaltige Entwicklung der Aquakultur in Österreich voranzutreiben und Konflikte und Fehlinvestitionen frühzeitig zu vermeiden.
In the present study, the maximum entropy model (MaxEnt) based on the data of sea surface temperature (SST) and published information was used to assess the site suitability for the aquaculture expansion of the sea cucumber Apostichopus japonicus and the sea urchin Strongylocentrotus intermedius in China. According to the current assessment, the coastal areas of Hebei province and Tianjin have great prospects for A. japonicus aquaculture, while is currently being underutilized. In the south, more than 94% of the coastal areas in Zhejiang, Fujian, and Guangdong provinces are suitable for the growth of A. japonicus for six months, especially the coastal areas of Lianjiang, Changle, Fuqing and Putian in Fujian province. The water temperatures in more than 94% of China's coastal areas are higher than 25 °C in July and August, which probably results in the mortality of S. intermedius in aquaculture. This clearly indicates that high water temperature is the bottleneck of S. intermedius aquaculture and well explains the limited expansion of this commercially important exotic species since the introduction in 1989. We suggest a new aquaculture model of S. intermedius that extends the seed production to November to avoid the mass mortality in summer. In the south, 64% of coastal areas in Zhejiang and Fujian provinces are suitable for the transplantation of S. intermedius to the south. The present study suggests the ecological niche model MaxEnt based on the data of SST and published information as a new tool for the assessment of the site suitability of sea cucumbers and sea urchins in China. This provides new insights into the aquaculture expansion of native and exotic species.
O presente estudo no município de Conceição do Araguaia no estado do Pará visando observar de forma espacial o estabelecimento de empreendimentos aquícolas e a possibilidade de ampliação da atividade, utilizando análise espacial ponderada. Foi verificado a distribuição espacial dos piscicultores existentes e suas respectivas produções, através de ferramentas geoestatísticas, entre as quais: Averagem Nearest Neighbor (ANN) e kernel, para análise de densidade e o método Natural Neighbor (NN) para avaliar as áreas mais produtivas. Para análise de ponderação a áreas propícias a construção de viveiros escavados utilizou a metodologia Weighted Overlay, que sobrepõem várias camadas com pesos atribuídos, de acordo com a sua participação no processo construção aquícola. Na análise de ponderação foram utilizadas imagens de satélite processadas de forma a representar relevos, hidrografia e uso do solo, em alguns mapas foi utilizado informações de instituições governamentais. Os resultados mostraram que a dispersão dos piscicultores se deu de forma agregada. Os aglomerados formados dentro de um raio de 5,0 km, constituíram 6 áreas, mas apenas duas com potencial para crescimento. As ponderações de áreas propicias, mostraram que 27,43% é regular e 16,65% são ideais, muito embora a atividade se desenvolveu nas áreas regulares.
Mariculture in open seas particularly, sea cage farming is rapidly expanding all along the territorial waters of the Indian sub-continent. Intensification of such new activities in open waters may lead to issues related to sustainability and spatial usage. Additionally, there could be escalation of ecological apprehensions and other cross sectoral conflicts. Thus, in view of the importance of sustainable and judicious utilization of open waters for mariculture development in the country, a preliminary Geographic Information System (GIS) based decision support model and a spatial framework was developed for site selection of cage farms in the territorial waters of Gujarat state, India along the Arabian Sea. The transit trajectory of 20 km sea space accounting to 23949.33 km2 area was modelled under the study. Apart from the preferable biological and oceanographic arrays for the culture system and candidate marine fish species; data on maritime aids, sewage, industrial outlets, river mouths, ecologically sensitive locations and other constraints were marked, re-classified, optimized and benchmarked for the decision-making analysis. The developed comprehensive model consisted office sub-models viz., topographic, physical, chemical and biological oceanographic and socio-infrastructural models. The model explored and demarcated suitable sea space of 12557.74 km2 (52.43% of total) for mariculture. Out of the demarcated area, 27.43% was the most suitable and 25.00% was moderately suitable for mariculture development, emphasizing the untapped potential of the available open waters of Gujarat state. The sensitivity simulation indicated that the developed systematic analytical GIS-Multi Criteria Evaluation (MCE) model was effective, stable and delivered an efficient solution for complex spatial challenges for mariculture site selection process. Further, these results demonstrated that the present spatial decision support model, in particular its methodology and framework, allowed identification of the best suitable sites for mariculture along the territorial waters of the country. The model was adaptable to all maritime states of this subcontinent and could be an effective and useful tool to resolve the complex spatial problems associated with the site selection process for mariculture in open seas. It also provides a way forward for policymakers and stakeholders to formulate strategies for mariculture expansion while governing the marine resources in a holistic, cleaner and sustainable manner.
Maximum entropy (maxent) modelling is a widely used method for developing species distribution models (SDMs), but default maxent modelling methods can result in overly complex models with poor transferability. Methods suggested to reduce overfitting include increasing regularisation, using only linear and quadratic features, or applying forward selection of predictors using maximum likelihood (ML) methods. We built models using these options to determine environmental suitability within existing aquaculture zones for eight seaweed species, four red (Rhodophyta: Florideophyceae) and four brown (Ochrophyta: Phaeophyceae), that are being investigated for aquaculture in southern Australia. Forward selection models were the most parsimonious, but we encountered failure of ML methods for Pterocladia lucida (Rhodophyta) due to separation. Separation is a known issue for logistic regression and has recently been recognised in maxent models. Separation occurs where a variable, or combination of variables, is a perfect predictor for a binary response, here, species occurrence, and results in ML parameter estimates tending to infinity. One method for obtaining finite parameter estimates under separation is to apply a Cauchy prior distribution for coefficients. We therefore also built models for each species using a Cauchy-prior version of the forward selection method, and found that these models performed similarly to those built with ML methods. Default models achieved marginally higher predictive performance than other options based on training data metrics, but simpler models performed equivalently to, or better than, default models at predicting independent presence-absence test data. Predictive performance using test data varied considerably between species, but the difference in performance between models within each species was generally small. Our results confirm the concern that default maxent models may suffer from over-fitting and poor transferability. Model transferability and interpretability were important for our purpose, hence, based on the principle of parsimony, forward selection models were preferred. We also found that forward selection models retained similar predictive performance to the best model as assessed by each metric, further supporting use of these models. Where ML methods failed due to separation, the use of the Cauchy-prior method was a viable alternative. Predictions for the region of interest (Spencer Gulf, South Australia) were generated using the most parsimonious models, and Solieria robusta (Rhodophyta) showed the highest predicted suitability of the eight candidate species within existing aquaculture zones, especially in northern Spencer Gulf. Predicted suitability was low for the other Rhodophyta considered, while each of the Phaeophyceae showed moderate to high suitability in at least some southern Spencer Gulf aquaculture zones. These model results help to inform selection of the best candidate species and suitable farming areas for future research.
Attention is presently turning to the processes, methods and tools that allow practical
implementation of the ecosystem approach to aquaculture (EAA).This will require the
use of various tools and methodologies, including environmental impact assessments
and risk analysis. Ecosystem-based management involves a transition from traditional
sector-by-sector planning and decision-making to the more holistic approach of
integrated natural resource management at different scales and for ecosystems that cross
administrative boundaries. An essential element for the implementation of the EAA will
be the use of spatial planning tools including Geographic Information Systems, remote
sensing and mapping for data management, analysis, modelling and decision-making.
These proceedings focus on the status and process of implementing these tools which, in
turn, necessitate the development of capacity building, training and promotion of spatial
planning among decision-makers and technical staff. The document is organized in two
parts. The first, the workshop report, deals with the background of the EAA effort and
the genesis of the workshop. Most importantly, it captures the salient contributions
of participants from their formal presentations and general discussions. The main
conclusions of a review of the status and potential of spatial planning tools, decision making
and modelling in implementing the EAA are also included. The review itself,
along with an abstract, forms the second part
This publication is the proceedings of the Food and Agriculture
Organization of the United Nations (FAO) Expert Workshop on Site
Selection and Carrying Capacities for Inland and Coastal Aquaculture
convened at the Institute of Aquaculture, University of Stirling, the
United Kingdom of Great Britain and Northern Ireland, from 6–8
December 2010.
The main purpose of this document is to summarize knowledge and
provide guidance to member countries on the process of aquaculture
site selection and carrying capacity estimates within an ecosystem
approach to aquaculture (EAA). Seven global reviews and ten regional
reviews on site selection and carrying capacity encompassing inland
aquaculture and coastal aquaculture were presented and discussed at
the workshop. Four carrying capacity categories, appropriate for
different types of aquaculture, were discussed and agreed upon:
physical, production, ecological and social. The range and capability of
modelling tools, including spatial tools, available for addressing these
capacities were discussed.
The prioritization and sequence for addressing site selection and the
different categories of carrying capacity were considered in detail in
terms of both regional or national priorities and site-specific
considerations.
Two major outcomes have been developed from the workshop:
(i) a comprehensive record of the workshop proceedings (this
document), which includes global and regional reviews and a summary
of major findings and recommendations; and (ii) a set of guidelines for
addressing site selection and carrying capacity in the context of the
framework of the ecosystem approach to aquaculture (EAA), including
summaries of the key findings and recommendations for aquaculture
site selection and carrying capacity with an EAA perspective.
Recommendations were made for promotion of these concepts and
approaches by FAO.
This publication is organized in two parts. One part contains the
workshop report and the first global review entitled “Carrying
capacities and site selection within the ecosystem approach to
aquaculture”, while the second part is the full document.
The latter part is available on a CD–ROM accompanying the printed
part of this publication.
Defining the physical suitability of an area for marine cage fish farming is of great importance, as each cage type has its own engineering tolerance levels and is designed to cope with a certain range of environmental conditions. Currently, there are no definitive, objective methods used to evaluate the suitability of coastal and offshore sites with respect to the physical limits of the location and the engineering design of a specific cage type. This study developed models which incorporate physical environmental parameters and cage engineering design within a GIS (graphical information system) environment, providing a valuable decision support tool for farmers, regulators and policy makers. The Western Isles of Scotland, UK, were selected as a study area due to the wide range of coastal and offshore environments. In addition, we selected 4 cage types designed for different wave exposure conditions (sheltered, moderately exposed, exposed and offshore). The models have been developed for worst-case scenarios, such as maximum significant wave height, conditions which are often difficult to predict. As shown in this study, the models can be used to assess the risk of using the selected cage type in a certain area and to highlight specific locations for development. The results indicate there is scope for further expansion of the aquaculture industry in the Western Isles using cages designed for exposed and offshore conditions, whereas there is limited potential for new developments using cages designed for moderately exposed environments. This allows stakeholders to make a robust decision about what cage type to use and where to locate it.
Wildfires are a serious threat for land managers and property owners, and over the last few decades this threat has expanded as a result of increased rural development. Most wildfires in the north-eastern US occur in the wildland-urban interface, those regions of intermingling urban and non-developed vegetated lands, where access to firefighting resources can be limited. We created monthly wildfire ignition probability maps from environmental predictors and wildfires occurring between 2000 and 2009 for the states of New Jersey, Ohio and Pennsylvania. Predictor variables included a drought index, long-term soil moisture, percentage forest and wildland-urban interface classifications. Probability maps generated from modelled (Maxent) extrapolations were used to create monthly hazard maps to aid agencies and managers with resource allocation and likelihood projections of wildfires across the region. Our results suggest that monthly hazard assessments provide a better indication of potential wildfires than does a single mean annual probability. Our monthly predictions retain information related to long-term seasonal variability associated with environmental variables and the recorded wildfires providing spatial and temporal information for resource allocation.
Remotely sensed datasets are increasingly being used to model habitat suitability for a variety of taxa. We review habitat suitability models (HSMs) developed for both plants and animals that include remote sensing predictor variables to determine how these variables could affect model projections. For models focused on plant species habitat, we find several instances of unintentional bias in HSMs of vegetation due to the inclusion of remote sensing variables. Notably, studies that include continuous remote sensing variables could be inadvertently mapping actual species distribution instead of potential habitat due to unique spectral or temporal characteristics of the target species. Additionally, HSMs including categorical classifications are rarely explicit about assumptions of habitat suitability related to land cover, which could lead to unintended exclusion of potential habitat due to current land use. Although we support the broader application of remote sensing in general, we caution developers of HSMs to be aware of introduced model bias. These biases are more likely to arise when remote sensing variables are added to models simply because they improve accuracy, rather than considering how they affect the model results and interpretation. When including land cover classifications as predictors, we recommend that modellers provide more explicit descriptions of how habitat is defined (e.g., is deforested land considered suitable for trees?). Further, we suggest that continuous remote sensing variables should only be included in habitat models if authors can demonstrate that their inclusion characterizes potential habitat rather than actual species distribution. Use of the term ‘habitat suitability model’ rather than ‘species distribution model’ could reduce confusion about modelling goals and improve communication between the remote sensing and ecological modelling communities.
Background/Question/Methods
Maxent, one of the most commonly used methods for inferring species distributions and environmental tolerances from occurrence data, allows users to fit models of arbitrary complexity. Model complexity is typically constrained via a process known as L1 regularization, but at present little guidance is available for setting the appropriate level of regularization, and the effects of inappropriately complex or simple models are largely unknown. In this study, we demonstrate the use of information criterion approaches to setting regularization in Maxent, and compare models selected using information criteria to models selected using other criteria that are common in the literature. We evaluate model performance using occurrence data generated from a known “true” initial Maxent model, using several different metrics for model quality and transferability.
Results/Conclusions
We demonstrate that models that are inappropriately complex or inappropriately simple show reduced ability to infer habitat quality, reduced ability to infer the relative importance of variables in constraining species’ distributions, and reduced transferability to other time periods. We also measure the relative effectiveness of different model selection criteria, and demonstrate that information criteria may offer significant advantages over the AUC-based methods commonly used in the literature.
Four statistical techniques for modelling landslide susceptibility were compared: multiple logistic regression (MLR), multivariate adaptive regression splines (MARS), classification and regression trees (CART), and maximum entropy (MAXENT). According to the literature, MARS and MAXENT have never been used in landslide susceptibility modelling, and CART has been used only twice. Twenty independent variables were used as predictors, including lithology as a categorical variable. Two sets of random samples were used, for a total of 90 model replicates (with and without lithology, and with different proportions of positive and negative data). The model performance was evaluated using the area under the receiver operating characteristic curve (AUC) statistic. The main results are (a) the inclusion of lithology improves the model performance; (b) the best AUC values for single models are MLR (0.76), MARS (0.76), CART (0.77), and MAXENT (0.78); (c) a smaller amount of negative data provides better results; (d) the models with the highest prediction capability are obtained with MAXENT and CART; and (e) the combination of different models is a way to evaluate the model reliability. We further discuss some key issues in landslide modelling, including the influence of the various methods that we used, the sample size, and the random replicate procedures.
Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate-change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present-day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding-bird species over the past ∼20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision-planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.
Aim To demonstrate that multi-modelling methods have effectively been used to combine static species distribution models (SDM), predicting the geographical pattern of suitable habitat, with dynamic landscape and population models to forecast the impacts of environmental change on species’ status, an important goal of conservation biogeography.
Methods Three approaches were considered: (1) incorporating models of species migration to understand the ability of a species to occupy suitable habitat in new locations; (2) linking models of landscape disturbance and succession to models of habitat suitability; and (3) fully linking models of habitat suitability, habitat dynamics and spatially explicit population dynamics.
Results Linking species–environment relationships, landscape dynamics and population dynamics in a multi-modelling framework allows the combined impacts of climate change (affecting species distribution and vital rates) and land cover dynamics (land use change, altered disturbance regimes) on species to be predicted. This approach is only feasible if the life history parameters and habitat requirements of the species are well understood.
Main conclusions Forecasts of the impacts of global change on species may be improved by considering multiple causes. A range of methods are available to address the interactions of changing habitat suitability, habitat dynamics and population response that vary in their complexity, realism and data requirements.
Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species’ distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species’ occurrence data. Presence-only data were effective for modelling species’ distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
We applied a remote-sensing method using MODIS time-series imagery to detect the expansion of intensive farming systems (shrimp farming and triple rice cropping) in the Soc Trang and Bac Lieu provinces of the Vietnamese Mekong Delta (VMD). Field surveys for interpreting the estimates derived from the remote-sensing analyses were conducted in June and September 2007. From 2000 to 2006, there has been rapid expansion of inland aquaculture, especially shrimp farming, in the western part of the Bac Lieu province and the coastal regions of both the Bac Lieu and Soc Trang provinces. The triple rice-cropped area expanded concentrically from specific small locations in the Bac Lieu province from 2001 to 2006. The triple rice-cropped areas in Soc Trang province also expanded concentrically from 2001 to 2003, but some of these new triple rice-cropped areas returned to double rice cropping after 2004. Interviews with farmers and ancillary hydrological monitoring data suggested that changes in the water environment and transmission of information about new farming systems are closely connected with the annual expansion of triple rice-cropped areas in both provinces. The availability of salt-free irrigation water in the dry season may have led some pioneering farmers to attempt full-scale dry-season cropping. Furthermore, successful dry-season harvests and recent increases in the price of rice might have encouraged neighboring farmers to follow suit. Based on MODIS time-series imagery with field interviews at land-use change hotspots, the spatial structure of coastal farming systems and their recent changes were revealed from a macroscopic view point.
The 2007 Energy Independence and Security Act mandates a five-fold increase in US biofuel production by 2022. Given this ambitious policy target, there is a need for spatially explicit estimates of landscape suitability for growing biofuel feedstocks. We developed a suitability modeling approach for two major US biofuel crops, corn (Zea mays) and switchgrass (Panicum virgatum), based upon the use of two presence-only species distribution models (SDMs): maximum entropy (Maxent) and support vector machines (SVM). SDMs are commonly used for modeling animal and plant distributions in natural environments, but have rarely been used to develop landscape models for cultivated crops. AUC, Kappa, and correlation measures derived from test data indicate that SVM slightly outperformed Maxent in modeling US corn production, although both models produced significantly accurate results. When compared with results from a mechanistic switchgrass model recently developed by Oak Ridge National Laboratory (ORNL), SVM results showed higher correlation than Maxent results with models fit using county-scale point inputs of switchgrass production derived from expert opinion estimates. However, Maxent results for an alternative switchgrass model developed with point inputs from research trial sites showed higher correlation to the ORNL model than the corresponding results obtained from SVM. Further analysis indicates that both modeling approaches were effective in predicting county-scale increases in corn production from 2006 to 2007, a time period in which US corn production increased by 24%. We conclude that presence-only methods are a powerful first-cut tool for estimating relative land suitability across geographic regions in which candidate biofuel feedstocks can be grown, and may also provide important insight into potential land-use change patterns likely to be associated with increased biofuel demand.
Published in Cooperation with THE UNITED STATES AQUACULTURE SOCIETY. The rapid growth of aquaculture worldwide and domestically has caused concerns over social and environmental impacts. Environmental advocacy groups and government regulatory agencies have called for better management to address potentially negative impacts and assure sustainable aquaculture development. Best Management Practices (BMPs) combine sound science, common sense, economics, and site-specific management to mitigate or prevent adverse environmental impacts. Environmental Best Management Practices for Aquaculture will provide technical guidance to improve the environmental performance of aquaculture. This book will be the only comprehensive guide to BMPs for mitigation of environmental impacts of aquaculture in the United States. The book addresses development and implementation of BMPs, BMPs for specific aquaculture production systems, and the economics of implementing best management practices. Written by internationally recognized experts in environmental management and aquaculture from academia, government, and non-governmental organizations, this book will be a valuable reference for innovative producers, policy makers, regulators, research scientists, and students.
Marine aquaculture of bivalve molluscs is an important economic activity in Santa Catarina State, Brazil, with more than 5000 persons directly and indirectly involved and an annual revenue of US$ 18 million in 2013. In the first decade of this activity, a lack of proper regulation imposed multiple obstacles to the sustainable management of local shellfish farming. The occupation of marine space occurred in a disorderly manner, and the unplanned development led to unfavourable conditions that threatened the sustainability of the industry. This study describes how better planning and management tools have improved governance of marine aquaculture in Santa Catarina State. The process included development of a legal framework for aquaculture planning, elaboration of local development plans with a participatory and multidisciplinary approach, development of a geographic information system to identify favourable areas and creation of a Web-based aquaculture management system. The combined application of these actions, along with continuing extension services, is expected to contribute to the regulation of 837 shellfish farming areas, the expansion of farming activity, the mitigation of the environmental and visual impacts caused by coastal aquaculture and an increase in the public health of shellfish consumers. In this manuscript, we report an example of how the application of better planning and management of the aquaculture sector can prepare the industry for a sustainable growing cycle.
The combined impact of sea level rise, changes in the upstream freshwater flow, and tidal regime on salinity intrusion that affects Pangasius (Pangasianodon hypophthalmus) farming in the Mekong Delta was assessed in this study. Salinity intrusion was simulated for the whole Mekong Delta by a 1D numerical model. The scenario derived from the SRES B2 climate change projection for Vietnam by the year 2100 (0.73 m of sea level rise and 29 % reduction of the Mekong River flow in the dry season). The simulated results suggest that the saline water will shift landward by 70–80 km which covers almost 63 % area of the Mekong Delta. Furthermore, it shows that the Pangasius farming area will be reduced by approximately 11 % with the shrinkage of the freshwater zone due to the salinity intrusion.
The economic performance of gilthead seabream, Sparus aurata, aquaculture in Mediterranean countries is not homogeneous despite the availability of a universalized technology and the absence of trade barriers. Differences in competitiveness among aquaculture facilities result, in part, from economic and environmental factors, which are conditioned by the geographical location of the facility. This article aims to identify and analyze the competitive advantages derived from the different environmental conditions in which seabream production has been developed along the Mediterranean Sea. A particle swarm optimization algorithm based on a seabream bioeconomic model was applied to the economic optimization of multibatch aquaculture production. The analysis involved hypothetical fattening farms located in the major areas in which this species is cultured. The water temperature was the only parameter that varied among locations. The average water temperatures in these locations were below the optimum growth temperature, around which growth progressively diminishes. The results of the study showed that the locations with higher average water temperatures and less variable water temperatures allowed the cultivation process to be more economically efficient. The seabream farms located in Greece and Turkey had a competitive advantage in terms of productivity and operating profitability because of more favorable environmental conditions.
The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling, with over 1000 published applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt typically outperforms other methods based on predictive accuracy and 2) the software is particularly easy to use. MaxEnt users must make a number of decisions about how they should select their input data and choose from a wide variety of settings in the software package to build models from these data. The underlying basis for making these decisions is unclear in many studies, and default settings are apparently chosen, even though alternative settings are often more appropriate. In this paper, we provide a detailed explanation of how MaxEnt works and a prospectus on modeling options to enable users to make informed decisions when preparing data, choosing settings and interpreting output. We explain how the choice of background samples reflects prior assumptions, how nonlinear functions of environmental variables (features) are created and selected, how to account for environmentally biased sampling, the interpretation of the various types of model output and the challenges for model evaluation. We demonstrate MaxEnt’s calculations using both simplified simulated data and occurrence data from South Africa on species of the flowering plant family Proteaceae. Throughout, we show how MaxEnt’s outputs vary in response to different settings to highlight the need for making biologically motivated modeling decisions.
This article examines the acceptance of aquaculture development by residents and visitors of two islands, Cephallonia and Ithaki, in the Ionian Sea, in western Greece. Aquaculture farms have been established recently in both islands, and processing and packaging units in Cephallonia, generating jobs for the local communities and land rents for the villages in the coastal areas near the fish cages. However, the farms and processing and packaging units entail certain negative impacts on the environment. This study reveals that aquaculture farms have found better acceptance in Ithaki, where aqua culture is a form of development suited to this remote, small, predominantly rural island. The degree of acceptability is higher for locals than for tourists, but also for islanders who do not live in the areas where the processing units are situated. Respondents who consider the pollution of the marine environment by the farms to be high, mostly locals and residents of the villages in the vicinity of the aquaculture infrastructure or the main cities in the islands, are more likely to express a negative attitude toward aquaculture and its further development.
Shrimp farming in Bangladesh has been expanded rapidly following huge demand in the international market. This fast development is however accompanied by lack of adequate planning and regulation at the national policy level. This unplanned and haphazard shrimp farming is gathering considerable debate due to its negative environmental and socio-economic consequences. This paper first investigates the nature of adverse impacts of unregulated shrimp farming in the coastal region of the country. In that respect, the article makes a thorough evaluation of existing regulatory and institutional framework regarding shrimp farming in Bangladesh. Ultimately, the paper argues that a paradigm shift is required from the present sectoral approach of resource management. Finally, it recommends to pursue a holistic approach together with integration of Integrated Coastal Zone Management (ICZM) principles into national laws and policies for sustainable shrimp farming in Bangladesh.
Geographic Information Systems (GIS) capability to link spatial analysis and ecological theory is gaining increased attention in the area of Ecology and Conservation Biology, as the continue pressure of human activities on the environment is leading to habitat destruction and extinctions and therefore there is a need to model current and future species distribution. In this work we employ a simple measure, used before in Remote Sensing and Anthropology, to model the distribution species based on presence only data. This measure, called Mahalanobis Typicalities, is derived from the Mahalanobis Distance and expresses the probability of finding a pixel with a Mahalanobis Distance greater than or equal to that of the pixel being evaluated, in other words, it tells us how typical is the area being analyzed compared to those used as a reference. Virtual species were used in order to have perfect control of the predictive power of the method under different species response curves to environmental gradients. Performance of this technique was compared to other presence-only species distribution methods, such as Maximum Entropy, Genetic Algorithm for Rule-set Production, Ecological Niche Factor Analysis, BIOCLIM and DOMAIN. Results shows the high power of the model to predict both habitat suitability and presence-absence for normal, skewed and mixed species responses to environmental gradients as well as a low performance of all methods to predict under bimodal responses to environmental gradients.
A system is provided to aid in site selection and design for aquaculture ponds. This technique is based on similar systems used in evaluating soils for use in agriculture, road construction, waste disposal, residential development, etc. Information necessary for decision making has been system-atized in tabular form giving limitation ratings (slight, moderate or severe) and restrictive features for each important soil or water property.
