Abstract

The growth of urban centers, along with the fragmentation of natural habitats, can interfere with the distribution pattern of species and their abundance, thus compromising the conservation of urban biodiversity. Principal players in this biodiversity are arthropods that help to decompose litterfall, favoring the recycling of nutrients and, hence, are an important part in sustaining the forest fragments that remain in urban areas. Therefore, it is important to study arthropod biodiversity in green urban areas, especially those areas where litterfall management is an important part of maintaining biodiversity. Accordingly, this study evaluated arthropod diversity associated with litterfall in three urban forests with different size and litterfall management practices, including Água Branca Park (ABP) and Tietê Ecological Park (TEP)—Núcleo Engenheiro Goulart in São Paulo City and Chico Mendes Park (CMP) in Osasco City, all belonging to the Metropolitan Region of São Paulo (MRSP), Brazil. Four litterfall harvests were carried out in each park between April and August of 2015 with twelve samples collected with a wood mold (30-cmx30-cm) at randomly points on the forest floor. The collected material was then screened in the laboratory and the arthropods were visually separated and preserved in alcohol 70%. Arthropods were classified by the order to which they belonged. Litterfall was dried in a forced air oven at 65 °C for seven days. Dried litterfall was then separated into leaves, branches, reproductive parts and miscellaneous fragments and weighed. Arthropod diversity was measured by Shannon, Margalef and Pielou indexes and non-metric multidimensional scaling analysis (NMDS) using the Manhattan distance index. Litterfall weight was compared by one-way ANOVA. The orders Hymenoptera, Collembola and Isopoda were dominant in CMP, ABP and TEP, respectively but multiple rare orders had a presence in all parks, albeit at different abundance. NMDS showed abundance similarity among the parks; however, TEP showed greater richness, Shannon diversity and evenness. The fractions of leaf litterfall and reproductive parts were different between the CMP and TEP. Overall, our results confirm that neither litterfall management, nor park size, is a final determinant of arthropod distribution, even though the abundance of dominant species was shown to differ in each park.

Highlights

  • Urban forests are small forest fragments inside urban environments

  • At Chico Mendes Park, visitors were observed walking on the litterfall, a situation that was little observed at Tietê Ecological Park

  • To demonstrate the biodiversity of arthropods associated with litterfall, a total of 1176 individuals were sampled, distributed into 19 orders, including 365 individuals belonging to 12 orders in Chico Mendes Park (CMP), 330 individuals in 16 orders in ABP and 481 individuals in 17 orders in Tietê Ecological Park (TEP) (Table 1)

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Summary

Introduction

Urban forests are small forest fragments inside urban environments. They form green patches in an immense gray matrix and play an important role in maintaining the biodiversity of species that occupy and/or transit into these areas [1,2]. Like larger forest fragments, these areas are subjected to such stresses as fire, pollution, urban growth and even vandalism [3,4] Such stresses promote a particular dynamic of edaphic biodiversity in these forests and it can interfere with nutrient recycling of litterfall, an important part of organic matter that supports energy flow in ecosystems [5,6,7,8]. The largest fraction of litterfall in tropical regions consists of leaves, accounting for approximately 70% of the organic matter returned to the forest soils [9] In urban areas, such as parks and forest fragments, litterfall can be managed according to the requirements of the area. The sampled material was stored in separate plastic bags and properly identified with number, date and site and taken to the laboratory for analysis [9]

Screening of Litterfall Fractions
Screening and Identification of Arthropods
Data Analysis
Results
Conclusions
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