scholarly journals Land use, macroecology, and the accuracy of the Maximum Entropy Theory of Ecology: A case study of Azorean arthropods

2021 ◽  
Author(s):  
Micah Brush ◽  
Thomas J. Matthews ◽  
Paulo A.V. Borges ◽  
John Harte
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Metabolic Rate ◽  
Maximum Entropy ◽  
Management Practices ◽  
Entropy Theory ◽  
State Variables ◽  
Arthropod Communities ◽  
Natural Pasture ◽  
Maximum Entropy Theory

AbstractHuman activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbances affect the shape of macroecological patterns, and analyzing these patterns can provide insights into how ecosystems are affected by land use change. The Maximum Entropy Theory of Ecology (METE) simultaneously predicts many of these patterns using a set of ecological state variables: the number of species, the number of individuals, and the total metabolic rate. The theory’s predictions have been shown to be successful across habitats and taxa in undisturbed natural ecosystems, although previous tests of METE in relation to disturbance have focused primarily on systems where the state variables are changing relatively quickly. Here, we assess predictions of METE applied to a different type of disturbance: land use change. We use METE to simultaneously predict the species abundance distribution (SAD), the metabolic rate distribution of individuals (MRDI), and the species–area relationship (SAR) and compare these predictions to arthropod data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: 1. native forest, 2. exotic forest, 3. semi-natural pasture, and 4. intensive pasture. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture consistently provided the worst fit. The intensive pasture is intermediately well fit for the SAD and MRDI, and comparatively well fit for the SAR, though the residuals are not normally distributed. The direction of failure of the METE predictions at the pasture sites is likely due to the hyperdominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium and the changing management practices throughout the year, leading to greater heterogeneity in composition and complex dynamics that violate METE’s assumption of static state variables. The comparative better fit for the intensive pasture could then result from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux.

Modelling fire probability in the Brazilian Amazon using the maximum entropy method

2016 ◽  
Vol 25 (9) ◽  
pp. 955 ◽  
Author(s):  
Marisa G. Fonseca ◽  
Luiz Eduardo O. C. Aragão ◽  
André Lima ◽  
Yosio E. Shimabukuro ◽  
Egidio Arai ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Maximum Entropy ◽  
Forest Fires ◽  
Maximum Entropy Method ◽  
Management Practices ◽  
Brazilian Amazon ◽  
Forest Degradation ◽  
Entropy Method ◽  
Monthly Basis

Fires are both a cause and consequence of important changes in the Amazon region. The development and implementation of better fire management practices and firefighting strategies are important steps to reduce the Amazon ecosystems’ degradation and carbon emissions from land-use change in the region. We extended the application of the maximum entropy method (MaxEnt) to model fire occurrence probability in the Brazilian Amazon on a monthly basis during the 2008 and 2010 fire seasons using fire detection data derived from satellite images. Predictor variables included climatic variables, inhabited and uninhabited protected areas and land-use change maps. Model fit was assessed using the area under the curve (AUC) value (threshold-independent analysis), binomial tests and model sensitivity and specificity (threshold-dependent analysis). Both threshold-independent (AUC = 0.919 ± 0.004) and threshold-dependent evaluation indicate satisfactory model performance. Pasture, annual deforestation and secondary vegetation are the most effective variables for predicting the distribution of the occurrence data. Our results show that MaxEnt may become an important tool to guide on-the-ground decisions on fire prevention actions and firefighting planning more effectively and thus to minimise forest degradation and carbon loss from forest fires in Amazonian ecosystems.

scholarly journals Derivations of the Core Functions of the Maximum Entropy Theory of Ecology

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 712 ◽  
Author(s):  
Alexander Brummer ◽  
Erica Newman
Keyword(s):  
Species Richness ◽  
Structure Function ◽  
Maximum Entropy ◽  
Information Entropy ◽  
Lagrange Multipliers ◽  
Metabolic Energy ◽  
Entropy Theory ◽  
State Variables ◽  
The Core ◽  
Maximum Entropy Theory

The Maximum Entropy Theory of Ecology (METE), is a theoretical framework of macroecology that makes a variety of realistic ecological predictions about how species richness, abundance of species, metabolic rate distributions, and spatial aggregation of species interrelate in a given region. In the METE framework, “ecological state variables” (representing total area, total species richness, total abundance, and total metabolic energy) describe macroecological properties of an ecosystem. METE incorporates these state variables into constraints on underlying probability distributions. The method of Lagrange multipliers and maximization of information entropy (MaxEnt) lead to predicted functional forms of distributions of interest. We demonstrate how information entropy is maximized for the general case of a distribution, which has empirical information that provides constraints on the overall predictions. We then show how METE’s two core functions are derived. These functions, called the “Spatial Structure Function” and the “Ecosystem Structure Function” are the core pieces of the theory, from which all the predictions of METE follow (including the Species Area Relationship, the Species Abundance Distribution, and various metabolic distributions). Primarily, we consider the discrete distributions predicted by METE. We also explore the parameter space defined by the METE’s state variables and Lagrange multipliers. We aim to provide a comprehensive resource for ecologists who want to understand the derivations and assumptions of the basic mathematical structure of METE.

scholarly journals Derivations of the Core Functions of the Maximum Entropy Theory of Ecology

2019 ◽  
Author(s):  
Alexander Brummer ◽  
Erica Newman
Keyword(s):  
Species Richness ◽  
Structure Function ◽  
Maximum Entropy ◽  
Information Entropy ◽  
Lagrange Multipliers ◽  
Metabolic Energy ◽  
Entropy Theory ◽  
State Variables ◽  
The Core ◽  
Maximum Entropy Theory

The Maximum Entropy Theory of Ecology, or METE, is a theoretical framework of macroecology that makes a variety of realistic ecological predictions about how species richness, abundance of species, metabolic rate distributions, and spatial aggregation of species interrelate in a given region. In the METE framework, "ecological state variables" (representing total area, total species richness, total abundance, and total metabolic energy) describe macroecological properties of an ecosystem. METE incorporates these state variables into constraints on underlying probability distributions. The method of Lagrange multipliers and maximization of information entropy (MaxEnt) lead to predicted functional forms of distributions of interest. We demonstrate how information entropy is maximized for the general case of a distribution, which has empirical information that provides constraints on the overall predictions. We then show how METE’s two core functions are derived. These functions, called the "Spatial Structure Function" and the "Ecosystem Structure Function" are the core pieces of the theory, from which all the predictions of METE follow (including the Species Area Distribution, the Species Abundance Distribution, and various metabolic distributions). Primarily, we consider the discrete distributions predicted by METE.We also explore the parameter space defined by the METE’s state variables and Lagrange multipliers. We aim to provide a comprehensive resource for ecologists who want to understand the derivations and assumptions of basic mathematical structure of METE.

Maximum entropy theory

1985 ◽  
Vol 41 (2) ◽  
pp. 113-122 ◽  
Author(s):  
A. K. Livesey ◽  
J. Skilling
Keyword(s):  
Maximum Entropy ◽  
Entropy Theory ◽  
Maximum Entropy Theory

scholarly journals Flooding and Land Use Change in Southeast Sulawesi, Indonesia

Land ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 139 ◽  
Author(s):  
Lisa C. Kelley ◽  
Agung Prabowo
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Management Practices ◽  
Vegetable Production ◽  
Flood Events ◽  
Daily Production ◽  
Extreme Flood ◽  
Agrarian Societies

Flooding is a routine occurrence throughout much of the monsoonal tropics. Despite well-developed repertoires of response, agrarian societies have been ‘double exposed’ to intensifying climate change and agro-industrialization over the past several decades, often in ways that alter both the regularity of flood events and individual and community capacity for response. This paper engages these tensions by exploring everyday experiences of and responses to extreme flood events in a case study village in Southeast Sulawesi, Indonesia, which has also been the site of corporate oil palm development since 2010. We first reconstruct histories of extreme flood events along the Konawe’eha River using oral histories and satellite imagery, describing the role of these events in straining the terms of daily production and reproduction. We then outline the ways smallholder agriculturalists are responding to flood events through alterations in their land use strategies, including through the sale or leasing of flood-prone lands, the relocation of riverine vegetable production to hillside locations, and adoption of new cropping choices and management practices. We highlight the role of such responses as a driver of ongoing land use change, potentially in ways that increase systemic vulnerability to floods moving forward.

scholarly journals Using Farmer Decision Rules for Mapping Historical Land Use Change Patterns from 1954 to 2007 in Rural Northwestern Vietnam

Land ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 130
Author(s):  
Thanh Thi Nguyen ◽  
Melvin Lippe ◽  
Carsten Marohn ◽  
Tran Duc Vien ◽  
Georg Cadisch
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Management Practices ◽  
Anthropogenic Activities ◽  
Decision Rules ◽  
Remote Sensing Data ◽  
Rural Landscapes ◽  
Sensing Data ◽  
Assessment Period

The present study revealed how local socioecological knowledge elucidated during participatory rural appraisals and historical remote sensing data can be combined for analyzing land use change patterns from 1954 to 2007 in northwestern Vietnam. The developed approach integrated farmer decision rules on cropping preferences and location, visual and supervised classification methods, and qualitative information obtained during various forms of participatory appraisals. The integration of historical remote sensing data (aerial photo, Landsat, LISS III) with farmer decision rules showed the feasibility of the proposed method to explain crop distribution patterns for the assessment period of 53 years. Our approach is beneficial for data-limited environments, which is a prevalent situation for many developing regions. The derived land use and crop type dataset was used for understanding how anthropogenic activities altered the study area of the Chieng Khoi commune during the assessment period of five decades, and what potential impact this can have on the natural resource base. The newly developed approach offers a methodological pathway that can be easily transferred to local government authorities for a better understanding of cropping transitions and agricultural expansion trends in data-limited rural landscapes. The detected land use change patterns and upland cropping expansion of more than two hundred percent in 53 years not only revealed the consequences of the interactions and feedback between farmers and their land, but further highlighted the urgent need for implementing sustainable land management practices in the case study watershed of the Chieng Khoi commune and northwestern Vietnam in general.

Study on Probabilistic Damage Constitutive Relation of Rocks Based on Maximum-Entropy Theory

2020 ◽  
Vol 20 (2) ◽  
pp. 06019018 ◽  
Author(s):  
Bin Hu ◽  
Peng-Zhi Pan ◽  
Wei-Wei Ji ◽  
Shuting Miao ◽  
Decai Zhao ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Constitutive Relation ◽  
Entropy Theory ◽  
Maximum Entropy Theory

Maximum Entropy

2020 ◽  
pp. 161-184
Author(s):  
John Harte
Keyword(s):  
Maximum Entropy ◽  
Rapid Change ◽  
Entropy Theory ◽  
State Variables ◽  
Total Abundance ◽  
Inference Procedure ◽  
Functional Forms ◽  
Natural Historian ◽  
Parameter Values ◽  
Maximum Entropy Inference

A major goal of ecology is to predict patterns and changes in the abundance, distribution, and energetics of individuals and species in ecosystems. The maximum entropy theory of ecology (METE) predicts the functional forms and parameter values describing the central metrics of macroecology, including the distribution of abundances over all the species, metabolic rates over all individuals, spatial aggregation of individuals within species, and the dependence of species diversity on areas of habitat. In METE, the maximum entropy inference procedure is implemented using the constraints imposed by a few macroscopic state variables, including the number of species, total abundance, and total metabolic rate in an ecological community. Although the theory adequately predicts pervasive empirical patterns in relatively static ecosystems, there is mounting evidence that in ecosystems in which the state variables are changing rapidly, many of the predictions of METE systematically fail. Here we discuss the underlying logic and predictions of the static theory and then describe progress toward achieving a dynamic theory (DynaMETE) of macroecology capable of describing ecosystems undergoing rapid change as a result of disturbance. An emphasis throughout is on the tension between, and reconciliation of, two legitimate perspectives on ecology: that of the natural historian who studies the uniqueness of every ecosystem and the theorist seeking unification and generality.

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