Spatial Modelling Approaches for Estimating Richness of Benthic Invertebrates Throughout New Zealand Waters

Diversity and Distributions, Год журнала: 2025, Номер 31(2)

Опубликована: Фев. 1, 2025

ABSTRACT Aim Understanding the distribution of marine biodiversity is critical for evidence‐based identification areas protection and restoration. Taxonomic richness a key, intuitive component often used to guide spatial planning protection. In this study, we explore relative merits two modelling approaches, stacked species models (S‐SDMs) macro‐ecological (MEMs), mapping benthic invertebrate taxa. Location New Zealand Exclusive Economic Zone. Methods Two hundred seven individual layers from SDMs genera were pooled an existing database create single layer. The same occurrence data develop SDMs, comprising over 120k occurrences, was fit MEMs using ensemble approach. Results S‐SDM layer performed poorly when validated against observed richness, while MEM approach well. While there some consistencies in predicted as high substantial differences between methods also apparent, with seemingly better able discern nuanced, fine‐scale patterns richness. Areas by include parts Chatham Rise, large sub‐Antarctic region, continental‐shelf coastal habitat south South Island, north‐east coast North around East Cape Kermadec, Lau‐Colville Macquarie Ridges. Main Conclusions Spatial catchability biases underlying may contribute poor performance suggest not be appropriate datasets limited systematic sampling. predictions provide best available information waters thus offer important current future processes.

Язык: Английский

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Comparative Analysis of MaxEnt and Deep Learning Approaches for Modeling Humpback Whale Distribution in North Iceland

Ecology and Evolution, Год журнала: 2025, Номер 15(3)

Опубликована: Март 1, 2025

In this study, we compared the established MaxEnt and a more novel deep learning approach for modeling distribution of humpback whales (Megaptera novaeangliae) in north Iceland. We examined mechanisms, structures, optimization techniques both approaches, highlighting their differences similarities. Monthly models Skjálfandi Bay were created, from 2018 until 2021, using presence-only sighting data satellite remote sensing data. Search efforts boat tracklines utilized to create pseudo-absence points models. Additionally, trained used projections year 2022, solely based on available environmental results area under curve value. The findings indicate that approaches have limitations advantages. does not allow continuous updating within time series, yet it mitigates risk overfitting by employing maximum entropy principle. model is likely overfit, but larger weight network increases model's capability capture complex relationships patterns. Ultimately, show had higher predictive performance current future whale distributions. Both inherent limitations, such as low resolution input data, spatial biases, inability fully entire complexity natural processes. Despite this, showed promising prompts further research different study areas applications other mobile animal species.

Язык: Английский

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Development of a Seafloor Community Classification for the New Zealand Region Using a Gradient Forest Approach

Frontiers in Marine Science, Год журнала: 2022, Номер 8

Опубликована: Янв. 14, 2022

To support ongoing marine spatial planning in New Zealand, a numerical environmental classification using Gradient Forest models was developed broad suite of biotic and high-resolution predictor variables. modeling uses species distribution data to control the selection, weighting transformation predictors maximise their correlation with compositional turnover. A total 630,997 records (39,766 unique locations) 1,716 taxa living on or near seafloor were used inform 20 gridded variables represent patterns turnover four groups overall community. Compositional community classified hierarchical procedure define at different levels detail. The 75-group level assessed as representing highest number that captured majority variation across Zealand environment. We refer this “Seafloor Community Classification” (SCC). Associated uncertainty estimates for each also produced, an added measure – coverage space further highlight geographic areas where predictions may be less certain owing low sampling effort. Environmental differences among deep-water SCC relatively muted, but greater evident intermediate depths line well-defined oceanographic observed Zealand’s oceans. became even more pronounced shallow depths, localised conditions such productivity, topography, seabed disturbance tidal currents important differentiating factors. similarities mirrored by biological compositions. is significant advance previous classifications includes substantially wider range than has been attempted previously. critically appraised considerations use management are discussed.

Язык: Английский

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On the rise: Climate change in New Zealand will cause sperm and blue whales to seek higher latitudes

Ecological Indicators, Год журнала: 2022, Номер 142, С. 109235 - 109235

Опубликована: Авг. 2, 2022

Climate impacts affect marine ecosystems worldwide with island nations such as New Zealand being extremely vulnerable because of their socio-economic and cultural dependence on the costal environment. Cetaceans are ideal indicator species ecosystem change ocean health given extended life span cosmopolitan distribution, but limited data availability prevents anticipating in distribution under future climate changes. We projected range shifts a key odontocete mysticete (Physeter macrocephalus Balaenoptera musculus) 2100 relative to present day waters, using an ensemble modelling approach, three scenarios different severity. The results show latitudinal shift suitable habitat for both whale species, increasing magnitude severity sea surface temperature warming. most severe scenario tested generated 61% 42% loss decrease currently sperm blue whales, respectively, mostly Zealand's northern waters. These predicted changes will have strong impact functioning services waters also coastal areas (critical species' foraging survival). Not only do these simulated help identify potential refugia mitigate global warming, they generate socioeconomic consequences relying wildlife tourism, industry, environmental protection.

Язык: Английский

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Assessing the carbon storage value of kelp forest restoration in the Hauraki Gulf Marine Park, New Zealand: Lessons from no-take Marine Protected Areas

Marine Policy, Год журнала: 2023, Номер 154, С. 105682 - 105682

Опубликована: Июнь 1, 2023

Язык: Английский

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Key factors for species distribution modeling in benthic marine environments

Frontiers in Marine Science, Год журнала: 2023, Номер 10

Опубликована: Дек. 4, 2023

Species distribution modeling is a widely used technique for estimating the potential habitats of target organisms based on their environmental preferences. These methods serve as valuable tools resource managers and conservationists, utilization increasing, particularly in marine environments where data limitations persist challenge. In this study, we employed global predictions six cold-water coral species case study to investigate various factors influencing predictions, including algorithms, background points sampling strategies sizes, collinearity datasets, using both discriminative functional performance metrics. The choice method exhibits stronger influence model compared effects point size, dataset. Predictions that utilize kernel density backgrounds, maintain an equal number presences algorithms BRT, RF, MARS, employ substantial MAXENT, coupled with collinearity-filtered dataset modeling, yield higher levels performance. Overall, BRT RF outperformed conclusion further substantiated by analysis smoothed residuals uncertainty associated predicted habitat suitability Madrepora oculata . This offers insights enhancing benthic environments, thereby benefiting management conservation species.

Язык: Английский

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Passive Acoustic Monitoring Reveals Spatio-Temporal Distributions of Antarctic and Pygmy Blue Whales Around Central New Zealand

Frontiers in Marine Science, Год журнала: 2021, Номер 7

Опубликована: Янв. 6, 2021

Effective management of wild animal populations relies on an understanding their spatio-temporal distributions. Passive acoustic monitoring (PAM) is a non-invasive method to investigate the distribution free-ranging species that reliably produce sound. Critically endangered Antarctic blue whales ( Balaenoptera musculus intermedia ) (ABWs) co-occur with pygmy B. m. brevicauda (PBWs) around New Zealand. Nationally, both are listed as “data deficient” due difficulties in access and visual sub-species identification. PAM was used distributions via specific song detections central Propagation models, incorporating ambient noise data, enabled comparison among recording locations different marine environments. ABW peaked during austral winter spring, indicating Zealand, South Taranaki Bight (STB) particular, migratory corridor for ABWs. Some calls were also detected breeding season (September October). PBW highly concentrated STB, particularly between March May, suggesting aggregation PBWs may occur here. Therefore, STB great importance whale. absent from parts but at east coast this time. Detection area models valuable when interpreting comparing locations. The results provide information required critically ABWs highlight relative Zealand

Язык: Английский

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Drivers of Spatial Distributions of Basking Shark (Cetorhinus maximus) in the Southwest Pacific

Frontiers in Marine Science, Год журнала: 2021, Номер 8

Опубликована: Апрель 26, 2021

Basking sharks ( Cetorhinus maximus ) were widely reported throughout New Zealand waters. Once commonly observed, and sometimes in large numbers, basking are now infrequently reported. shark observations known to be highly variable across years, their distribution occurrence have been shown influenced by environmental predictors such as thermal fronts, chl- a concentration, the abundance of prey (zooplankton). Little is South Pacific more information on distribution, habitat use, migratory patterns required better understand species’ regional ecology. Here, we used bootstrapped Habitat Suitability Models [HSM, ensembled from Boosted Regression Tree (BRT) Random Forest (RF) models] determine drivers predict suitability estimated uncertainty for first time. High−resolution (1 km 2 grid resolution) biotic data, including inferred species, all available records Zealand’s Exclusive Economic Zone (EEZ) included ensemble HSMs. The most influential driver modeled was vertical flux particulate organic matter at seabed, which may indicate higher levels primary production surface ocean density mesopelagic zone seafloor. BRT RF models had good predictive power (AUC TSS > 0.7) both performed similarly with low variability model fit metrics. Areas high east west coasts Island, Puysegur Ridge, Auckland Island slope. outputs produced here could incorporated into future management framework assessing threat conservation needs (e.g., spatially explicit risk assessment) this regionally protected well providing guidance research efforts areas interest sampling).

Язык: Английский

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Cetacean conservation planning in a global diversity hotspot: dealing with uncertainty and data deficiencies

Ecosphere, Год журнала: 2021, Номер 12(7)

Опубликована: Июль 1, 2021

Abstract Many cetacean species are at risk from anthropogenic disturbances including climate change, pollution, and habitat degradation. Identifying hotspots for conservation management is therefore required. Aotearoa–New Zealand waters used by 53% of the world’s a global diversity hotspot. Using geographic predictions taxa, we aimed to identify important areas within New using two methods: estimates richness spatial prioritization analysis. For both methods, investigated how varying levels uncertainty in taxa’ occurrence layers would affect our interpretation hotspots. Despite some marked differences distribution diversity, across all scenarios, highlighted six distinct deep offshore regions as habitat. Generally, inshore had lower than areas, but these remain with limited ranges (e.g., endemic Māui Hector’s dolphins), places similar values Furthermore, predicted taxa estimates. The use different allows integration distributional information differing sources (different modeling methods numbers records) be integrated robust conservative way. Identification provides efficient step toward prioritizing participatory process.

Язык: Английский

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