## Materials and methods
### Audio Data  
The audio data for this investigation were taken from the datasets captured by six BeePi monitors. Two BeePi monitors were deployed in Logan, UT, USA (41.7370\({}^{\circ}\) N, 111.8338\({}^{\circ}\) W) and the other two in North Logan, UT, USA (41.7694\({}^{\circ}\) N, 111.8047\({}^{\circ}\) W) from April 2017 to September 2017 in four Langstroth beehives with Italian honey bee colonies. The fifth and sixth BeePi monitors were deployedin Langstroth beehives with two freshly installed Carniolan colonies in Logan, UT, USA (41.7370\({}^{\circ}\) N, 111.8338\({}^{\circ}\) W) from May 2018 to July 2018. In a previous investigation [13], we reported on some advantages and disadvantages of embedding microphones into hive walls and insulating them against propolization with small metallic mesh nets. In this study, the microphones were placed approximately 10 cm above the landing pad with two microphones on each side (see Figure 1). Each monitor saved a 30-s audio wav file every 15 min recorded with the four microphones above the beehives' landing pads and connected to a Raspberry Pi computer. We experimentally found these two parameters (30 s every 15 min) to be a reasonable compromise between the continuity of monitoring and the storage capacity of a Beepi monitor. In a Beepi monitor, all captured data are saved locally either on the Raspberry Pi's sdcard or on a USB storage device connected to the Raspberry Pi. No cloud computing facilities are used for data storage or analysis. Each 30-s audio sample was segmented into 2-s wav samples with a 1-s overlap, resulting in 28 2-s wav samples per one 30-s audio file. Data collection software is written in Python 2.7 [37]. We obtained the ground truth classification by manually labeling 9110 2-s audio samples captured with four Beepi monitors in two apiaries (one in Logan, UT, USA and one in North Logan, UT, USA ) in May and June 2017. The two apiaries were approximately seventeen kilometers apart. The first apiary (apiary 1) was in a more urban environment in Logan, UT, USA. In this apiary, the first monitored beehive (beehive 1.1) was placed next to a garage with a power generator. The second monitored beehive (beehive 1.2) was placed approximately twenty meters west of beehive 1.1 behind a row of aspens and firs where the generator's sound was less pronounced. However, beehive 1.2 was located closer to a large parking lot. Hence, some audio samples from beehive 1.2 contained sounds of car engines and horns. Some samples from beehives 1.1 and 1.2 contained sounds of fire engine or ambulance sirens. In May 2018, two more Langstroth beehives (beehive 1.3 and beehive 1.4) were added to apiary 1 to obtain the validation data for BUZZZ (see below for details). The second apiary (apiary 2) was in a more rural area in North Logan, UT, USA, seventeen kilometers north of apiary 1. In this apiary, we collected the data from two monitored beehives located approximately fifteen meters apart. Each beehive was located next to an unmonitored beehive. The first monitored beehive in apiary 2 (beehive 2.1) was placed close to a big lawn. The lawn was regularly moved by the property owner and watered with an automated sprinkler system. The second monitored beehive in apiary 2 (beehive 2.2) was located fifteen meters west of beehive 2.1, deeper in the backyard where ambient noise (sprinklers, mower's engine, children playing on the lawn, human conversation) was barely audible. The validation dataset of BUZZZ used for model selection was obtained from two Langstroth beehives (1.3 and 1.4) in apiary 1 obtained in May 2018. Figure 1: Four [PERSON] lapel microphones above Langstroth landing pad. The four microphones (two on each side of the pad) are placed approximately 10 cm above the Langstroth landing pad; four microphones are connected to the microphone hub inside the box with the Beepi hardware components placed on top of the hive; the microphones are not affected by rain or snow.