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

地球正在经历着几千年来未曾见过的前所未有的环境变化，包括农业和发展扩张的景观的大规模变化以及生物多样性的灭绝危机。最近的研究表明，热带森林的再生将在减缓全球人类活动引起的环境变化、减少大气温室气体排放、恢复失去的生态系统功能和服务方面发挥关键作用。然而，尽管全世界大部分被砍伐的森林正在进行更新，但它们很少恢复到最初的旧生长功能和条件。支撑这一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地区。该项目旨在通过研究景观结构如何与散播种子的动物相互作用来影响热带森林的再生来解决这一知识鸿沟。这项研究将在马达加斯加高度濒危的热带雨林中进行，这些热带雨林具有复杂的土地利用模式。从这项研究中获得的见解将对确定不同的景观情景具有更广泛的影响，在这些情景中，森林更有可能再生为老树森林条件，从而有助于缓解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，并让艺术家提供不同的视角，并与多个利益相关者进行创造性的沟通。本项目将研究在人工景观中，景观结构对热带森林更新中的性状介导的种子传播的直接和间接影响。众所周知，生境数量、破碎化程度和基质质量等景观特征影响着几个关键的扩散过程，包括种子雨、种子来源的多样性和种子播散器的多样性，所有这些都影响扩散后的苗木招募和由此产生的更新植被群落。这些过程可能受到植物传播特性的影响，如果实和种子的类型、形状和大小。我们假设，景观结构直接作为非生物过滤器，间接作为生物过滤器，通过分别确定种子可用性和种子传播器可用性来影响更新森林中的种子多样性。在这一框架内，该项目将利用一种综合的、多尺度的方法来解决知识的根本差距，这种方法结合了种子群落集合的测量和以特征为中介的种子传播、预测性建模和空间上明确的升级，以深入了解景观结构如何影响森林更新。具体地说，研究人员将(1)沿着不同景观背景下更新热带森林的演替梯度(时间序列)进行种子多样性分析；(2)调查景观结构和种子传播者如何相互作用，影响更新森林中的植物多样性；(3)结合遥感和空间上明确的基于主体的模型，得出景观结构如何在多个空间尺度上影响森林恢复的机械解释。通过专注于可以说是最重要的重建阶段，该项目将促进关于如何根据景观环境稳定、推迟或加速热带森林重建的知识。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.