M.L. Parry J.P. Palut

Bio: M.L. Parry J.P. Palut is an academic researcher. The author has contributed to research in topics: Climate change. The author has an hindex of 1, co-authored 1 publications receiving 6784 citations.

Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

Abstract: Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

A statistical explanation of MaxEnt for ecologists

Abstract: MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model from a statistical perspective, making explicit links between the structure of the model, decisions required in producing a modelled distribution, and knowledge about the species and the data that might affect those decisions. To begin we discuss the characteristics of presence-only data, highlighting implications for modelling distributions. We particularly focus on the problems of sample bias and lack of information on species prevalence. The keystone of the paper is a new statistical explanation of MaxEnt which shows that the model minimizes the relative entropy between two probability densities (one estimated from the presence data and one, from the landscape) defined in covariate space. For many users, this viewpoint is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts. We then step through a detailed explanation of MaxEnt describing key components (e.g. covariates and features, and definition of the landscape extent), the mechanics of model fitting (e.g. feature selection, constraints and regularization) and outputs. Using case studies for a Banksia species native to south-west Australia and a riverine fish, we fit models and interpret them, exploring why certain choices affect the result and what this means. The fish example illustrates use of the model with vector data for linear river segments rather than raster (gridded) data. Appropriate treatments for survey bias, unprojected data, locally restricted species, and predicting to environments outside the range of the training data are demonstrated, and new capabilities discussed. Online appendices include additional details of the model and the mathematical links between previous explanations and this one, example code and data, and further information on the case studies.

Social Capital, Collective Action, and Adaptation to Climate Change

Abstract: The effects of observed and future changes in climate are spatially and socially differentiated. The impacts of future changes will be felt particularly by resource-dependent communities through a multitude of primary and secondary effects cascading through natural and social systems. Given that the world is increasingly faced with risks of climate change that are at the boundaries of human experience3, there is an urgent need to learn from past and present adaptation strategies to understand both the processes by which adaptation takes place and the limitations of the various agents of change – states, markets, and civil society – in these processes. Societies have inherent capacities to adapt to climate change. In this article, I argue that these capacities are bound up in their ability to act collectively.

A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2

Abstract: Recent research has highlighted the valuable role that coastal and marine ecosystems play in sequestering carbon dioxide (CO(2)). The carbon (C) sequestered in vegetated coastal ecosystems, specifically mangrove forests, seagrass beds, and salt marshes, has been termed blue carbon. Although their global area is one to two orders of magnitude smaller than that of terrestrial forests, the contribution of vegetated coastal habitats per unit area to long-term C sequestration is much greater, in part because of their efficiency in trapping suspended matter and associated organic C during tidal inundation. Despite the value of mangrove forests, seagrass beds, and salt marshes in sequestering C, and the other goods and services they provide, these systems are being lost at critical rates and action is urgently needed to prevent further degradation and loss. Recognition of the C sequestration value of vegetated coastal ecosystems provides a strong argument for their protection and restoration; however, it is necessary to improve scientific understanding of the underlying mechanisms that control C sequestration in these ecosystems. Here, we identify key areas of uncertainty and specific actions needed to address them.

A new scenario framework for climate change research: the concept of shared socioeconomic pathways

Abstract: The new scenario framework for climate change research envisions combining pathways of future radiative forcing and their associated climate changes with alternative pathways of socioeconomic development in order to carry out research on climate change impacts, adaptation, and mitigation. Here we propose a conceptual framework for how to define and develop a set of Shared Socioeconomic Pathways (SSPs) for use within the scenario framework. We define SSPs as reference pathways describing plausible alternative trends in the evolution of society and ecosystems over a century timescale, in the absence of climate change or climate policies. We introduce the concept of a space of challenges to adaptation and to mitigation that should be spanned by the SSPs, and discuss how particular trends in social, economic, and environmental development could be combined to produce such outcomes. A comparison to the narratives from the scenarios developed in the Special Report on Emissions Scenarios (SRES) illustrates how a starting point for developing SSPs can be defined. We suggest initial development of a set of basic SSPs that could then be extended to meet more specific purposes, and envision a process of application of basic and extended SSPs that would be iterative and potentially lead to modification of the original SSPs themselves.