一个空间建模框架，用于不同采样协议的监测调查，以及斯堪的纳维亚中部鸟类丰度的案例研究
A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird abundance in mid-Scandinavia
摘要：
我们提出了一种新的方法来模拟总丰度合并计数数据信息的调查与不同的采样协议。所提出的方法用于挪威和瑞典的国家繁殖鸟类监测计划的数据。每次普查都在每个国家按照两种不同的采样协议收集丰度数据，即这些协议提供来自四种不同采样过程的数据。建模框架假设一个共同的高斯随机场共享的观测和真实的丰度与它们之间的线性或松弛的线性关联。这些模型考虑到了每项取样协议的特殊性，包括影响每项观测过程的条款，即考虑到观测单位和可探测性的差异。贝叶斯推断使用集成嵌套拉普拉斯近似（INLA）和随机偏微分方程（SPDE）方法进行空间建模。我们还提出了一个模拟研究的基础上，从斯堪的纳维亚半岛中部的实证普查数据，以评估模型下的模型误指定的性能。最后，在我们的研究区域在斯堪的纳维亚半岛中部的鸟类的总预期丰度的地图与不确定性估计。
英文摘要：
We present a new methodology to model total abundance by merging count data information from surveys with different sampling protocols. The proposed methods are used for data from national breeding bird monitoring programs in Norway and Sweden. Each census collects abundance data following two different sampling protocols in each country, i.e. these protocols provides data from four different sampling processes. The modeling framework assumes a common Gaussian Random Field shared by both the observed and true abundance with either a linear or a relaxed linear association between them. The models account for particularities of each sampling protocol by including terms that affect each observation process, i.e. accounting for differences in observation units and detectability. Bayesian inference is performed using the Integrated Nested Laplace Approximation (INLA) and the Stochastic Partial Differential Equation (SPDE) approach for spatial modeling. We also present the results of a simulation study based on the empirical census data from mid-Scandinavia to assess the performance of the models under model misspecification. Finally, maps of the total expected abundance of birds in our study region in mid-Scandinavia are presented with uncertainty estimates.
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