Detection of arboreal feeding signs by Asiatic black bears: effects of hard mast production at individual tree and regional scales

Abstract

Arboreal feeding signs are among several field indicators of the use of tree crowns by the Asiatic black bear (Ursus thibetanus) to sit and eat fruit; however, it is unclear which factors influence this sign formation in hard mast species. Here, we investigated the influence of seed production by individual trees and at a regional scale by major hard mast species on the detection of arboreal feeding signs. For 7 years, we quantitatively assessed seed production by 374–481 trees each year of three dominant hard mast species (Quercus crispula, Quercus serrata and Castanea crenata) in the Ashio‐Nikko Mountains of central Japan and checked for the presence or absence of arboreal feeding signs in these trees. We estimated individual tree energy values and regional mast energy values across these three species and evaluated the influence of each factor on the detection probability of arboreal feeding signs. Arboreal feeding signs were more likely in individual trees with larger mast energy values and during poor mast years. There was no difference among species in the relative importance of individual tree energy or regional mast energy. Interaction of factors was also detected: the magnitude of the positive effect of individual tree energy on the detection of arboreal feeding signs was larger in poorer mast years, and the negative effect of regional mast energy was more conspicuous in the case of trees with greater mast energy. Thus, bears may maximize their feeding efficiency on hard mast in various ways, depending on regional mast availability; during poor mast years, bears are more likely to climb trees with higher individual tree energy values and leave arboreal feeding signs. Arboreal feeding signs cannot be used as an indicator of bear density unless both individual tree energy and regional mast energy values are monitored.

Estimating the seasonal energy balance in Asian black bears and associated factors

“…Based on this information, we identified 2006, 2010, and 2012 as poor mast years and 2007, 2008, 2009, 2011, 2013, and 2014 as years with above‐average yield and thus good mast years (Tochigi et al. ). Tochigi et al.…”

“…Tochigi et al. () quantitatively assessed the seed production of 241–304 individual Q. crispula trees over several years in this study area and estimated individual tree energy values and regional mast energy values.…”

“…Because Q. crispula is the most dominant species across a wide elevation range and is reportedly an autumn staple food resource of bears in this area (Kozakai et al 2011), we defined the poor and good mast years based on the acorn production of Q. crispula. Based on this information, we identified 2006, 2010, and 2012 as poor mast years and 2007, 2008, 2009, 2011, 2013, and 2014 as years with above-average yield and thus good mast years (Tochigi et al 2018). Tochigi et al (2018) quantitatively assessed the seed production of 241-304 individual Q. crispula trees over several years in this study area and estimated individual tree energy values and regional mast energy values.…”

“…Based on this information, we identified 2006, 2010, and 2012 as poor mast years and 2007, 2008, 2009, 2011, 2013, and 2014 as years with above-average yield and thus good mast years (Tochigi et al 2018). Tochigi et al (2018) quantitatively assessed the seed production of 241-304 individual Q. crispula trees over several years in this study area and estimated individual tree energy values and regional mast energy values.…”

Impact of the spatial uncertainty of seed dispersal on tree colonization dynamics in a temperate forest

“…Various temporal factors may affect the degree of aggregated dispersal, including annual variation in tree fecundity (Shibata et al 2002), weather conditions such as wind speed (Sato et al 2010), and the abundance and movement patterns of frugivorous animals (Naoe et al 2018). Furthermore, the behavior of frugivores may be influenced by the patterns of seed production at a landscape scale (Koike et al 2011, Morales et al 2012, Tochigi et al 2018). All of these temporal variables may cause year-to-year changes in seedfall distribution irrespective of dispersal mode (Schurr et al 2008, Martínez and González-Taboada 2009, Koike et al 2011, Wright et al 2016, Yamazaki et al 2016, Naoe et al 2018.…”