Habitat Distribution Research Articles

Transferability of tsetse habitat models between different regions in Kenya and Rwanda

Accurate and reliable information on the distribution of tsetse habitats is crucial for the effective management of African Trypanosomiasis in sub-Saharan Africa. However, conducting large-scale surveillance of tsetse flies to develop distribution maps is impractical due to vast areas infested and limited resources available. To address this challenge, we evaluated the applicability of tsetse habitat models developed in the intensively sampled Shimba Hills National Reserve in Kenya for both the wet and the dry season, to two other regions in Kenya (Ruma National Park and Nguruman Conservancy) and one region in Rwanda (Akagera National Park). The models utilized satellite-based estimates of vegetation greenness, land cover, and land surface temperature, combined with tsetse occurrence data, to predict habitat suitability. An independent dataset of tsetse occurrence was used to benchmark the performance of the transferred models. The performance of the transferred models was significantly influenced by the similarity in environmental conditions between the model's development area and the transfer area. In regions with high dissimilarity, such as Nguruman Conservancy during the dry season, model transfer was unsuccessful with an F1-score of zero. In all other regions and seasons, the transferred models showed satisfactory performance, with F1-score values exceeding 0.65. Nevertheless, site-specific models outperformed (>0.8 F1-score) the transferred models, indicating that models specifically developed with data for each location can provide more accurate information on tsetse distribution. In conclusion, our study demonstrates that tsetse habitat models can be transferred with relatively good accuracies to seasons and regions that exhibit environmental similarity with the model training area. Despite the higher accuracy of site-specific models, transferring models to similar sites remains a meaningful exercise in the absence of detailed surveillance data.

Characterizing Håkon Mosby Mud Volcano (Barents Sea) cold seep systems by combining ROV-based acoustic data and underwater photogrammetry

Cold-seeps have a unique geo-ecological significance in the deep-sea environment. They impact the variability of present-day submarine sedimentary environments, affecting the evolution of the landscape over time and creating a variety of submarine landforms, one of which is Mud Volcanoes (MVs). MVs form due to the extrusion of mud, fluids, and gas, mainly methane, from deeper sedimentary layers. These natural gas seepage systems could significantly affect climate change and the global carbon cycle. We present a comprehensive method that combines ROV-based multibeam mapping and underwater photogrammetry to enhance the understanding of the physical relationships between geomorphic units characterizing the Håkon Mosby Mud Volcano (HMMV) and the distribution of associated habitats. HMMV is indeed characterized by high thermal and geochemical gradients from its center to the margins resulting in a clear zonation of chemosynthetic communities. Our approach integrates multi-resolutions and multi-sources data acquired using a work-class ROV. The ROV-based microbathymetry data helped to identify the different types of fine-scale submarine landforms in the central part of HMMV. This revealed three distinct geomorphic units, with the central hummocky region being the most complex. To further study this area, ROV images were analyzed using a defined Structure from Motion workflow producing millimetric resolution 2D and 3D models. Object-Based Image Analysis (OBIA), applied on orthomosaics, allowed us to obtain a fine classification of main benthic communities covering a total area of 940m2, including the active seepage area of the hummocky rim. Four major substrate types were identified in these regions: uncovered mud, bacterial mats high-density, bacterial mats low-density, sediments and tubeworms. Their relationship with terrain morphology and seepage activity were investigated at different spatial scales, contributing to a deeper understanding the ecological functioning of cold seep ecosystems in MVs. The applied workflow is proposed as an innovative processing technique for future studies on cold-seep systems. Geomorphic and ecological processes in extreme environments are inherently linked and marked by spatial patterns typifying associated habitats and sedimentary environments. This is poorly investigated in previous studies, leaving a substantial gap in the geomorphological drivers responsible for habitat distribution and extent in cold seep systems.

A global analysis reveals a collective gap in the transparency of offset policies and how biodiversity is measured

AbstractOffsetting policies have increased worldwide, utilizing a range of biodiversity metrics to compensate for development impacts. We conducted a global analysis of offset legislation by reviewing policies from 108 countries, which have voluntary offsets, or which require offsets by law. We sought to understand how well biodiversity metrics and offset currencies are documented in current policies. Where biodiversity metrics are documented we aimed to understand how metrics were scored, combined, and multiplied to create offset currencies. We found only 22 jurisdictions (from 14 countries) had guidelines documenting how biodiversity should be assessed during offsetting, representing a significant gap in the guidance available for offsets. Of the 22 guidelines, 14 (63%) documented use of aggregated currencies, eight (23%) did not aggregate biodiversity metrics into a single currency, and three (17%) did not specify either approach. Habitat type and condition, as well as area, were widely recommended across policies (>50%). Where species‐level metrics were considered, guidelines generally focused on habitat distributions rather than abundance or population metrics. The lack of consistent and clear guidance about how biodiversity should be measured in offsets reduces our ability to determine the effectiveness of offsets in compensating for development impacts long term.

Habitat Use and Diet Composition of the Common Eland (Tragelaphus oryx) in Ngorongoro Conservation Area, Tanzania

Ngorongoro Conservation Area (NCA) is renowned worldwide for its multiple land use where pastoralism and wildlife conservation co-exist. Thus, the NCA must meet a delicate balance of competing needs between livestock and wildlife. Currently the NCA is conducting resettlement program to facilitate pastoralists who are willing to move and resettle outside of the conservation area in order to reduce the number of people and livestocks in NCA. The common eland (Tragelaphus oryx) are among the large herbivore species found in the NCA that might be affected by possible competition between livestock and wildlife. The information on this species including habitat utilization and feeding ecology is limited. This study therefore, investigated the factors influencing habitat use and diet composition of the common eland (Tragelaphus oryx) in NCA. Data were collected along 82 pre-established transects using direct field survey. The study therefore assessed habitat use, distribution patterns, diet composition and conservation threats facing the common eland in NCA, The results indicated that the grassland habitat was mainly used by elands (> 85% in both dry and wet seasons), while other habitats were least used (< 15%). Eland diet composition varied significantly among plant species, with the animals most frequently feeding on Themeda triandra but rarely on Vachellia tortilis and Hibiscus aponeurus. The study concludes with recommendations for enhancement of grassland habitat management and reduced anthropogenic activities to enhance eland conservation in NCA.

The Minimal Impact of Anthropogenic Disturbances on the Spatial Activities of Leopard Cats in Xinlong, China.

The habitat plays a crucial role in ensuring the survival of wildlife. However, the increasing disturbances caused by human activities present a substantial threat to habitats, especially for species such as the leopard cat (Prionailurus bengalensis), which is a significant small predator. Currently, research on leopard cats predominantly focuses on low-altitude regions within its distribution range, leaving plateau areas understudied. To enhance our understanding of the impact of human disturbances on leopard cat habitats, we undertook a study employing infrared camera trappings to monitor leopard cats' activity in Xinlong of southwestern China between 2015 and 2023. We analyzed the spatial distribution and habitat suitability of the leopard cats by utilizing ensemble species distribution models (ESDMs). Moreover, we employed two-species occupancy models to investigate the spatial interaction between leopard cats and human disturbances. The results indicated that (1) the potential suitable habitat area for leopard cats encompassed approximately 1324.93 km2 (14.3%), primarily located along the banks of Yalong river. (2) The distribution of suitable habitat was predominantly influenced by competitors, specifically the yellow-throated marten (YTM), accounting for 52.4% of the influence, as well as environmental factors such as distance to water (DTW) at 12.0% and terrain roughness index (TRI) at 10.0%. Human interference, including cattle presence (4.6%), distance to road (DTD, 4.9%), and distance to settlement (DTS, 3.5%), had a limited impact on the habitat distribution. (3) Within a 5 km radius, habitat suitability increased with proximity to human settlements. (4) Leopard cats exhibited spatial independence from humans and domestic cattle (species interaction factor (SIF) = 1.00) while avoiding domestic horses (SIF = 0.76 ± 0.03). The relatively minor impact of human disturbances in Xinlong could be attributed to traditional cultural practices safeguarding wildlife and the leopard cat's environmental adaptability. We recommend establishing a novel conservation paradigm based on the living dynamics of wildlife communities in Xinlong, thereby offering a more targeted approach to biodiversity preservation in the future.

Domains of scale in cumulative effects of energy sector development on boreal birds

ContextIndustrial development in Canada’s boreal forest creates cumulative environmental effects on biodiversity. Some effects may be scale-dependent, creating uncertainty in understanding and hindering effective management.ObjectivesWe estimated cumulative effects of energy sector development on distributions of sixteen migratory songbird species at multiple spatial scales within the boreal region of Alberta, Canada, and evaluated evidence for scale domains in species responses.MethodsWe used a hierarchical, multi-scale sampling and modelling framework to compare effects of oil and gas footprint on songbirds at five spatial scales. We used Bayesian Lasso to facilitate direct comparison of parameter estimates across scales, and tested for differences in grouped parameter estimates among species.ResultsWe found consistent scale-dependent patterns across species, showing variable responses to development occurring at the smallest scale, little effect at intermediate scales, and stronger, mainly positive effects at the largest scales. Differences in grouped parameter estimates across scales showed strong evidence for scale domains in the response of songbirds to energy sector development.ConclusionsWe concluded that variable effects at the smallest scale represented individual habitat selection, while larger scale positive effects reflected expanding distributions of open habitat- and disturbance-associated species in areas of high oil and gas footprint. Our results show that single-scale analyses do not reflect population processes occurring at other scales. Future research on linking patterns at different scales is required to fully understand cumulative effects of land use change on wildlife populations.

Predicting the geographical distribution of the Persian leopard, Panthera pardus tulliana, a rare and endangered species

The endangered Persian Leopard, Panthera pardus tulliana, is a top predator and keystone species whose small, fragmented population is still distributed across the Zagros Mountain regions of northeastern Iraq. Their population is under threat from habitat loss and fragmentation, illegal hunting, prey depletion, minefields, and conflicts with humans. Conservation efforts require accurate information on the current and future distribution patterns of this species. Therefore, this study aimed at establishing new baseline data based on the maximum entropy model (Maxent) combined with GIS techniques, field surveys (i.e., camera traps, kill reports, carcasses), and relevant environmental variables obtained from multiple sources. Modeling demonstrated that the current suitable habitat distribution of the species comprises 12.4 % (6318 km2) of the total area of the study area (50971 km2). Of these suitable areas, 0.8 % (431 km2) were categorized as high suitable, 3.8 % (1935 km2) as medium suitable, and 7.8 % (3953 km2) as low suitable. Overall, as demonstrated by modeling under the preselected environmental predictors, the suitable habitat distribution of the Persian Leopard would contract by 1.3 % (666 km2) and 1.7 % (843 km2) in 2070 under the RCP2.6 and RCP8.5 climate change scenarios, respectively. There would be a latitudinal shift, and the distance between the current and future centroids would be around 43.492 km. This spatial shift would be mostly towards the Zagros Mountains in the northeast of Iraq, alongside the Iran-Iraq border. The most important variables that contributed significantly to the distribution of the species across the study area included slope (47.3 %), temperature seasonality (bio4) (27.9 %), land cover (7.7 %), human population density (4.2 %), soil pH (2.7 %), temperature (Bio2) (2.7 %), and NDVI (1.8 %). These results could have great implications for establishing strategic protected areas not only for the target species of this study but for a wide range of plant communities and prey species (e.g., goats, wild boar) across the mountain ecosystem.

Extending the interpretation of Natura 2000 habitat types beyond their definition can bias their conservation status assessment: An example with species-rich Nardus grasslands (6230*)

In this study, taking as an example the species-rich Nardus stricta grasslands (habitat 6230*) within the Natura 2000 network of the Lombardy region (northern Italy, central southern Alps), we evaluated i) whether the spatial distribution of the habitat 6230* corresponded to essential features for its identification, and ii) whether a broad habitat interpretation could affect its regional conservation status assessment.We analysed the spatial distribution of habitat 6230* regarding the elevation, geological substrate, forest treeline, land use types and other habitat types. Using the regional database of habitat relevés, we calculated the threshold values of conservation status for a range of indicators of structure, functions and future prospects. To this end, we used a subset of relevés of the subalpine sub-type of habitat 6230*, as it corresponds to plant communities where habitat interpretation can easily be extended beyond its definition.The mapped distribution of habitat 6230* did not entirely match the essential features required for its identification. Some polygons were located at the ecological extremes of habitat 6230*, on carbonate substrates and in the alpine belt. In those conditions, the habitat showed an Unfavourable-bad (U2) conservation status, decreasing species richness and typical species dominance and frequency. Our findings highlighted that plant communities representing ecological extremes of the habitat type 6230* should no longer be referred to the same habitat type.The proposed indicators can help identify habitat sub-types more conducive to successful restoration measures, thereby ensuring favourable conservation status. In turn, this guarantees sustainable agricultural land use, which simultaneously promotes biodiversity and high-quality food products. Furthermore, the procedure could be extended to other habitat types for early identification of priority monitoring areas, especially when their interpretation has gone beyond their definition, with little consideration given to the consequences on the regional conservation status assessments.

Estimation of habitat suitability and landscape connectivity for Liaoning and Jilin clawed salamanders (Hynobiidae: Onychodactylus) in the transboundary region between the People’s Republic of China and the Democratic People’s Republic of Korea

Human activities and climate change have caused damage to the natural world, leading to increased attention on habitat protection. However, most conservation efforts focus on flagship species, while many other species lack protection and are gradually becoming extinct due to the lack of conservation efforts and public attention. The Liaoning clawed salamander (Onychodactylus zhaoermii) and the Jilin clawed salamander (Onychodactylus zhangyapingi) are two amphibians endemic to Northeast Asia, but they have not received enough conservation attention, and little is known about their distribution. In this study, we collected field survey and literature data for both species to obtain data on occurrence, and constructed ecological niche models (ENMs) to understand their suitable habitat and potential distribution. The ENMs revealed that the suitable habitat of O. zhangyapingi was primarily located within the Yalu River basin, as well as western and eastern mountains of the Democratic People’s Republic of Korea (DPR Korea). On the other hand, the suitable habitat for O. zhaoermii was mainly distributed in the Xiuyan area of Liaoning in China, the Changbai Mountains, and north of the Tumen River basin. Although there is currently no direct evidence of the species’ presence in DPR Korea, the ENM results support their putative presence in the nation, as there are large patches of suitable habitat. In addition, the connectivity model showed the presence of transboundary corridors between patches of suitable habitat, with some nodes (here defined as continuous patches of habitat enabling connection between suitable habitats) located in multiple provinces or within different countries. In addition, the two nodes with the lowest resistance distance value were contiguous with the nodes along the corridors. In our evaluation of the transboundary corridors in the eastern and western parts of the study area, we found that the surfaces located downstream along the Tumen River showed a better quality for corridor. However, the gradual fragmentation and disappearance of the landscape may lead the two species to extinction. Therefore, we recommend establishing a transboundary amphibian protection network in the China-DPR Korea river basin and encouraging collaborations for amphibian surveys and applied conservation projects in the Tumen River basin.

Assessment Heartworm Disease in the Canary Islands (Spain): Risk of Transmission in a Hyperendemic Area by Ecological Niche Modeling and Its Future Projection.

Heartworm disease is a vector-borne zoonotic disease caused by Dirofilaria immitis. The Canary Islands (Spain), geolocated close to the coast of Western Sahara, is an archipelago considered hyperendemic where the average prevalence in domestic dogs is high, heterogeneous, and non-uniform. In addition, Culex theileri has been reported as a vector of the disease on two of the most populated islands. Our aim was to develop a more accurate transmission risk model for dirofilariosis for the Canary Islands. For this purpose, we used different variables related to parasite transmission; the potential distribution of suitable habitats for Culex spp. was calculated using the ecological niche model (ENM) and the potential number of generations of D. immitis. The resulting model was validated with the geolocation of D. immitis-infected dogs from all islands. In addition, the impact of possible future climatic conditions was estimated. There is a risk of transmission on all islands, being high in coastal areas, moderate in midland areas, and minimal in higher altitude areas. Most of the dogs infected with D. immitis were geolocated in areas with a high risk of transmission. In 2080, the percentage of territory that will have been gained by Culex spp. is small (5.02%), although it will occur toward the midlands from coastal areas. This new model provides a high predictive power for the study of cardiopulmonary dirofilariosis in the Canary Islands, as a hyperendemic area of the disease, and can be used as a tool for its prevention and control.

Prediction of suitable planting areas of Rubia cordifolia in China based on a species distribution model and analysis of specific secondary metabolites

The expansion or reduction of suitable habitats for medicinal plants may result from climate change. There are few reports on the distribution of suitable habitats or potential origins of Rubia cordifolia L., a relatively common herb. However, due to its important pharmacological properties, it is essential that high-quality R. cordifolia can be provided in the future. Therefore, this study combined the biomod2 ensemble platform and the secondary metabolites of R. cordifolia roots to predict its suitable habitats and potential planting areas. Root samples and occurrence data were gathered through fieldwork and public databases. Ultra high-performance liquid chromatography was used to measure the concentrations of two important secondary metabolites in the roots. According to the findings, appropriate habitats covering an area of 2,706,795 km2 were found in various regions, primarily in the eastern and southern parts of China. Under future climate scenarios, suitable habitats shrank inward or expanded outward along the current suitable habitats. Additionally, purpurin was extensively spread, and mollugin was narrowly distributed within the suitable habitats, resulting in dispersed and restricted potential planting areas (893,116 km2). In addition, the precipitation of the wettest month is crucial for distributing suitable habitats and the synthesis of two secondary metabolites. However, there is a risk of losing suitable planting areas for R. cordifolia due to future climate scenarios. Therefore, effective conservation and management measures are urgently needed. In conclusion, the findings of this study may serve as a guide for choosing appropriate planting areas for R. cordifolia.

Future distribution patterns of nine cuttlefish species under climate change

While most coastal communities are expected to, or have been, negatively impacted by climate change, cephalopods have generally thrived with shifting ocean conditions. However, whilst benefitting from the same physiological flexibility that characterizes cephalopods in general, cuttlefish have depth constraints imposed by the presence of a cuttlebone and are limited to specific locations by their particularly low vagility. To evaluate the potential effects of marine climate change on cuttlefish, Species Distribution Models (SDM) were applied to nine species of genus Sepiidae to assess potential changes to their future distribution (2050 and 2100), under four representative concentration pathway (RCP) scenarios (i.e., RCP 2.6, 4.5, 6.0, and 8.5; CMIP5). We show that future cuttlefish habitat suitability and distribution will potentially decrease. The species with the most extreme impacts, Doratosepion braggi (Verco, 1907), was observed to decline as much as 30.77% in average habitat suitability (from present 55.26% to 24.48% at RCP 8.5 in 2100), to Sepia officinalis Linnaeus, 1758 with a low maximum decrease of 1.64% in average habitat suitability (from present 59.62% to 57.98% at RCP 8.5 in 2100). Increases in habitat suitability were projected mostly at higher latitudes, while habitat decrease was predicted for the tropical regions and lower latitudinal limits of species’ distributions. As their habitats decrease in terms of habitat suitability, cuttlefish may not benefit from future changes in climate. Additionally, as potential “sea canaries” for coastal ecosystems, we may see many species and habitats from these systems affected by climate change, particularly in tropical regions.

Impacts of Climate Changes on Geographic Distribution of Primula filchnerae, an Endangered Herb in China.

Primula filchnerae, an endangered plant endemic to China, has drawn people's attention in recent years due to its ornamental value in flower. It was rarely recorded since being described in 1902, but it was rediscovered in 2009 and is now known from a limited number of sites located in Hubei and Shaanxi Provinces. Since the species is still poorly known, a number of unanswered questions arise related to it: How has P. filchnerae responded to past climate change and how might it respond in the future? Why was P. filchmerae so rarely collected during the past century? We assembled geographic coordinates for P. filchnerae through the field surveys and website searches, and then used a maximum entropy model (MaxEnt) to simulate its potential suitable distribution in six periods with varied carbon emission levels by combining bioclimatic and environmental factors. MaxEnt showed that Min Temperature of the Coldest Month (bio6) and Precipitation of the Coldest Quarter (bio19) affected P. filchnerae's distribution most, with an aggregate contribution >60% and suitable ranges above -5 °C and below 40 mm, respectively. We also analyzed potential habitat distribution in various periods with differing impacts of climate change compared to today's suitable habitats, and in most cases, Shaanxi and Sichuan remained the most stable areas and with possible expansion to the north under various carbon emission scenarios, but the 2050s SSP5-8.5 scenario may be an exception. Moreover, we used MaxEnt to evaluate population shifts, with various scenarios indicating that geometric center would be concentrated in Sichuan Province in China. Finally, conservation strategies are suggested, including the creation of protected areas, long-term monitoring, raising public awareness of plant conservation, situ conservation measures, assisted migration, and species introduction. This study demonstrates how P. filchnerae may have adapted to changes in different periods and provides a scientific basis for germplasm conservation and management.

Research on a Multi-Species Combined Habitat Suitability Assessment Method for Various Fish Species

To reveal the evolution of habitat distribution for multiple fish species in the lower reaches of the Gongzui Hydropower Station, this study conducted a catch survey to determine the target species of the reach. Based on their suitability curves, a combined suitability assessment model for multiple fish species was constructed. The reliability of the model was verified by combining acoustic observations of flow fields and fish distribution in specific flow conditions. A two-dimensional hydrodynamic model was coupled to quantitatively analyze the distribution characteristics of fish habitat patches under different flow conditions. The results indicate that the correlation coefficient between the multi-species comprehensive suitability index and the number of fish is 0.676, which indicates that the model can better evaluate the distribution of multiple fish habitats in the study river reach; the weighted usable area (WUA) decreased as the discharge increased; from low flow condition (<800 m3/s) to high flow condition (>2000 m3/s), the patch area of suitable habitat decreased from 11,424 m2 to 1268 m2, and the connectivity between patches also showed a downward trend; and the habitat shifted to the near-shore area of the downstream wider and shallower section, which was highly correlated with the migration process of low-depth and low-velocity areas. The model proposed in this study can establish a rapid response between the suitable habitat distribution of multiple fish species and discharge conditions, which can provide a research method for quantitative evaluation of multi-species habitats in river, and make a significant contribution to the sustainable development of riverine fisheries resources and river water ecology.

Unraveling the functional dark matter through global metagenomics.

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

Deep Learning in Chinese Text Information Extraction Model for Coastal Biodiversity

In the coastal areas of China, scientists have collected nearly 500 species of coastal plants and seaweeds. The collected information includes species description, morphological characteristics, habitat distribution and resource value of plants in China. By effectively extracting Chinese text information, this article establishes a Chinese text information extraction model based on DL. This article is based on short-term and short-term memory artificial neural networks for short text classification. In addition, this article also integrates the L-MFCNN models of MFCNN for short text classification. Comparing the two methods with traditional text recognition algorithms, information extraction based on syntax analysis and deep learning, the results show that, compared with the comparison method, the recognition accuracy of Chinese text information of this neural network model can reach 96.69%. Through model training and parameter adjustment, Chinese text information of coastal biodiversity can be quickly extracted, and species categories or names can be identified.

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes.

The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

Assessing fish–fishery dynamics from a spatially explicit metapopulation perspective reveals winners and losers in fisheries management

Abstract Sustainable management of living resources must reconcile biodiversity conservation and socioeconomic viability of human activities. In the case of fisheries, sustainable management design is made challenging by the complex spatiotemporal interactions between fish and fisheries. We develop a comprehensive metapopulation framework integrating data on species life‐history traits, connectivity and habitat distribution to identify priority areas for fishing regulation and assess how management impacts are spatially distributed. We trial this approach on European hake fisheries in the north‐western Mediterranean, where we assess area‐based management scenarios in terms of stock status and fishery productivity to prioritize areas for protection. Model simulations show that local fishery closures have the potential to enhance both spawning stock biomass and landings on a regional scale compared to a status quo scenario, but that improving protection is easier than increasing productivity. Moreover, the interaction between metapopulation dynamics and the redistribution of fishing effort following local closures implies that benefits and drawbacks are heterogeneously distributed in space, the former being concentrated in the proximity of the protected site. A network analysis shows that priority areas for protection are those with the highest connectivity (as expressed by network metrics) if the objective is to improve the spawning stock, while no significant relationship emerges between connectivity and potential for increased landings. Synthesis and applications. Our framework provides a tool for (1) assessing area‐based management measures aimed at improving fisheries outcomes in terms of both conservation and socioeconomic viability and (2) describing the spatial distribution of costs and benefits, which can help guide effective management and gain stakeholder support. Adult dispersal remains the main source of uncertainty that needs to be investigated to effectively apply our model to fisheries regulation.

Simulation and analysis of red-crowned crane habitat suitability using maximum entropy and information entropy models

The red-crowned crane (Grus japonensis) is a rare waterfowl species that is sensitive to environmental changes in its habitat selection; as such it effectively reflects the variation in wetland landscapes. Therefore, analysis of the habitat suitability for the red-crowned crane can be used to determine the species requirements and to predict its potential habitat distribution, thereby providing a basis for the protection of wetlands and endangered species. In this study, the Landsat satellite remote sensing data of Zhalong Wetland from 1996 to 2019 were used to simulate the nest coordinates of red-crowned cranes using a binary logistic model and to simulate the distribution of suitable habitat via a maximum entropy model. Moreover, an information entropy model was used to examine the yearly changes in habitat suitability and the underlying mechanisms and influencing factors. These two entropy models were combined to simulate the habitat suitability distribution and variation with high accuracy, determine the contribution rates of influencing factors, and provide data for analyzing interannual changes. The following results were obtained. First, the habitat suitability was highest in the center, core area and decreased towards the periphery of Zhalong Wetland. Second, the habitat suitability increased in some regions in the south, decreased in some areas in the north, and remained unchanged in the majority of the peripheral regions. Third, habitat suitability was primarily impacted by landscape patterns, distances to rivers and ditches, and vegetation. Red-crowned cranes preferred to reside far from human disturbance in wetlands near rivers with reeds (Phragmites australis) as the dominant species.

Using regional‐scale predictive habitat models to assess protection and identify potential locations for additional management or monitoring for a species of conservation interest

Abstract Marine protected areas (MPAs) and associated management measures are being implemented to conserve marine benthic species. To make effective decisions, marine managers need data on the distributions of species of interest and anthropogenic pressures, but also the potential connectivity between habitat patches. To explore how predictive modelling can be utilized in such a process, a model was developed to predict the distribution of northern sea fan, Swiftia pallida, habitat around parts of Scotland, Northern Ireland, and Ireland. The predicted distribution of suitable habitat was compared with spatial data on mobile bottom‐contacting fishing activity, and the location of MPAs designated for benthic features, and the management measures within MPAs that restrict mobile bottom‐contacting fishing activity, which is the main pressure‐causing activity that S. pallida are sensitive to. Over 20% of predicted suitable habitat is within MPAs, over 10% is within MPA management measures and over 48% is within areas that have experienced no bottom contacting‐fishing activity, which is significantly higher than the equivalent values for the study region as a whole. However, patches were identified that potentially experience above average levels of fishing activity and remain unmanaged, including within MPAs designated for associated features. The analysis also highlighted patches that could be candidates for monitoring recovery and the locations of unknown populations. For each patch of suitable habitat, the number of other patches within 22 km, a previously published estimate of dispersal distance for S. pallida, was used as a proxy for connectedness. Connectedness was estimated to be greatest for patches towards the centre and west of the study region. The results indicate how the outputs of predictive distribution models can be used in conjunction with other data to prioritize areas for surveys and identify locations where effective management may facilitate conservation or the recovery of benthic species.