Percequillo Alexandre R, Dalapicolla Jeronymo, Abreu-Júnior Edson F, Roth Paulo Ricardo O, Ferraz Katia M P M B, Chiquito Elisandra A
Departamento de Ciências Biológicas, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Piracicaba, São Paulo, Brazil.
Department of Life Sciences, The Natural History Museum, London, United Kingdon.
PeerJ. 2017 Dec 15;5:e4071. doi: 10.7717/peerj.4071. eCollection 2017.
Since 1996, when Vivo questioned how many species of mammals occur in Brazil, there has been a huge effort to assess this biodiversity. In this contribution, we present new records for rare species of the sigmodontine rodent genera and previously unknown to Brazilian Amazon. We provided detailed information on the morphologic variation to allow the proper identification of these species. We also furnished updated information on their collection, aiming to establish hypothesis of their geographic distribution, based on SDM's, aiming to hypothesize potential occurrence areas for these species.
Rodent specimens were sampled in separate inventories in two sites of Rondônia State (Hydroelectric Dam Jirau and Parque Nacional de Pacaás Novos) and one site in Pará State (Pacajá), Brazil, and were compared to specimens from museum collections to apply appropriate names. The SDM were conducted using two algorithms for rare species, MaxEnt and randomForest (RF), and were based on seven localities for , and 10 for .
All specimens were collected with pitfall traps. One specimen of genus was trapped in the Hydroelectric Dam Jirau. We identified this specimen as , and the SDM species indicates suitable areas for its occurrence at high elevations near on the Andes and lowlands of Amazon Basin to the South of the Rio Amazonas. Two specimens of were recorded, and we identified the specimen from Pacaás Novos as , with SDM suggesting main areas of occurrence on Western Amazon. We applied the name to the specimen from Pacajá, with SDM recovering suitable areas in Eastern Amazon.
We reinforced the importance of pitfall traps on the study of Neotropical rodents. We described morphologic variation within and among all species that do not invalidate their specific status, but in the near future a re-evaluation will be mandatory. The new records extended the species distribution considerably. SDM was successful to predict their distributions, as the two algorithms presented important differences in range size recovered by the models that can be explained by differences in the thresholds used for the construction of the models. Most suitable areas coincide with the areas facing most of the deforestation in Amazon. We added two rare species of sigmodontine rodents to the list of Brazilian Mammals, which now comprises 722 species (or 775 valid nominal taxa). Although more information is available than in 1996, it is essential that mammal experts maintain inventory and revisionary programs to update and revise this information. This is even more important, as changes in Brazilian environmental legislation are being discussed, suggesting reduced need for environmental impact reports prior to beginning commercial enterprises, resulting in the loss of information about native biodiversity in the affected areas.
自1996年维沃(Vivo)质疑巴西有多少种哺乳动物以来,人们为评估这种生物多样性付出了巨大努力。在本论文中,我们展示了巴西亚马逊地区此前未知的稻鼠亚科(Sigmodontinae)啮齿动物稀有物种的新记录。我们提供了详细的形态变异信息,以便正确识别这些物种。我们还提供了它们的采集信息更新,旨在基于物种分布模型(SDM)建立其地理分布假说,以推测这些物种的潜在出现区域。
在巴西朗多尼亚州的两个地点(吉劳水电站和帕卡阿斯诺沃斯国家公园)以及帕拉州的一个地点(帕卡亚)的单独清查中采集啮齿动物标本,并与博物馆收藏的标本进行比较以确定合适的名称。物种分布模型使用针对稀有物种的两种算法,最大熵模型(MaxEnt)和随机森林(RF),分别基于7个 和10个 地点的数据。
所有标本均使用陷阱诱捕采集。在吉劳水电站捕获了一只 属的标本。我们将该标本鉴定为 ,物种分布模型表明其在安第斯山脉附近高海拔地区以及亚马逊河南部低地的亚马逊盆地有适宜出现的区域。记录到了两只 属的标本,我们将来自帕卡阿斯诺沃斯的标本鉴定为 ,物种分布模型显示其主要出现在亚马逊西部。我们将来自帕卡亚的标本命名为 ,物种分布模型显示其在亚马逊东部有适宜区域。
我们强调了陷阱诱捕在新热带区啮齿动物研究中的重要性。我们描述了所有物种内部和之间的形态变异,这些变异并未使其特定地位无效,但在不久的将来必须进行重新评估。新记录大大扩展了这些物种的分布范围。物种分布模型成功预测了它们的分布,因为两种算法在模型恢复的分布范围大小上呈现出重要差异,这可以通过构建模型所使用的阈值差异来解释。大多数适宜区域与亚马逊地区面临森林砍伐最严重的区域重合。我们在巴西哺乳动物名录中新增了两种稀有的稻鼠亚科啮齿动物,该名录现在包括722种(或775个有效命名分类单元)。尽管现在可获得的信息比1996年更多,但哺乳动物专家必须维持清查和修订计划以更新和修正这些信息。这一点尤为重要,因为巴西环境立法正在讨论中,这意味着商业企业开始前对环境影响报告的需求可能减少,从而导致受影响地区本地生物多样性信息的丢失。