In the present work we focus on the distribution of two species of sponges. One of these is Asconema setubalense, a sponge found in rocky substrate that was sampled with a photogrammetric vehicle through georeferenced images. The other is Pheronema carpenteri, which inhabits soft bottoms and was sampled by beam trawl. For the spatial distribution modeling of both sponges, the geomorphological variables of depth, slope, broad and fine scale bathymetric position index (BPI), aspect, and types of bottoms were used, all with a resolution of 32 m. Additionally, layers of silicates and currents near the bottom were extracted from Copernicus Marine Environment Monitoring Service (CMEMS), with a resolution of ∼4 and ∼9 km, respectively. Due to the low resolution of the layers, it was considered necessary to validate their use by model comparison, where those that included these variables turned out to be more explanatory than the others. The models were developed in a complex continental break of the Central Cantabrian Sea, which comprises several submarine canyons and a seamount (Le Danois Bank). On the one hand, a very high resolution (32 m) spatial distribution model based on A. setubalense presence was developed using the MaxEnt maximum entropy model. On the other, depending on the availability of density data, generalized additive models (GAMs) were developed for P. carpenteri distribution, although in this case the sampler only allowed a maximum resolution of almost 1 Km. For the A. setubalense, the variables that best explained their distribution were ground types and depth, and for P. carpenteri, silicates, slope, northness, and eastward seawater velocity. The final model scores obtained were an AUC of 0.98 for the MaxEnt model, and an R squared of 0.87 for the GAM model.

在当前的工作中，我们重点介绍两种海绵的分布。其中之一是乌头Asconema，这是在岩石基质中发现的海绵，用摄影测量工具通过地理参考图像对其进行了采样。另一个是费氏木匠，它居住在柔软的底部，并通过光束拖网进行采样。对于两种海绵的空间分布建模，均使用了深度，坡度，宽和细尺度测深位置指数（BPI），纵横比和底部类型的地貌变量，所有分辨率均为32 m。此外，从哥白尼海洋环境监测局（CMEMS）提取了硅酸盐层和底部附近的洋流，其分辨率分别为〜4 km和〜9 km。由于这些层的分辨率较低，因此认为有必要通过模型比较来验证其用途，其中包含这些变量的层比其他层更具解释性。这些模型是在坎塔布连海中部复杂的大陆断裂中开发的，该断裂包括几个海底峡谷和一个海山（Le Danois银行）。A.setubalense存在是使用MaxEnt最大熵模型开发的。另一方面，根据密度数据的可用性，开发了通用加性模型（GAM）卡彭特里分布，尽管在这种情况下，采样器仅允许将近1 Km的最大分辨率。为了A.setubalense，最能解释其分布的变量是地面类型和深度，对于 卡彭特里，硅酸盐，坡度，北部和东部海水速度。获得的最终模型得分是MaxEnt模型的AUC为0.98，GAM模型的R平方为0.87。