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Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Non-volant small mammals, the most diverse ecological group of mammals in Neotropical forests, play an important role in forest dynamics and are good indicators of both local and landscape alterations. However, little is known about species and diversity distribution and only a few of the largest Atlantic Forest remnants have been adequately sampled. Based on a survey we carried out in the Morro Grande Forest Reserve, São Paulo State, and on other 20 Atlantic forest inventories, this study aims at (1) describing the non-volant small mammal list and community structure of the Reserve, (2) describing how species and diversity are distributed in space and time in the Reserve and (3) investigating how diversity is affected by capture methods. The non-volant small mammal fauna of the Reserve includes several rare and mature forest species, besides common species from genera that are usually abundant in other well preserved forests. The total number of species is high, in part due to the use of large pitfall traps in the sampling protocol, but also probably due to the Reserve location and altitude. The additive partitioning of diversity indicates that a major part of diversity is found locally in sample sites, a second part among sample sites within the same habitat type and just a minor part among habitats, suggesting the importance of micro-scale forest heterogeneity to the distribution of non-volant small mammals. Abundance and richness did not vary between the two sampled years and it is possible that continuous forest areas may present more temporally stable populations and communities. However, they varied seasonally, with high values found at the end of the wet season and low values at the end of the dry season. Pitfall traps showed to be extremely efficient for capturing non-volant small mammals. Atlantic forest, inventories, non-volant small mammals, diversity patterns, sampling methods, additive partitioning, inter-annual variations, seasonal variations, spatial variations, habitat Key words:

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