Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-s...Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.展开更多
The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and i...The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index (HSI) model using two potential important environmental variables - sea surface temperature (SST) and sea surface height anomaly (SSHA) - and fishery data from the main fishing ground (165°-180°E) during June and July of 1999-2003. A geometric mean model (GMM), minimum model (MM) and arithmetic weighted model (AWM) with different weights were compared and the best HSI model was selected using Akaike's information criterion (AIC). The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort (CPUE) and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index (SI) regression models were SISST-based = 0.7SIeffort-SST + 0.3 SICPUE-SST, and SISSHA-based = 0.5SIeffort-SSHA + 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISST-based+ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.展开更多
Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine species.The response of species abu...Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine species.The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons.Therefore,it is necessary to determine the optimal combination of environmental variables in HSI modelling.In this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI models.Significant variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017.Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined.Among the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best performance.Four environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis shrimp.The distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were observed.This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.展开更多
We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of imp...We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of importance,are Secchi depth,sediment composition,water temperature,salinity,current velocity,water depth and nutrient quality. Specific factor piecewise functions have been used to transform parameter values into normalized quality indexes. The weight of each factor was defined using expert knowledge and the analytic hierarchy process(AHP) method. All of the data thus obtained were interpolated using the inverse distance weighted(IDW) interpolation method to create maps for the entire region. In this study,the analysis of habitat suitability in the subtidal zone of Xiaoheishan Island was conducted for four seasons. According to the GIS-based HSI model,the optimal habitat of Z ostera marina L. appears in spring,although habitat remains suitable all year round. On the whole,the optimum site for eelgrass restoration is located in the eastern region,followed by the western and southern regions. We believe that the GIS-based HSI model could be a promising tool to select sites for Z ostera marina L. restoration and could also be applicable in other types of habitat evaluation.展开更多
Finding the right balance between timber production and the management of forest-dependent wildlife species,present a difficult challenge for forest resource managers and policy makers in Okinawa,Japan.A possible expl...Finding the right balance between timber production and the management of forest-dependent wildlife species,present a difficult challenge for forest resource managers and policy makers in Okinawa,Japan.A possible explanation of this can be found in the unique nature of the forest management area which is populated with various kinds of rare and endangered species.This issue has been brought to light as a result of the nomination of northern Okinawa Island in 2018 as a candidate for World Natural Heritage site.The nomination has raised public awareness to the possibility of conflicting management objectives between timber extraction and the conservation of habitat for forest-dependent wildlife species.Managing exclusively for one objective over the other may fail to meet the demand for both forest products and wildlife habitat,ultimately jeopardizing the stability of human and wildlife communities.It is therefore important to achieve a better balance between the objective of timber production and conservation of wildlife habitat.Despite the significance of this subject area,current ongoing discussions on how to effectively manage for forest resources,often lack scientific basis to make sound judgement or evaluate tradeoffs between conflicting objectives.Quantifying the effect of these forest management activities on wildlife habitat provides useful and important information needed to make forest management and policy decisions.In this study we develop a spatial timber harvest scheduling model that incorporates habitat suitability index(HSI)models for the Okinawa Rail(Gallirallus okinawae),an endangered avian species found on Okinawa,Japan.To illustrate how the proposed coupling model assembles spatial information,which ultimately aids the study of forest management effects on wildlife habitat,we apply these models to a forest area in Okinawa and conduct a simple simulation analysis.展开更多
The quality of environmental data and its possible impact on the marine species habitat modelling are often overlooked while the sources for these data are increasing.This study selected sea surface temperature(SST)fr...The quality of environmental data and its possible impact on the marine species habitat modelling are often overlooked while the sources for these data are increasing.This study selected sea surface temperature(SST)from two commonly used sources,the NOAA Ocean Watch and IRI/LDEO Climate Data Library,and then constructed habitat suitability index model to evaluate the influences of SST from the two sources on the outcomes of Ommastrephes bartramii habitat models for the months of July–October in the Northwest Pacific Ocean during 1996–2012.This study examined the differences in the amount of estimated unfavourable/favourable habitat area when the SST used for model building and inference were the same or different.Dynamics in suitable habitat area calculated from SST was insensitive to the two different SST products.In the fishing season of O.bartramii,the changes of magnitude and trend of monthly suitable habitat area in August and September were similar over time,whereas there were large differences for July and October.Importantly,there is a substantial lack of consistency in the O.bartramii habitat distribution based on SST of two sources.This study considered the sources of environmental data for habitat modelling and then inferred species habitat distribution whether by the same or different data source.展开更多
The islands and associated back channels on the Ohio River, USA, are believed to provide critical habitat features for several wildlife species. However, few studies have quantitatively evaluated habitat quality in th...The islands and associated back channels on the Ohio River, USA, are believed to provide critical habitat features for several wildlife species. However, few studies have quantitatively evaluated habitat quality in these areas. Our main objective was to evaluate the habitat quality of back and main channel areas for several species using habitat suitability index (HSI) models. To test the effectiveness of these models, we attempted to relate HSI scores and the variables measured for each model with measures of relative abundance for the model species. The mean belted kingfisher (Ceryle alcyon) HSI was greater on the main than back channel. However, the model failed to predict kingfisher abundance. The mean reproduction component of the great blue heron (Ardea herodias) HSI, total common muskrat (Ondatra zibethicus) HSI, winter cover component of the snapping turtle (Chelydra serpentina) HSI, and brood-rearing component of the wood duck (Aix sponsa) HSI were all greater on the back than main channel, and were positively related with the relative abundance of each species. We found that island back channels provide characteristics not found elsewhere on the Ohio River and warrant conservation as important riparian wildlife habitat. The effectiveness of using HSI models to predict species abundance on the river was mixed. Modifications to several of the models are needed to improve their use on the Ohio River and, likely, other large rivers.展开更多
基金supported by the National 863 project (2007AA092201 2007AA092202)+4 种基金National Development and Reform Commission Project (2060403)"Shu Guang" Project (08GG14) from Shanghai Municipal Education CommissionShanghai Leading Academic Discipline Project (Project S30702)supported by the National Distantwater Fisheries Engineering Research Center, and Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, ChinaYong Chen’s involvement in the project was supported by the Shanghai Dongfang Scholar Program
文摘Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.
基金Supported by the PhD Programs Foundation of Ministry of Education of China (No. 20093104110002)the National High Technology Research and Development Program of China (863 Program) (Nos. 2007AA092201, 2007AA092202)+2 种基金the National Natural Science Foundation (No. NSFC40876090)the Shanghai Leading Academic Discipline Project (No. S30702)Y. Chen's involvement in the project was partially supported by the Shanghai Dongfang Scholar Program
文摘The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index (HSI) model using two potential important environmental variables - sea surface temperature (SST) and sea surface height anomaly (SSHA) - and fishery data from the main fishing ground (165°-180°E) during June and July of 1999-2003. A geometric mean model (GMM), minimum model (MM) and arithmetic weighted model (AWM) with different weights were compared and the best HSI model was selected using Akaike's information criterion (AIC). The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort (CPUE) and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index (SI) regression models were SISST-based = 0.7SIeffort-SST + 0.3 SICPUE-SST, and SISSHA-based = 0.5SIeffort-SSHA + 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISST-based+ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.
基金The National Key R&D Program of China under contract No.2017YFE0104400the National Natural Science Foundation of China under contract No.31772852the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)under contract No.2018SDKJ0501-2。
文摘Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine species.The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons.Therefore,it is necessary to determine the optimal combination of environmental variables in HSI modelling.In this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI models.Significant variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017.Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined.Among the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best performance.Four environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis shrimp.The distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were observed.This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.
基金Supported by the Key Laboratory of Marine Ecology and Environmental Science and Engineering,SOA(No.MESE-2013-01)the National Natural Science Foundation of China(No.41206102)the National Marine Public Welfare Research Project(No.201305009)
文摘We present a GIS-based habitat suitability index(HSI) model to identify suitable areas for Zostera marina L. restoration in the subtidal zone of Xiaoheishan Island. The controlling factors in the model,in order of importance,are Secchi depth,sediment composition,water temperature,salinity,current velocity,water depth and nutrient quality. Specific factor piecewise functions have been used to transform parameter values into normalized quality indexes. The weight of each factor was defined using expert knowledge and the analytic hierarchy process(AHP) method. All of the data thus obtained were interpolated using the inverse distance weighted(IDW) interpolation method to create maps for the entire region. In this study,the analysis of habitat suitability in the subtidal zone of Xiaoheishan Island was conducted for four seasons. According to the GIS-based HSI model,the optimal habitat of Z ostera marina L. appears in spring,although habitat remains suitable all year round. On the whole,the optimum site for eelgrass restoration is located in the eastern region,followed by the western and southern regions. We believe that the GIS-based HSI model could be a promising tool to select sites for Z ostera marina L. restoration and could also be applicable in other types of habitat evaluation.
基金supported by a Grant-in-Aid for Scientific Researches (No. 16K12641&17H00806) from the Ministry of Education, Culture, Sports, Science, and technology of Japan
文摘Finding the right balance between timber production and the management of forest-dependent wildlife species,present a difficult challenge for forest resource managers and policy makers in Okinawa,Japan.A possible explanation of this can be found in the unique nature of the forest management area which is populated with various kinds of rare and endangered species.This issue has been brought to light as a result of the nomination of northern Okinawa Island in 2018 as a candidate for World Natural Heritage site.The nomination has raised public awareness to the possibility of conflicting management objectives between timber extraction and the conservation of habitat for forest-dependent wildlife species.Managing exclusively for one objective over the other may fail to meet the demand for both forest products and wildlife habitat,ultimately jeopardizing the stability of human and wildlife communities.It is therefore important to achieve a better balance between the objective of timber production and conservation of wildlife habitat.Despite the significance of this subject area,current ongoing discussions on how to effectively manage for forest resources,often lack scientific basis to make sound judgement or evaluate tradeoffs between conflicting objectives.Quantifying the effect of these forest management activities on wildlife habitat provides useful and important information needed to make forest management and policy decisions.In this study we develop a spatial timber harvest scheduling model that incorporates habitat suitability index(HSI)models for the Okinawa Rail(Gallirallus okinawae),an endangered avian species found on Okinawa,Japan.To illustrate how the proposed coupling model assembles spatial information,which ultimately aids the study of forest management effects on wildlife habitat,we apply these models to a forest area in Okinawa and conduct a simple simulation analysis.
基金The National Key R&D Program of China under contract Nos 2019YFD0901401 and 2019YFD0901404the National Natural Science Foundation of China under contract No.NSFC41876141+1 种基金the Shanghai Science and Technology Innovation Program under contract No.19DZ1207502the Construction and Application of Natural Resources Satellite Remote Sensing Technology System under contract No.202101004。
文摘The quality of environmental data and its possible impact on the marine species habitat modelling are often overlooked while the sources for these data are increasing.This study selected sea surface temperature(SST)from two commonly used sources,the NOAA Ocean Watch and IRI/LDEO Climate Data Library,and then constructed habitat suitability index model to evaluate the influences of SST from the two sources on the outcomes of Ommastrephes bartramii habitat models for the months of July–October in the Northwest Pacific Ocean during 1996–2012.This study examined the differences in the amount of estimated unfavourable/favourable habitat area when the SST used for model building and inference were the same or different.Dynamics in suitable habitat area calculated from SST was insensitive to the two different SST products.In the fishing season of O.bartramii,the changes of magnitude and trend of monthly suitable habitat area in August and September were similar over time,whereas there were large differences for July and October.Importantly,there is a substantial lack of consistency in the O.bartramii habitat distribution based on SST of two sources.This study considered the sources of environmental data for habitat modelling and then inferred species habitat distribution whether by the same or different data source.
文摘The islands and associated back channels on the Ohio River, USA, are believed to provide critical habitat features for several wildlife species. However, few studies have quantitatively evaluated habitat quality in these areas. Our main objective was to evaluate the habitat quality of back and main channel areas for several species using habitat suitability index (HSI) models. To test the effectiveness of these models, we attempted to relate HSI scores and the variables measured for each model with measures of relative abundance for the model species. The mean belted kingfisher (Ceryle alcyon) HSI was greater on the main than back channel. However, the model failed to predict kingfisher abundance. The mean reproduction component of the great blue heron (Ardea herodias) HSI, total common muskrat (Ondatra zibethicus) HSI, winter cover component of the snapping turtle (Chelydra serpentina) HSI, and brood-rearing component of the wood duck (Aix sponsa) HSI were all greater on the back than main channel, and were positively related with the relative abundance of each species. We found that island back channels provide characteristics not found elsewhere on the Ohio River and warrant conservation as important riparian wildlife habitat. The effectiveness of using HSI models to predict species abundance on the river was mixed. Modifications to several of the models are needed to improve their use on the Ohio River and, likely, other large rivers.
