Despite their innumerous and profound environmental impacts agricultural landscapes provide complementary conservation to a relevant part of the biota, including endangered, damaging, and valuable species, as well as populations which do not fit any of those categories. Monitoring is the major demand of wildlife management in human-altered environments. However, like any other field of knowledge, biodiversity monitoring still has conceptual, technological, and societal limitations. Conceptual framework still needs improvement in the number and nature of indicators, as well as the spatiotemporal dimensions of patterns and processes to be monitored. In addition, technological innovations are still needed for both sampling and analytical methodology, including statistical models and algorithms designed to accommodate low detectability, many heterogeneous sources of variation, spatiotemporal autocorrelation, and data scarcity. Although wildlife monitoring in multifunctional agricultural landscapes can provide a direct measure of their conservation value, there are still some societal constraints regarding the tangibility of such value, as well as who should pay for it. This realism is central to this book’s broader aim: to propose a long-term protocol for wildlife monitoring that can operate under real-world constraints, while still yielding meaningful ecological inferences.