BoCP-Implementation: Cascading Impacts of Landscape Structure on Forest Regeneration

地球正在经历数千年来前所未有的环境变化，包括农业和发展扩张的大规模景观转变以及生物多样性灭绝危机。最近的研究表明，热带森林的再生将在减缓全球人类引起的环境变化、减少大气温室气体和恢复失去的生态系统功能和服务方面发挥关键作用。然而，虽然全世界很大一部分被砍伐的森林进行了再生，但它们很少恢复到最初的原始功能和条件。支撑这种复苏的具体机制仍然不确定，特别是在受人类活动严重影响的景观中。该项目旨在通过研究景观结构如何与种子传播动物相互作用以影响热带森林的再生来解决这一知识差距。这项研究将在马达加斯加高度濒危的雨林中进行，这些雨林的特点是土地使用模式复杂。从这项研究中获得的见解将对确定森林更有可能再生为原始森林条件的不同景观情景产生更广泛的影响，从而有助于减缓气候变化和保护生物多样性。为了实现这一目标，一个国际化的多学科团队将与当地合作伙伴合作，吸引来自代表性不足群体的本科生，并让艺术家提供多样化的观点，并与多个利益相关者进行创造性的沟通。 本项目将调查景观结构对人为景观中再生热带森林中性状介导的种子传播的直接和间接影响。景观特性，如栖息地的数量，破碎化和矩阵的质量，是众所周知的调制几个关键的传播过程，包括种子雨，种子来源的多样性，种子传播者的多样性，所有这些都影响后传播幼苗招聘和由此产生的再生植被社区。这些过程可以受到植物传播特性的影响，例如果实和种子的类型，形状和大小。我们假设，景观结构直接作为一个非生物过滤器和间接作为一个生物过滤器，通过确定种子的可用性和种子传播器的可用性，分别影响再生森林的种子多样性。在这个框架内，该项目将解决知识的根本差距，通过使用一个综合的，多尺度的方法，结合测量种子群落组装和性状介导的种子传播，预测建模，并在空间上明确升级，以深入了解景观结构如何影响森林再生。具体来说，研究人员将（1）沿着演替梯度对种子多样性进行分析（2）研究景观结构和种子传播者如何相互作用影响更新林植物多样性;以及（3）使用遥感和空间显式代理的组合-基于模型，得出景观结构如何影响森林恢复在多个空间尺度的机制解释。通过关注再生过程中最重要的阶段，该项目将促进人们对如何根据景观环境稳定、延迟或加速热带森林再生的认识。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The Earth is undergoing unprecedented environmental changes not seen for millennia including massive transformation of landscapes for agricultural and development expansion and a biodiversity extinction crisis. Recent studies suggest that the regeneration of tropical forests will play a crucial role in mitigating global human-induced environmental change, reducing atmospheric greenhouse gasses, and recovering lost ecosystem functions and services. However, while a large proportion of cleared forests worldwide undergo regeneration, they rarely recover to initial old-growth functions and conditions. The specific mechanisms that underpin this recovery remain uncertain, particularly in landscapes heavily influenced by human activity. This project aims to address this knowledge gap by examining how landscape structure interacts with seed-dispersing animals to influence the regeneration of tropical forests. The study will take place in highly endangered rainforests in Madagascar, which are characterized by complex land-use patterns. The insights gained from this research will have broader implications for identifying different landscape scenarios where forests are more likely to regenerate to old-growth forest conditions, thus contributing to climate change mitigation and biodiversity conservation. To accomplish this, an international, multidisciplinary team will collaborate with local partners, engage undergraduate students from underrepresented groups, and involve artists to provide diverse perspectives and communicate creatively with multiple stakeholders. This project will investigate the direct and indirect effects of landscape structure on trait-mediated seed dispersal in regenerating tropical forests in anthropogenic landscapes. Landscape properties such as habitat amount, fragmentation and matrix quality, are known to modulate several crucial dispersal processes, including seed rain, diversity of seed sources, and diversity of seed dispersers, all of which affect post-dispersal seedling recruitment and the resulting community of regenerating vegetation. These processes can be influenced by plant dispersal traits, such as fruit and seed type, shape, and size. We hypothesize that landscape structure acts directly as an abiotic filter and indirectly as a biotic filter that influences seed diversity in regenerating forests by determining seed availability and seed disperser availability, respectively. Within this framework, the project will address fundamental gaps in knowledge by using an integrated, multi-scale approach that combines measurements of seed community assembly and trait-mediated seed dispersal, predictive modeling, and spatially explicit upscaling to gain insights into how landscape structure influences forest regeneration. Specifically, the researchers will (1) conduct an analysis of seed diversity along successional gradients (chronosequence) of regenerating tropical forests in different landscape contexts; (2) investigate how landscape structure and seed dispersers interact to influence plant diversity in regenerating forests; and (3) use a combination of remote sensing and a spatially explicit agent-based models to derive mechanistic explanations for how landscape structure influences forest recovery at multiple spatial scales. By focusing on arguably the most important stage of regeneration, this project will advance the knowledge of how tropical forest regeneration can be stabilized, delayed, or accelerated according to the landscape context.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.