text:
# Combinatorial Sleeping Bandits with Fairness Constraints

@article{Li2019CombinatorialSB,
title={Combinatorial Sleeping Bandits with Fairness Constraints},
author={Fengjiao Li and Jia Liu and Bo Ji},
journal={IEEE INFOCOM 2019 - IEEE Conference on Computer Communications},
year={2019},
pages={1702-1710}
}
• Published 15 January 2019
• Computer Science
• IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
The multi-armed bandit (MAB) model has been widely adopted for studying many practical optimization problems (network resource allocation, ad placement, crowdsourcing, etc.) with unknown parameters. [] Key Method By carefully integrating these two techniques, we develop a new algorithm, called Learning with Fairness Guarantee (LFG), for the CSMAB-F problem. Further, we rigorously prove that not only LFG is feasibility-optimal but it also has a time-average regret upper bounded by $\displaystyle \frac {N}{2… ## Figures and Tables from this paper Combinatorial Sleeping Bandits With Fairness Constraints • Computer Science IEEE Transactions on Network Science and Engineering • 2020 A new algorithm, called Learning with Fairness Guarantee (LFG), is developed for the CSMAB-F problem, which is rigorously proved that not only LFG is feasibility-optimal, but it also has a time-average regret. Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints • Computer Science IJCAI • 2020 This paper adopts a new approach that combines online convex optimization with bandit methods to design selection algorithms and manages to achieve a sublinear regret bound with probability guarantees. A Regret bound for Non-stationary Multi-Armed Bandits with Fairness Constraints • Computer Science ArXiv • 2020 This paper presents a new algorithm called Fair Upper Confidence Bound with Exploration (Fair-UCBe) algorithm for solving a slowly varying stochastic k-armed bandit problem, and is the first fair algorithm with a sublinear regret bound applicable to non-stationary bandits to the best of the authors' knowledge. Thompson Sampling for Combinatorial Semi-bandits with Sleeping Arms and Long-Term Fairness Constraints • Computer Science ArXiv • 2020 It is proved TSCSF-B can satisfy the fairness constraints, and the time-averaged regret is upper bounded by$\frac{N}{2\eta} + O\left(\frac{\sqrt{mNT\ln T}}{T}\right)$, which is the first problem-independent bound of TS algorithms for combinatorial sleeping multi-armed semi-bandit problems. Achieving Fairness in the Stochastic Multi-armed Bandit Problem • Computer Science AAAI • 2020 A fairness-aware regret is defined that takes into account the above fairness constraints and naturally extends the conventional notion of regret, called r-Regret, that holds uniformly over time irrespective of the choice of the learning algorithm. Combinatorial Sleeping Bandits with Fairness Constraints and Long-Term Non-Availability of Arms • Computer Science 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) • 2020 The algorithm proposed in this paper deals with the situation of long term non-availability of arms in combinatorial sleeping bandits problem and still maintain the regret bounds along with the queue fairness constraints, and a better way of estimating the fairness that takes into account the longterm non- availability of arms is proposed. Exploring Best Arm with Top Reward-Cost Ratio in Stochastic Bandits • Computer Science IEEE INFOCOM 2020 - IEEE Conference on Computer Communications • 2020 A fundamental lower bound for sample complexities of any algorithms under Bernoulli distributions is provided, and it is shown that the samples of the proposed three algorithms match that of the lower bound in the sense of$\log \frac{1}{\delta }\$.
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach
2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
• 2021
Three algorithms are proposed that satisfy the fairness requirement of fair worker selection in Federated Learning systems by giving a higher priority to fairness, and FairDG ensures a stronger short-term fairness guarantee, which holds in every round.
Stochastic Multi-armed Bandits with Arm-specific Fairness Guarantees
• Computer Science
ArXiv
• 2019
A Fairness-aware regret is defined that takes into account the above fairness constraints and extends the conventional notion of regret in a natural way, and shows that logarithmic regret can be achieved while (almost) satisfying the fairness requirements.
Fairer LP-based Online Allocation
• Computer Science
ArXiv
• 2021
A fair algorithm that uses an interior-point LP solver and dynamically detects unfair resource spending is proposed that can control cumulative unfairness on the scale of order O(log(T )), while maintaining the regret to be bounded without dependency on T .

## References

SHOWING 1-10 OF 37 REFERENCES
Combinatorial Sleeping Bandits With Fairness Constraints
• Computer Science
IEEE Transactions on Network Science and Engineering
• 2020
A new algorithm, called Learning with Fairness Guarantee (LFG), is developed for the CSMAB-F problem, which is rigorously proved that not only LFG is feasibility-optimal, but it also has a time-average regret.
Achieving Fairness in the Stochastic Multi-armed Bandit Problem
• Computer Science
AAAI
• 2020
A fairness-aware regret is defined that takes into account the above fairness constraints and naturally extends the conventional notion of regret, called r-Regret, that holds uniformly over time irrespective of the choice of the learning algorithm.
Bandits with Knapsacks
• Computer Science
2013 IEEE 54th Annual Symposium on Foundations of Computer Science
• 2013
This work presents two algorithms whose reward is close to the information-theoretic optimum: one is based on a novel "balanced exploration" paradigm, while the other is a primal-dual algorithm that uses multiplicative updates that is optimal up to polylogarithmic factors.
Fair Task Allocation in Crowdsourced Delivery
• Computer Science
IEEE Transactions on Services Computing
• 2021
This work introduces a new assignment strategy for crowdsourced delivery tasks that takes fairness towards workers into consideration, while maximizing the task allocation ratio, and presents both offline and online versions of the proposed algorithm, F-Aware.
Combinatorial Multi-Armed Bandit with General Reward Functions
• Wei Chen
• Computer Science, Mathematics
NIPS
• 2016
A new algorithm called stochastic combinatorial multi-armed bandit (CMAB) framework is studied, which allows a general nonlinear reward function, whose expected value may not depend only on the means of the input random variables but possibly on the entire distributions of these variables.
Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations
• Computer Science, Mathematics
IEEE/ACM Transactions on Networking
• 2012
New efficient policies are shown to achieve regret that grows logarithmically with time, and polynomially in the number of unknown variables, for this combinatorial multi-armed bandit problem.
Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part II: Markovian rewards
• Mathematics, Computer Science
• 1987
A lower bound is provided for the regret associated with any uniformly good scheme, and a scheme which attains the lower bound for every configuration C is constructed, given explicitly in terms of the Kullback-Liebler number between pairs of distributions.
Fairness in Learning: Classic and Contextual Bandits
• Computer Science
NIPS
• 2016
A tight connection between fairness and the KWIK (Knows What It Knows) learning model is proved: a provably fair algorithm for the linear contextual bandit problem with a polynomial dependence on the dimension, and a worst-case exponential gap in regret between fair and non-fair learning algorithms.
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
• Economics, Computer Science
Found. Trends Mach. Learn.
• 2012
The focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed payoffs and adversarial payoffs.
Finite-time Analysis of the Multiarmed Bandit Problem
• Computer Science
Machine Learning
• 2004
This work shows that the optimal logarithmic regret is also achievable uniformly over time, with simple and efficient policies, and for all reward distributions with bounded support.


text:
### Abstract

This paper addresses the problems of what to imitate and how to imitate in simple uni- and bi-manual manipulatory tasks. To solve the what to imitate issue, we use a probabilistic method, based on Hidden Markov Models, for extracting the relative importance of reproducing either the gesture or the specific hand path in a given task. This allows us to determine a metric of imitation performance. To solve the how to imitate issue, we compute the trajectory that optimizes the metric, given a set of robot's body constraints. We validate the methods in a series of experiments, where a human demonstrator teaches through kinesthetic a humanoid robot how to manipulate simple objects.

### Bibtex reference

@article{Billard06,
author="A. Billard and S. Calinon and F. Guenter",
}

format: plain


text:
## Bernoulli

• Bernoulli
• Volume 22, Number 4 (2016), 2001-2028.

### Quantifying repulsiveness of determinantal point processes

#### Abstract

Determinantal point processes (DPPs) have recently proved to be a useful class of models in several areas of statistics, including spatial statistics, statistical learning and telecommunications networks. They are models for repulsive (or regular, or inhibitive) point processes, in the sense that nearby points of the process tend to repel each other. We consider two ways to quantify the repulsiveness of a point process, both based on its second-order properties, and we address the question of how repulsive a stationary DPP can be. We determine the most repulsive stationary DPP, when the intensity is fixed, and for a given $R>0$ we investigate repulsiveness in the subclass of $R$-dependent stationary DPPs, that is, stationary DPPs with $R$-compactly supported kernels. Finally, in both the general case and the $R$-dependent case, we present some new parametric families of stationary DPPs that can cover a large range of DPPs, from the stationary Poisson process (the case of no interaction) to the most repulsive DPP.

#### Article information

Source
Bernoulli, Volume 22, Number 4 (2016), 2001-2028.

Dates
Revised: February 2015
First available in Project Euclid: 3 May 2016

https://projecteuclid.org/euclid.bj/1462297673

Digital Object Identifier
doi:10.3150/15-BEJ718

Mathematical Reviews number (MathSciNet)
MR3498021

Zentralblatt MATH identifier
1343.60058

#### Citation

Biscio, Christophe Ange Napoléon; Lavancier, Frédéric. Quantifying repulsiveness of determinantal point processes. Bernoulli 22 (2016), no. 4, 2001--2028. doi:10.3150/15-BEJ718. https://projecteuclid.org/euclid.bj/1462297673

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#### Supplemental materials

• Supplement to “Quantifying repulsiveness of determinantal point processes”. We provide some illustrations of the nonuniqueness of the most globally repulsive DPP in the sense of Definition 1.1, as stated in Proposition 3.1. We also show the p.c.f.s and some realizations associated to different values of the parameters for the parametric families of DPPs introduced in Section 5.


text:
# Movavg Matlab

How to calculate moving average. First, install ipython html notebook, then install matplotlib 1. 85 mm, and 3. 这些函数与MATLAB的画坐标轴、控制项外观及添加标签和标题这些标准函数可以同时使用。金融工具箱也提供了一系列完整的可以和金融时间序列对象同时工作的制表函数。. Baixar movAv. then Matlab will give the same result as when one set EMA20 is most of the charting. Returns the angle (in radians) whose cotangent is z. hàm được Matlab cung cấp sẵn, ta cũng có thể tạo ra hàm mới để phục vụ cho. matlab的画图部分打算分两到三部分来讲，首先本节先大致介绍一下常用的集中画图工具以及一些遇到的画图细节处理，等继续深入研究再在下一节补充完整matlab的画图功能。. 1 ．课程类别，是指制订教学大纲时所针对的课程所属类别，包括通识类必修课、学科基础课、专业必修课、通识类选修课、学科基础选修课、专业选修课、专业实验课等。. Get answers to questions in Power Spectrum from experts. com Blogger 160 1 25 tag:blogger. 量化的模型开发大致分为以下几个环节： ①数据处理，看你用什么工具，R还是Matlab还是python，或者是c++，最好是工具本身的格式，这样速度会快的多，比如Rdata，或matlab的mat格式，或者python的npy格式，或者c++的二进制格式，还有就是你要用什么数据，分钟数据，切片数据，还是tick数据，根据你的. O meu objectivo é no entanto Para obter valores de 201406 até 201812. Con Matlab allora diventa semplicissimo, se la tua matrica è denotata con A basta digitare: A’ cioè il nome della matrice seguito dall’apostrofo e premere invio. 股票技术分析是证券投资市场中. The most notorious application of DSLs is the definition of the emulation of the syntax used in the MATLAB program, which data scientists are familiar with. " This blog details my progress in developing a systematic trading system for use on the futures and forex markets, with discussion of the various indicators and other inputs used in the creation of the system. As an example/test this is something like what I want (below) but I'm finding that my end result is not really close to how it should look. Replace back with the backward offset respect to current position, and forward with the forward offset respect to current position. Eighteen series of dry‐relaxed weft‐knitted fabric samples were produced with three different yarn twist levels (724. Gostaria de calcular a média do valor da coluna, em relação aos 250 registros anteriores. This is NOT a true matrix norm, since arrays of arbitrary rank are always flattened. matlab中文论坛鼎力支持，提供“在线交流，有问有答”网络互动答疑平台 详解matlab金融工具箱及金融算法分析与应用 涵盖43个量化投资指标、14种算法应用和23个算法案例 涵盖14种常用数据处理算法、8种股票预测机器学习算法 详解. Solution ! ----- ! PROGRAM MovingAverage: ! This program reads in a set of input values and a window value, ! and computes the moving average of the input. txt'); %输入股票代码;. The Financial Toolbox provides a set of functions that create several of the most commonly-used types of financial charts. Lead must be less than or equal to Lag. stata求分组移动最值等,各位老师同学好，借用一帖的数据问个问题：在sort code和price之后，在stata中怎样根据“code”变量，求“price”每30天的移动最小值、最大值或者比如30%分位数的值？. com > AlgoTrading2010. hàm được Matlab cung cấp sẵn, ta cũng có thể tạo ra hàm mới để phục vụ cho. It isn't the traditional moving average that is used in finance. The syntax for linebreak has changed. Excel: Matlab seems to give better answer to exponential decay, anyone know why? A co-worker of mine plotted the data (pHi1,alf) below in Excel and used the "add trendline" to fit the data. Including reorganization of each node to make them more readable. First, install ipython html notebook, then install matplotlib 1. First you have to find out where is your java home located. The MATLAB diff function is applied to the data in W1 and the result is smoothed by means of a 10 point moving average computed by the DADiSP movavg function. TSMOVAVG will be removed in a future release. dateaxis(Aksis, DateForm, StartDate) replaces axis tick labels with date labels on a graphic figure. The object uses either the sliding window method or the exponential weighting method to compute the moving average. 用matlab实现几十年逐月资料的平均值 我来答. Moving Average function. • Wrapping functions with appropriate Matlab names to simplify porting programs from Matlab or Octave to R. You divide by however many 1's there are in the kernel. txt'); %输入股票代码;. ssh identity set up so that % you can ssh into any of these machines without needing to type a password. Matlab has two functions in the financial toolbox for calculating NPV for fixed and variable cash flows (pvfix and pvvar respectively), npvFlow. Moving Average - MA: A moving average (MA) is a widely used indicator in technical analysis that helps smooth out price action by filtering out the “noise” from random price fluctuations. How to Design a Moving average filter?. 股票技术分析是以预测市场价格变化的未来趋势为目的,通过分析历史 图表对市场价格的运动进行分析的一种方法. Usando movavg (função Matlab padrão), criaremos arrays de Médias Móveis Exponenciais:. Setup Rx observer over the wire requires WCF Duplex callback: (1) ServiceContract need to define IObserverCallback, instead of subscrbe method lamda. % % DATEFORM - A scalar dictating the format of the date string tick labels. 8 pointfig（涨跌点图）函数 28 1. Obsolete BDT Functions : accrfrac. convolve(x, np. 本書全面系統地講解了matlab金融演算法設計應用，以及金融數據挖掘中趨向和發展趨勢指標，並結合具體的機器學習演算法分析，讓讀者深入學習和掌握matlab金融數據機器學習演算法。本書注重實戰，通過大量的案例，幫助讀者更好地理解本書內容。. Q 5: Use the deﬁned function ’MovAvg' to calculate the moving average of ECG data with diﬀerent window size. We don't know what your data are. 超前和滞后的移动平均图. p can be a number or the string ‘Infinity’ to get the L. "Trading is statistics and time series analysis. - 股票时间序列拟合算法，包括简单移动平均，加权移动平均等利用matlab实现 [ movavg. 这些函数与MATLAB的画坐标轴、控制项外观及添加标签和标题这些标准函数可以同时使用。金融工具箱也提供了一系列完整的可以和金融时间序列对象同时工作的制表函数。. Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. 在 Matlab 中，还可以利用一个简单的 m 脚本 (priceTxt. ‘Not Available’ / Missing Values Description. spread is a combination of a volume multiplier the trend thrust indicator, which calculates a spread by subtracting the short (206) 938-0570 fax:and206-938-1307 email: [email protected] Como se tornar um comerciante bem sucedido do Forex do Part-Time. It serves two main goals: •Collecting R scripts that can be demonstrated in courses on ‘Numerical Analysis’ or ‘Scientiﬁc Computing’ using R/S as the chosen programming language. Write a program to read in a set of real values and a window size, and use the above formulas to compute their moving averages. 2018-04-04 15:46:46,028 : INFO : main : NodeLogger : : : ######################################################################################### 2018-04-04 15:46. g (x+y)/2 then only apply to my signal. 文章来源：点宽量化社区文章传送门：【Matlab量化策略基础】——基于Matlab金融工具箱进行行情数据绘图大家在MATLAB界面上点击绘图按钮，就能够找到 FINANCE TOOLBOX 提供的绘制图标了。下面我们逐一进行学习。. The date and time information in the fints object becomes the TT time vector, while the remaining variables in the fints object become variables in TT. Description. In other words it's flat out wrong IMO. com > AlgoTrading2010. % \iffalse % % $Id$ % % *driver> \documentclass{ltxdoc} \usepackage{lstdoc, textcomp} \EnableCrossrefs \CodelineIndex% \begin{document} \DocInput{lstdrvrs. Remember the average is the sum divided by the number of elements in the sum. 25+ years serving the scientific and engineering community Log In Try Origin for Free Chat Buy. tsmovavg calculates the first simple moving average with window width of numperiod/2. Gretl Command Reference Gnu Regression, Econometrics and Time-series Library Allin Cottrell Department of Economics Wake Forest University Riccardo Jack Lucchetti Dipartimento di Economia Università Politecnica. Notice: We are no longer accepting new posts, but the forums will continue to be readable. First you have to find out where is your java home located. tsmovavg calculates the simple, Use MOVAVG instead. •Wrapping functions with appropriate Matlab names to simplify porting programs from Matlab or Octave to R. semilogx 65, 89 set 45. View Notes - hmk12 from ECE 302 at Purdue University, Fort Wayne. There is no longer support for the input arguments Lead and Lag, only a single windowSize is supported, and there is only one output argument (ma). Conv() has options 'same', 'valid', and 'full' depending on how you want to handle the "edge effects" where your window reaches the beginning and end of your data where you don't have the full 6 months of data. Pylab combines the functionality of pyplot with the capabilities of NumPy in a single namespace, and therefore you do not need to import NumPy separately. 文章来源：点宽量化社区文章传送门：【Matlab量化策略基础】——基于Matlab金融工具箱进行行情数据绘图大家在MATLAB界面上点击绘图按钮，就能够找到 FINANCE TOOLBOX 提供的绘制图标了。下面我们逐一进行学习。. Moving Average 8 Hallo, ich muss einen einfachen Moving Average mit Periode 10 berechnen. how many lines of header are there iii. MATLAB Forum - Averaging / Smoothing einer Kurve - hi, ja, 5 ist zufällig gewählt. Math Forum » Discussions » Software » comp. On a cursory read of the code, if I am correct there is an issue with the logic employed in tradeSignal if I have understood it correctly. This MATLAB function displays a highlow chart from a series of opening, high, low, and closing prices of a security. com/profile/05403984765785686176 [email protected] Wie implementiert man diesen Code Vielen Dank für schätzen und Zeit. TransaktionsID är unik För varje TransaktionsID vill jag beräkna medelvärdet för kolumnvärde över tidigare 250 poster Så för TransactionID 300 samlar du alla värden från tidigare 250 rader, sorteras nedåt av TransactionID och sedan i kolumnen MovAvg Skriv resultatet av genomsnittet av dessa värden jag letar för att samla in data. (See MATLAB help for details on usage). This version allows weighting of the mean and setting of the lag value (rather than just centring the average automatically). Lead: Number of samples to use in leading average calculation. R defines the following functions: Any scripts or data that you put into this service are public. pdf), Text File (. The moving average is the most common filter in DSP, mainly because it is the easiest digital filter to understand and use. candle(High, Low, Close, Open, Color) plots a candlestick chart given column vectors with the high, low, closing, and opening prices of a security. Face Optional Face or par value Default 100 bndyield 4 65 Examples Compute the from EE 518 at University of Southern California. Search current and past R documentation and R manuals from CRAN, GitHub and Bioconductor. DSLs are syntactic layers built on top of Scala native libraries. NA can be coerced to any other vector type except raw. For example, the subaxes along the diagonal in the i th column is replaced by histogram(X(:,i)). 【最后20免费名额】如何从一名 AI 爱好者晋升为 AI 开发者？理论+实践的 ModelArts AI实战营来袭！. Any MATLAB function or script can be processed just as if it were a native DADiSP function. Math Forum » Discussions » Software » comp. How to calculate moving average. 0 New Features/Enhancements. Highlight the characters vd. Charting Financial Data. 要在 MATLAB R2018a 中运行使用交错式复矩阵 API 编译的 Fortran MEX 文件，您必须使用 MATLAB R2018a Update 3。-largeArrayDims - 使用 MATLAB 大型数组处理 API。此 API 处理元素数目超过 2 31-1 个的数组。调用 LAPACK 或 BLAS 函数时必须使用此选项。. The angle function is simply. If you don't then you're not getting the average. Different types of moving average of a time series. The moving statistics System objects measure statistics of streaming signals in MATLAB ®. matlab中程序写到一半遇到某个函数需要help怎么做可以避免前面程序的运行 写到这里我想知道movavg是什么，于是help movavg. The practice of adjusting IQC target following a change in assay method. Sunday, 12 March 2017. n indicates the number of previous data points used with the current data point when calculating the moving average. The less power the initiator has with tarding to others, the foolish monkey s quickly forget and are distracted Recently signed up via matlab my opinion what to select th software Binary options methods, alpari shuts down uk products binary option about uk binary options with binary is accepting bitcoin as this status is a deposit bonus even. If the arguments are specified by their order, and not by parameter-value pairs, there is a nice way to accomplish this take advantage of varargin. Mathcad Functions Function Name (Parameters) acos (z) acosh (z) acot (z) Function Definition Returns the angle (in radians) whose cosine is z. Como se tornar um comerciante bem sucedido do Forex do Part-Time. DSLs allow software developers to abstract computation in terms that are easily understood by scientists. 2014-10-30 22:54:44,810 INFO main NodeLogger : ############################################################# 2014-10-30 22:54:44,826 INFO main NodeLogger : # # 2014. Re: Weighted & Hull Moving Average I know this is an excel forum but if you're constantly working with very large datasets I recommend looking into R programming. Set the lag as 6, which indicates the window size or number of periods for the moving average. M = movmean(___,dim) returns the array of moving averages along dimension dim for any of the previous syntaxes. If the closing price is greater than the opening price, the body (the region between the open and close price) is unfilled; otherwise the body is filled. Join GitHub today. For EMA, wilder=FALSE (the default) uses an exponential smoothing ratio of 2/(n+1), while wilder=TRUE uses Welles Wilder's exponential smoothing ratio of 1/n. (Optional) Vertical line color. For users having additional charting requirements, the Financial Time Series Toolbox provides a more comprehensive set of charting functions. MovingAverage System object™ computes the moving average of the input signal along each channel, independently over time. Learn more about moving, average, filter Hi everyone im kinda new with filter design in Matlab and in need of some help. It does not attempt to model market conditional heteroskedasticity any more than UWMA does. Averaging the symptoms in multidimensional condition monitoring for machines in nonstationary operation. 如何在Matlab中使用Plotly绘图 Plotly是一款适用于Phython、Java、Matlab等平台的在线绘图程序，其强大的制图能力，被广泛应用在学术。。。。等领域。 下面，我们从零开始，看看如何用Plotly美化Matlab中的图片！ Step1:： 首先，在Plotly官网上注册账号。. The following Matlab project contains the source code and Matlab examples used for trading strategy back tester. candle(Data) plots a candlestick chart from a series of opening, high, low, and closing prices of a security. First, install ipython html notebook, then install matplotlib 1. % See DATEAXIS for details on the date string formats. m This is a slightly more advanced version of movAv and provides an alternative to movavg and tsmovavg ("time-series moving average"). The text used in the course was "Numerical Methods for Engineers, 6th ed. Moving Average function. Months have different numbers of days in them. post-3813578615574558118. 〓 MATLAB 资讯公告 〓 MATLAB 技术论坛动态 MATLAB 人物访谈专栏 MathWorks 新闻资讯 〓 MATLAB 资源共享 〓 MATLAB/Simulink 腾讯讲堂 MATLAB/Simulink 视频教学 MATLAB/Simulink 原创精华 MATLAB/Simulink 电子文档 MATLAB/Simulink 程序源码 MATLAB/Simulink 书籍推荐 MATLAB/Simulink 文献论文 MATLAB. Matlab includes functions called movavg and tsmovavg ("time-series moving average") in the Financial Toolbox, movAv is designed to replicate the basic functionality of these. What are the input and output of the function? b. if ~exist('scaling','var') scaling = 1. m (siehe auch movAv2 - eine aktualisierte Version, die eine Gewichtung erlaubt) Beschreibung Matlab enthält Funktionen namens movavg und tsmovavg (Zeitreihen gleitender Durchschnitt) in der Financial Toolbox, movAv ist entworfen, um die grundlegende Funktionalität dieser zu replizieren. MATlab隶属函数怎么写？ [问题点数：40分，结帖人chang_bo]. n indicates the number of previous data points used with the current data point when calculating the moving average. m (lihat juga movAv2 - versi terbaru yang memungkinkan pembobotan) Deskripsi Matlab mencakup fungsi yang disebut movavg dan tsmovavg (time-series moving average) di Financial Toolbox, movAv dirancang untuk mereplikasi fungsi dasar ini. Click the button below to return to the English version of the page. this is definitely not the most robust barcode reader, but seems to work on low resolution barcode photos, with some amount of distortion. Package Name Description and HTML Help File----- a2reg Module to estimate models with two fixed effects aaplot Module for scatter plot with linear and/or quadratic fit, automatically annotated abar Module to perform Arellano-Bond test for autocorrelation abg Module to implement the Alpha-Beta-Gamma Method of Distributional Analysis aboutreg. There is no longer support for the input arguments Lead and Lag, only a single windowSize is supported, and there is only one output argument (ma). MBSWAL Weighted Average Life mortgagepool. Matlab instrument control code to implement a NVNA using a 4-Port VNA (Vector Network Analyzer). 空气污染指数的分形结构和其趋势预测研究. Is there a function that will do what I want or should I just get on with it? I've found movavg but it seems to do something else or maybe I just haven't followed it correctly. Changes in Version 1. " This blog details my progress in developing a systematic trading system for use on the futures and forex markets, with discussion of the various indicators and other inputs used in the creation of the system. Gt Hallo, gt gt Ich muss einen einfachen Moving Average mit Periode 10. wie lässt sich dies Abweichung der Anfangswerte und die Verschiebung für movavg, conf und filter in den Griff bekommen?. Eighteen series of dry‐relaxed weft‐knitted fabric samples were produced with three different yarn twist levels (724. Método De Media Móvil En Matlab. 本書全面系統地講解了matlab金融演算法設計應用，以及金融數據挖掘中趨向和發展趨勢指標，並結合具體的機器學習演算法分析，讓讀者深入學習和掌握matlab金融數據機器學習演算法。本書注重實戰，通過大量的案例，幫助讀者更好地理解本書內容。. Download miễn phí Đề tài Thiết kế hệ thống giải các bài toán tài chính thông qua Matlab. 基于Matlab的量化投资》这个系列帖子除了讨论量化投资的方法和理念，还会讨论Matlab这个工具的一些实用问题，之所以采用Matlab来做量化投资而没用采用MC，TB，MT4，天软等其他量化（程序化）平台，一是因为自己用Matlab也7年左右比较熟悉；二是自己使用Matlab来. What Is the Best First Order IIR (AR Filter) Approximation to a Moving Average Filter (FIR Filter)? Using the following code on MATLAB yields something equivalent. The proposed system incorporates neuro. Gt gt Wie kann ich das tun in Matlab gt gt gt gt Ich benutze movavg (Serie, 1,20,0) aber ich bin nicht Sicher, wenn das richtig ist Gt gt gt gt Was soll ich für Blei und Verzögerung verwenden gt gt gt gt Danke, gt gt Miguel Ich brauche den Simple Moving Average in seiner normalen Form zu verwenden, weil ich eine C NET Bibliothek erstellt habe. First you have to find out where is your java home located. The syntax of movavg function in MATLAB is described below: [Short, Long] = movavg(Asset, Lead, Lag, Alpha) where Lead is Number of samples to use in leading average. Trading Axis System. A moving average is a technique to get an overall idea of the trends in a data set; it is an average of any subset of numbers. Search for : Matrix. The running mean is a case of the mathematical operation of convolution. 程序化交易量化交易策略代码下载分享,交易源代码,量化交易培训视频,培训,视频,程序化交易培训,程序化交易视频,matlab量化,Python量化,r语言量化,mc视频,tb培训视频,金字塔股票交易系统培训视频,量化股票交易,期货量化程序化交易,量化源代码分享下载,交易书籍pdf,股票交易书籍pdf,期货交易书籍pdf,期权. Algorithmic trading is a trading strategy that uses computational algorithms to drive trading decisions, usually in electronic financial markets. 要在 MATLAB R2018a 中运行使用交错式复矩阵 API 编译的 Fortran MEX 文件，您必须使用 MATLAB R2018a Update 3。-largeArrayDims - 使用 MATLAB 大型数组处理 API。此 API 处理元素数目超过 2 31-1 个的数组。调用 LAPACK 或 BLAS 函数时必须使用此选项。. As an example/test this is something like what I want (below) but I'm finding that my end result is not really close to how it should look. Internal quality control data of the index laboratory were acceptable prior to the product recall. First, there is the general time looping, then there is a 5-period loop with movavg(), and last there is a 2-period loop with pch(). Measure Statistics of Streaming Signals. GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together. MOVAVG Leading laggingmoving averages chart. Excel: Matlab seems to give better answer to exponential decay, anyone know why? A co-worker of mine plotted the data (pHi1,alf) below in Excel and used the "add trendline" to fit the data. "Trading is statistics and time series analysis. Plot and view the signal in time domain. 模型回测，据我理解就是一个大循环:. movavg function lead and lag meaning. Search current and past R documentation and R manuals from CRAN, GitHub and Bioconductor. Also, as I'm faily new to matlab, from C, I tend to use for loops which I'm aware is not the way to use Matlab. Index was out of range. 斯托克_新浪博客,斯托克,几种经典的滤波算法(转),C++时间与字符串转换,期货日内炒单交易技巧及单盘感训练,Matlab 正则表达式零基础起步教程(转. matlab中程序写到一半遇到某个函数需要help怎么做可以避免前面程序的运行 写到这里我想知道movavg是什么，于是help movavg. Prys binêre Dominator aflaai demos binêre strategieë. Moving Avg calculation. The angle function is simply defined as atan2(Im(z), Re(z)). doc xlsread doc movavg. 这些函数与MATLAB的画坐标轴、控制项外观及添加标签和标题这些标准函数可以同时使用。金融工具箱也提供了一系列完整的可以和金融时间序列对象同时工作的制表函数。. Trading Axis System. Furthermore, if you import pylab, pyplot, and NumPy functions can be called directly without any reference to a module (namespace), making the environment more similar to Matlab. 金融matlab-第22章_院校资料_高等教育_教育专区 1115人阅读|13次下载. Moving Average - MA: A moving average (MA) is a widely used indicator in technical analysis that helps smooth out price action by filtering out the “noise” from random price fluctuations. use case with 11 trials to analyze. Solution ! ----- ! PROGRAM MovingAverage: ! This program reads in a set of input values and a window value, ! and computes the moving average of the input. 2007-01-01. Matlab双均线分钟K线策略例子\MovAvg. tsmovavg calculates the simple, Use MOVAVG instead. txt'); %输入股票代码;. Write a program to read in a set of real values and a window size, and use the above formulas to compute their moving averages. Moving Average - MA: A moving average (MA) is a widely used indicator in technical analysis that helps smooth out price action by filtering out the "noise" from random price fluctuations. Description. Moving averages are often used to help highlight trends, spot trend reversals and provide trade signals. These functions are more suitable for one-time computations on data that is available in a batch. Hello, I am trying to find the rolling 30 day EMA for a time series without using a for loop (I have a lot of data). Search for : Matrix. Plot and view the signal in time domain. The MATLAB diff function is applied to the data in W1 and the result is smoothed by means of a 10 point moving average computed by the DADiSP movavg function. Columnvector userspecified X-axis tick scalardictating datestring tick labels. "Trading is statistics and time series analysis. Explicitely listing about 200 MATLAB-emulating function( name)s. movavgとfilter関数の速度比較. m, change:2010-11-23,size:6035b %% Algorithmic Trading with MATLAB(R): Simple Lead/Lag EMA % This demo is an introduction to using MATLAB to develop and test a simple % trading strategy using an exponential moving average. Dismissed matlab(), using it now for infos only, not assigning any MATLAB function names to the environment (because of CRAN policies). Obsolete BDT Functions : accrfrac. JIRA Summary Details ORG-5528, ORG-5991 New Axis dialog with tree nodes for the X, Y, and Z axes. Saturday, 26 August 2017. Service quality framework for clinical laboratories. Enter dates as serial date numbers or date strings. This should not be correct as my raw data is 466x1 and a movavg of '200' must be no more than 266x1 as there is insufficient data points for the first 200 entries to creat the average. h 00003 \brief The Zenautics Matrix Class 00004 \author Glenn D. Electricity Theft Detection on a Low Voltage Reticulation Environment Thesis presented in partial fulfillment of the requirements for the degree of Master of Science. MATLAB is known especially for its highly intuitive and interactive programming. 股票技术分析是证券投资市场中非常普遍应用. To help you convert from the older fints to the newer timetable functionality, use the following information. A Bollinger band chart plots actual data along with three other bands of data. To obtain the stock performance in 2014, use the MATLAB timerange function to select rows of the timetable. Plotting uploads/day. Furthermore, if you import pylab, pyplot, and NumPy functions can be called directly without any reference to a module (namespace), making the environment more similar to Matlab. In Matlab, these data (Open, High, Low, Close, Spread) will be also loaded using a simple m-script (priceTxt. MATLAB的M函数文件还可以具有个数不确定的输入、输出. Uses Matlab/Octave function. 所属分类：其他 开发工具：matlab 文件大小：20KB 下载次数：1 上传日期：2017-12-05 02:32:49 上 传 者：uku. Note that the movavg and movstd in Table 2 are the average and standard deviation of a time series, respectively, over the past m trading days. 基于Matlab的量化投资》这个系列帖子除了讨论量化投资的方法和理念，还会讨论Matlab这个工具的一些实用问题，之所以采用Matlab来做量化投资而没用采用MC，TB，MT4，天软等其他量化（程序化）平台，一是因为自己用Matlab也7年左右比较熟悉；二是自己使用Matlab来. m, change:2012-04-30,size:3513b %% yafcoTest1 % 脚本程序 % Last Modified by % % 程序实现测试所使用的MATLAB版本：MATLAB R2011b(7. This should not be correct as my raw data is 466x1 and a movavg of '200' must be no more than 266x1 as there is insufficient data points for the first 200 entries to creat the average. khích các thử nghiệm. MATLAB金融算法分析实战：基于机器学习的股票量化分析，作者：吴婷 余胜威 著，机械工业出版社 出版，欢迎阅读《MATLAB金融算法分析实战：基于机器学习的股票量化分析》，读书网|dushu. Moving Average Fenster Filter Matlab. There is no longer support for the input arguments Lead and Lag, only a single windowSize is supported, and there is only one output argument (ma). com > AlgoTrading2010. DESIGN OF A LEAD CONTROLLER USING MATLAB (SAMPLE ASSIGNMENT) For any Help with Design of a lead controller Assignment upload your Homework Assignment by clicking at "Submit Your Assignment " button or you can email it to [email protected] Matlab-style line and block comments. If you are a Matlab (or similar) user, you may think jj is an 84 × 1 vector, but it's not. MacGougan. help-octave (thread) Advanced [Prev exponential moving average from MOVAVG not correct?, Tim Octave equivalent to Matlab buttondownfcn?, Søren. Furthermore, if you import pylab, pyplot, and NumPy functions can be called directly without any reference to a module (namespace), making the environment more similar to Matlab. The default behavior for movavg is unweighted, or a simple moving average. MovingAverage System object™ computes the moving average of the input signal along each channel, independently over time. 使用matlab函数构建三维立方体的几种方法. If you use fints or the associated methods, you receive a warning. 所属分类：matlab例程 开发工具：matlab 文件大小：1KB 下载次数：26 上传日期：2011-06-10 21:07:58 上 传 者：sha. How does matlab calculate the initial points of a moving average? for example if my timeseries matrix TS is 10x1 and i want 2 and 5 period EMAS then movavg(TS, 2, 5, 'e') will return two 10x1 matrices even though the inital points in theory dont have enough samples to calculate the ema yet. MATLAB Forum - Averaging / Smoothing einer Kurve - hi, ja, 5 ist zufällig gewählt. If you didn't matlab , then you'd simply site summing values and the resulting image would be times as bright rather than in code same intensity range as the original. this is definitely not the most robust barcode reader, but seems to work on low resolution barcode photos, with some amount of distortion. gt Wie kann ich dies in Matlab gt gt Ich benutze movavg (Serie, 1,20,0), aber ich bin nicht sicher, ob dies richtig ist. Jun 28, 2017 · You can use np. Return the present value V of an investment that will pay off P in one lump sum at the end of N periods, given the interest rate R. Veja a página da política de. These functions work with standard MATLAB ® functions that draw axes, control appearance, and add labels and titles. Get pricing and licensing information for MATLAB and Simulink. On the Data tab, in the Analysis group, click Data Analysis. 1 Handbuch deutsch. Learn more about statistics, zscore, matlab, array MATLAB. If you don't then you're not getting the average. Ons is op soek na 'n ernstige aanlyn / aflyn verkope mense wat kan genereer betaal lei tot ons opsies / binêre opsies handel webwerf. 《matlab金融算法分析实战 基于机器学习的股票量化分析》，作者：吴婷 余胜威著，机械工业出版社，9787111573005，品类：传记>其他，以及《matlab金融算法分析实战-基于机器学习的股票量化分析》的摘要、书评、在线阅读等信息，为您购买《matlab金融算法分析实战-基于机器学习的股票量化分析》提供. At futures io, our goal has always been and always will be to create a friendly, positive, forward-thinking community where members can openly share and discuss everything the world of trading has to offer. Project Management. See ColorSpec in the MATLAB documentation for color names. % % See also BOLLING, HIGHLOW, CANDLE, POINTFIG. Principal value for complex z. movavg是一个取移动平均很好用的命令。之前对于一个股价序列wdata，为了取ma5和ma20，我不得不写好几个循环。其中ma5是：for t=i-4:i ma5(t,1)=wdata(i) MAT 发布于 MATLAB基础 2017-04-11. How to calculate moving average. matlab金融算法分析实战：基于机器学习的股票量化分析 电子书 租阅. The moving average is the most common filter in DSP, mainly because it is the easiest digital filter to understand and use. No Matlab, estes dados (Open, High, Low, Close, Spread) também serão carregados usando um script m simples (priceTxt. matlab之 时间序列MA（q）模型. Use the link below to browse all conversations related LabVIEW or select "Start a Topic" below to ask a question to the community of LabVIEW users. doc xlsread doc movavg. Consider for instance “PRT movavg(pch(y), 5);”. Exponentially weighted moving average estimation is widely used, but it is a modest improvement over UWMA. других часто встречающихся случайных величин, например стьюдентовой. plot 73, 89, 217 poly 33. Learn more about matlab function, finance MATLAB. com/profile/05403984765785686176 [email protected] Different types of moving average of a time series. 2 Now invoke the function MovAvg , with the arguments sig_out=MovAvg(noisy_pulse,N) Here N is the number of samples over which average is computed. If you have missing days or missing months, you should first run interp1 on it to fill them in. Moving averages are often used to help highlight trends, spot trend reversals and provide trade signals. movavg is updated to accept data input as a matrix, table, or timetable. Function Defaults. What is confusing me is that they are all the same size, "double 466x1". 〓 MATLAB 资讯公告 〓 MATLAB 技术论坛动态 MATLAB 人物访谈专栏 MathWorks 新闻资讯 〓 MATLAB 资源共享 〓 MATLAB/Simulink 腾讯讲堂 MATLAB/Simulink 视频教学 MATLAB/Simulink 原创精华 MATLAB/Simulink 电子文档 MATLAB/Simulink 程序源码 MATLAB/Simulink 书籍推荐 MATLAB/Simulink 文献论文 MATLAB. load the ﬁle header (hint: very similar to how the ecg data was loaded ) c. If the closing price is greater than the opening price, the body (the region between the opening and closing price) is unfilled. DSLs are syntactic layers built on top of Scala native libraries. MACD trading strategy. Types of available moving averages are: s for “simple”, it computes the simple moving average. 如何在Matlab中使用Plotly绘图 Plotly是一款适用于Phython、Java、Matlab等平台的在线绘图程序，其强大的制图能力，被广泛应用在学术。。。。等领域。 下面，我们从零开始，看看如何用Plotly美化Matlab中的图片！ Step1:： 首先，在Plotly官网上注册账号。. • Wrapping functions with appropriate Matlab names to simplify porting programs from Matlab or Octave to R. 8 pointfig（涨跌点图）函数 28 1. com > AlgoTrading2010. Thank you for this collection. I have monthly data and would like to calculate a 6-month backward moving average. For the running mean, you slide a window along the input and compute the mean of the window's contents. These functions work with standard MATLAB ® functions that draw axes, control appearance, and add labels and titles. Previously, when using table input, the first column of dates could be serial date numbers, date character vectors, or datetime arrays, and you were required to have specific number of columns. % -*- texinfo -*- % @deftypefn {Function File} {} movavg (asset, lead, lag) % @deftypefnx {Function File} {} movavg (asset, lead, lag, alpha) % @deftypefnx {Function. html mode html moler html movavg html muller html nchoosek html ndims html nearest_spd html. movavg Leading and lagging moving averages chart These functions work with standard MATLAB ® functions that draw axes, control appearance, and add labels and titles. R defines the following functions: Any scripts or data that you put into this service are public. Q 6: Generally describe the diﬀerence between a Matlab script and a Matlab function. n indicates the number of previous data points used with the current data point when calculating the moving average. You can choose any weights b j that sum to one. com moving average from the long. Enough level of smoothing was implemented using a 10 points window. % Moving average function % % avgx=movavg(x,n) % % Computes the "moving average" of the vector or matrix x, % averaging n terms at a time. Quick question/explination Re 'movavg'. Matlab là gì? (Xem chi tiết trong [1] [2], TLTK2 ) Matlab (Matrix Laboratory) là phần mềm của tập đoàn The Math Works, Inc. Anda tidak perlu mengganti layar antara Matlab, Ansys dan UltraEdit atau PSPad lagi, saat Anda melakukan FEM-Analysis. First, there is the general time looping, then there is a 5-period loop with movavg(), and last there is a 2-period loop with pch(). movavg matlab下的股票移动平均函数，用于计算股票的移动平均线.


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Open access peer-reviewed chapter

# Successes, Threats, and Factors Influencing the Performance of a Community-Based Wildlife Management Approach: The Case of Wami Mbiki WMA, Tanzania

By Sayuni B. Mariki

Submitted: June 14th 2017Reviewed: May 29th 2018Published: November 5th 2018

DOI: 10.5772/intechopen.79183

## Abstract

Over three decades, community-based wildlife management (CBWM) has been promoted as a promising option for achieving biodiversity conservation and community development. From the outset, different development partners have facilitated implementation of this process. However, studies on its effectiveness are limited, and the reported outcomes are mixed. In this study, I used qualitative methods (interviews, focus group discussion, informal interviews, direct observations, and secondary data) to assess the performance of the CWBM approach in Tanzania in view of its contribution to sustainable natural resource management and enhanced local livelihoods. The study used the Wami Mbiki Wildlife Management Area (WMA) as a case study. While the CBWM scheme was designed to achieve dual objectives, this study found that the resultant efforts, in this case, were largely unsuccessful following the end of donor support in 2011. The WMA lacks effective anti-poaching patrols, leading to increased illegal activities, such as poaching, overgrazing, tree cutting, and charcoal burning. Although the community-based organization was successfully established as an institution to provide leadership in natural resource management and tourism development, some key actors still lack necessary entrepreneurship and managerial skills, transparency, and good relationships to ensure its success and sustainability.

### Keywords

• community-based
• natural resources management
• threats
• Wami Mbiki
• wildlife management area

## 1. Introduction

### 1.1. Background

Over the past 3 decades, in most developing countries, there has been a paradigm shift in the management of natural resources from a top-down, state-centered approach to more decentralized approaches [1, 2, 3]. The new approach has been driven by factors such as constrained resources for conservation, biodiversity loss, and burgeoning rural populations [4, 5]. This alternative approach, which seeks to integrate wildlife conservation and rural development objectives, has been widely promoted as a strategy across the developing world that aims to conserve biodiversity, while simultaneously enhancing the rural livelihoods [6]. Moreover, this strategy provides an arena for other conservation strategies, for instance payment for ecosystem services, on which to build [7, 8]. The proponents of community-based wildlife management (CBWM) argue that devolving control of natural resources to local communities increases local participation, improves management of those resources, reduces conflicts, thereby improving the resource base and provision of benefits to communities [9, 10, 11, 12]. Since its inception, many international conservation and development agencies and partners have supported the CWBM approach [13, 14].

However, several studies from different parts of the world have revealed unexpected outcomes, mixed results in performance, and some degree of disillusionment with the CBWM approach [9, 10, 15]. Some studies show that, despite its popularity, CBWM has not met expectations of halting biodiversity depletion and poverty reduction among the local communities that have implemented it (e.g., [16, 17, 18, 19]). However, a few successful and convincing reports have demonstrated a positive correlation between livelihood improvement and conservation. For instance, Communal Area Wildlife Conservancies in Namibia are considered a major success story as the result of reduced illegal wildlife use and recovery of game populations [20]. Elsewhere, the impact of CBWM is harder to discern as many studies focus on the area of land conserved rather than effectiveness of the program [5]. Mixed factors have been reported to affect CBWM performance, such as the type of communities involved in CBWM, resource governance, effectiveness of the institutional framework, availability of skilled personnel, stakeholders’ capacity, reinvestment of CBWM projects, revenue sharing, and community cohesion [21, 22].

This chapter examines the performance of Wami Mbiki Wildlife Management Area (WMA) in Tanzania. WMAs are community-run protected areas, where several villages come together and set aside land for wildlife conservation. In return, these villages generate income mainly through sport hunting and photographic tourism [23]. Under this arrangement, the wildlife resource remains the property of the state although the villagers acquire the user rights of this resource. This chapter seeks to answer three main questions: (a) To what extent has the Wami Mbiki WMA contributed to sustainable natural resource conservation and enhanced rural livelihoods? (b) What are the threats facing this particular WMA? and (c) Which factors influence the performance of this WMA?

This study adopts the World Conservation Union’s (IUCN) definition of a “protected area” as a clearly defined geographical space, recognized, dedicated, and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values [24]. I proceed by first presenting the CBRNM framework; thereafter, I describe briefly the history of WMAs before outlining the methodology of the study, then presenting the results and providing a discussion. Generally, I conclude that more anti-poaching effort is needed to save the remaining wildlife because of the multiple threats to the survival of wildlife in the study area.

### 1.2. The CBNRM framework

Community-based natural resource management (CBNRM) is the management strategy of natural resources aiming to reduce poverty, conserve natural resources, and promote good governance and decentralization [25]. It requires some degree of devolution of decision-making power and authority over natural resources to communities and community-based organizations [26]. The CBNRM approach is built upon common property theory which argues that common pool resources can be utilized sustainably provided certain principles are applied [27]. These principles include the autonomy and recognition of the community as an institution, proprietorship, and tenurial rights, rights to make the rules and viable mechanisms to enforce them, and on-going incentives in the form of benefits that exceed costs [27, 28]. CBNRM is based on three key assumptions: (a) local people are better placed to conserve natural resources; (b) people will conserve a resource only if the benefits exceed the costs of conservation; and (c) people will conserve a resource that is directly linked to their quality of life [55, 56].

The local communities living with natural resources are best placed to conserve and manage them as they have sufficient knowledge and experience. A community in this context is defined as a group of people living within a legally defined geographic area with diverse socio-economic interests and capabilities with a shared interest in conserving natural resources [29]. Before colonialism, traditional institutions existed in local communities which had developed systems and practices for natural resource management [30, 31, 32, 33]. Other studies point out that local communities share an interest in conservation of natural resources as their livelihoods are intricately connected to these resources (e.g., [34]). Thus, people will conserve and manage resources that they perceive to contribute positively to their livelihoods [35]. Also, people living closest to natural resources have more to lose from depletion and degradation of these resources [36]. If given proper support and incentives, they will be most likely to effectively conserve them. Such an approach is also a cost-effective alternative to the fortress (fences and fines) approach to natural resource management.

In order to ensure sustainable and effective management of natural resources, the benefits must outweigh the costs [37, 38, 39]. Ostrom et al. [40] demonstrate this by pointing out that “an individual’s choice of strategy in any particular situation depends on how he/she perceives and weighs the benefits and costs of various strategies and their likely outcomes.” Therefore, communities will only embrace a participatory approach as a long-term livelihood strategy if it proves attractive to them [41]. For sustainable management of natural resources, participation of local communities is imperative. Participation can best be achieved through decentralization of authority over the resources and promotion of good governance. Governance, in simple terms, means the process of decision-making and the process by which decisions are implemented (or not implemented) [42]. However, good governance includes several key elements, that is, participation, rule of law, transparency, responsiveness, consensus-orientation, equity and inclusiveness, effectiveness and efficiency, and accountability. Based on this premise, this chapter considers these issues in theory and in practice by exploring the case of the Wami Mbiki Wildlife Management Area.

### 1.3. The wildlife management areas in Tanzania

In the 1980s, Tanzania experienced a wildlife crisis where almost half of its elephant population and entire black rhino population were wiped out through poaching [33]. Learning from the past failures, the government of Tanzania formulated the first comprehensive wildlife policy in 1998 advocating the devolution of natural resources governance to local communities. This policy provided opportunities that linked sustainable natural resource conservation and rural development [23]. The policy recognized the establishment of Wildlife Management Areas (WMAs) as one of the strategies for devolving management responsibilities and rights to local communities. WMA regulations were formulated in 2002 alongside the establishment of 16 pilot WMAs. The policy encouraged wildlife management at the local level by allowing local landholders to “manage wildlife on their land for their own benefit” ([23]: 13) in order to enhance conservation and alleviate poverty through sustainable utilization of natural resources [23]. The main assumption was that if local people acquire ownership of wildlife resources and obtain tangible benefits from them they are likely to manage the resources sustainably. This required a shift from state-centered control of natural resources to local communities, which also, maximized the value of wildlife-rich land compared to alternative land use so as to improve the standard of living and in turn provide incentives for communities to support conservation efforts.

The first pilot WMAs were established in 2003 and user rights granted in 2006 and 2007. Additional WMAs were created subsequently [43]. Currently, there are 17 WMAs that have attained authorized association (AA) status while 22 are in various stages of development. The number of villages in each WMA can range from 2 to 30. The WMAs cover over 23,000 km2 of Tanzania’s land surface. In designating a WMA, several villages have to set aside portions of their land for wildlife conservation and develop management plans and regulations for managing the land. Government approval is required for the plans to become operational and for formal ownership to be given to the communities. To be able to manage the WMA, an authorized association (AA), that is, a Community-based Organization (CBO) representing the member villages must be established and granted user rights by the Minister of Natural Resources and Tourism. Virtually all WMAs have been developed with external support (e.g., USAID, GTZ, DFID, UNDP, GEF, DANIDA, WWF, AWF, WCS, and ADAP). The costs of establishing a WMA are far beyond community affordability and are estimated to range between US$250,000 and$300,000 [44].

There has been considerable criticism of the concept of WMAs, facilitation, and devolution of management responsibilities. In practice, the government has retained considerable residual control of WMAs and has attempted to recentralize control of natural resources [45]. Administrative processes to establish WMAs have been criticized as bureaucratic, excessively complex, and with many hurdles hindering their development [46]. Although some WMAs generate revenue for their member villages, there is insufficient evidence that benefits exceed income received prior to the WMAs establishment [47]. The Wildlife policy was revised in 2007 and “Non-Consumptive Utilization of Wildlife Regulations” were formulated in 2008 which recentralized many powers and benefits to the government [46]. However, new regulations issued in 2012 have afforded more control and benefits to communities [48].

## 2. Research methodology

### 2.1. Study area: the Wami Mbiki Wildlife Management Area

The study was conducted in the Wami Mbiki Wildlife Management Area located in the central eastern part of Tanzania between latitudes 06°10′00″ and 06°30′00″ S and longitudes 37° 50′00′ and 38°15′40″ E. The WMA’s core wilderness area covers 2500 km21, combining land from 24 villages. The WMA was first identified in 1995 in a joint effort between local elders and tourist hunters who were concerned about unsustainable utilization of natural resources that threatened the future of the area and the livelihoods of the surrounding communities. It therefore started as a pilot project in 1997 with support from the Danish Hunters Association (DHA) and funding from DANIDA. The CBO named the Wami Mbiki Society (WMS) was registered on 15 July 2002 under the Societies Ordinance Act, with registration no. 11491. It became an authorized association in January 2007 and received user rights in April 2007 [49]. The WMS comprises representatives from member villages.

Facilitation of the Wami Mbiki WMA through DHA took place in three phases. The first phase (1998–2001) aimed at developing the WMA, sending Village Game Scouts (VGS) for training and building guard stations. The second phase (2002–2006) was mainly for building staff capacity, delegate training, and development activities in the surrounding villages. The third phase (2006–2011) focused mostly on business to attract investors. Generally, the funds received from DHA supported data collection for the development of land use plans (LUPs), business plans, and the legal establishment of the Society, formalizing a constitution, a general management plan, bylaws, community education and capacity building, protection of the natural resources as well as operational and technical expenses for the WMS.

The Wami Mbiki WMA has abundant flora and fauna. Wildlife species found in the WMA include lion, leopard, elephant, hartebeest, waterbuck, greater and lesser kudu, giraffe,buffalo, yellow baboon, hyena, wild dog, cheetah, bush pig, hippopotamus, and zebra among others. The area is also rich in birdlife, including varieties of miombo specialties such as the racket-tailed roller, pale-billed hornbill, rufous-bellied tit, and miombo wren-warbler, as well as many other birds. The primary vegetation type inside the WMA is open and closed woodlands, bushland, and inundated grasslands. The WMA has both rivers and natural ponds that serve as sources of water for wildlife. The Wami River divides the WMA into two segments (north and south) (Figure 1).

The climate of the area is warm tropical with short rains from October to December and long rains from March to May, ranging between 600 and 1200 mm per annum. The average annual temperature ranges between 26 and 28°C. The altitude ranges between 350 and 400 m above the sea level. The area is interspersed with rocky hillsides of thin soil cover and valleys with deep clay or alluvial soils.

The major land uses are agriculture, wildlife and forest conservation, livestock grazing, and human settlements [50]. Subsistence farming is the major economic activity (95%) followed by livestock grazing [51]. The main food crops include sweet potatoes, beans, cow peas, bambara nuts, tomatoes, pumpkins, and finger millet among others. Cash crops include pineapples, pumpkins, tomatoes, cashew nuts, and cow peas. Other income-generating activities for local communities include beekeeping, masonry, and small-scale business. Moreover, a few residents are employed as teachers, hospital staff, and prison staff. The population of member villages in 2006 was over 65,935. The main ethnic groups are Wakwere, Wazigua, Wamasai, and Wagogo.

### 2.2. Data collection

Data were collected using interviews, focus group discussions, direct observation, and informal discussions. Fifty-one interviews were conducted with people who were purposively selected and key informants. Interviewing was terminated when further data added no new insights to the research questions. Interviews lasted between 1 and 2 hours. Participants were encouraged to express themselves freely, and they were guaranteed anonymity and confidentiality. Interviews were conducted in Kiswahili, a common language in the study area. Moreover, four focus group discussions with generally 8–12 people were held to gather various viewpoints on the success and constraints of the WMA.

Finally, I reviewed relevant documents such as government policy documents, reports, and several existing published and unpublished studies conducted in the area. I used a tape recorder to record the data. Soon after data collection, the information was transcribed, organized into categories, and grouped into themes. The identified core themes were linked to the aims of the study, and these served as the basis for my findings and discussion presented below. Statements supported by appropriate quotations from the interviews are provided where necessary to elucidate a theme.

## 3. Results and discussion

### 3.1. Contribution of the WMA to biodiversity conservation and community welfare

#### 3.1.1. Contribution of the WMA to biodiversity conservation

The study showed a notable improvement in biodiversity conservation in Wami Mbiki between 1997 and 2011. This improvement is attributed to the efforts of the DHA through funding support from DANIDA. The funds facilitated patrol activities, payment of staff salaries, and support for community development projects. The wildlife numbers increased notably as shown in Table 1 below. Information from the Bagamoyo District Game Officer also indicated that wildlife killed by poachers decreased from 40 animals in 2006 to 14 in 2011.

YearNumber of large mammals
19975000
200412,578
200920,000
201031,900

### Table 1.

Number of wildlife from 1997 to 2010.

Source: Refs. [44, 50].

Despite the impressive increase over almost a decade, the 7 years that followed this success experienced a decline of about two thirds of the wildlife population, coinciding with the ending of donor support in 2011. This is manifested by infrequent and low sightings of some species such as lion, leopard, eland, sable antelope, giraffe, elephant, zebra, and reedbuck. Wild dogs and cheetahs are not seen in the area anymore, suggesting the possibility of local extinction. Field estimates by the VGS (see Table 2 below) show that all animals (except crocodiles and hippos) have decreased significantly. The respondents acknowledged an increase of crocodiles. This is partly because they are not hunted and have abundant food (i.e., livestock and wildlife).

Animal species20102017
Hippopotamus500350
Impala18,000Less than 1000
Sable antelope1000Less than 60
HartebeestAbout 700Less than 100
ElandAbout 600Less than 100
GiraffeAbout 500–600Less than 50
ZebraAbout 800Less than 70
GrysbokAbout 300Less than 50
ReedbuckAbout 200Less than 20
BuffaloAbout 2000less than 300
KuduAbout 500Less than 100
WarthogAbout 2000Less than 200

### Table 2.

Field estimates of wildlife populations in 2010 and 2017.

Source: Game scouts report.

Interviews show that elephant sightings are rare, but elephant signs such as dung, foot prints, and carcasses are observed in the area. The carnivores (lions and leopards) are decreasing partly because some are killed by pastoralists in retaliation for predation on livestock.

#### 3.1.2.1. Development projects

During phase 1 (1998–2001), DHA supported development projects in 14 villages—Dihinda, Kwamsanja, Lukenge, Kunke, Kanga, Kidudwe, Maseyu, Mwidu, Kaloleni, Tukamisasa, Diozile, Ponwekiona, Kwaruhombo, and Kifuleta. In the second phase (2002–2006), DHA distributed 1M TZS (2,000US$) to each member village per annum. Furthermore, from 2008 to 2011, the WMA earned 20M TZS (about 17,000 US$) annually from investment in photographic tourism. Half of the revenue was disbursed to the villages.

Several projects were implemented using DHA support and revenue collected from the WMA (see Table 3). These projects were implemented under the supervision of DHA staff.

Type of projectNumber
Construction of classrooms35
Construction of doctor’s house1
Construction of teachers’ offices2
Construction of teachers’ houses10
Construction of water pond1
Construction of culvert1
Construction of meeting hall1
Construction of dispensaries3 (of 14, 12. and 3 rooms)
Construction of pit latrines2 latrines (of 4, 2, and 4 holes)
Drilling of water well2
Renovation of classrooms23
Renovation of teachers’ office1
Renovation of dispensaries2
Finishing of village government office1
Making of desks40

### Table 3.

Projects supported by DHA and WMA revenue.

#### 3.1.2.2. Employment

The DHA employed 47 people; most of them were from the member villages. Following the termination of support and the concession fee, the number of staff decreased by more than a half, partly due to the lack of income to pay staff (see Table 4 below).

StaffNumber
20072016
Game scouts2620
Protection officer10
Drivers5 (4 for patrol cars, 1 for tractor at Mkongo Camp)1
Community workers40
Cashier11
Messenger6 (4 at Mkongo Camp, 2 at Morogoro Office)0
Secretary20
Accountant10
Manager10
Total4721

### Table 4.

Number of staff in 2007 and 2016.

In June 2011, the WWF started supporting WMA. The VGS were given an allowance of 5000 TZS (2USD) per day. The allowance stopped in February 2012 as WWF ceased its activities in the area. The patrol activities continued as VGS expected payment from WWF once it resumed its activities. However, when WWF re-commenced its activities in July 2013, it did not pay the VGS their arrears of salary. Consequently, the VGS sued the WMS in the labor court. Since January 2014, the VGS have received no pay apart from a portion of fines imposed on apprehended offenders. Due to the lack of payment and work equipment, the WMA has retained few VGS. Currently, the VGS conducts occasional foot patrols near the WMA headquarters and a few areas under severe threat (see Table 5).

20072017
Work equipmentNumber (s)
Cars–41 car is used occasionally, 3 are not working
Motorcycles—6Motorcycles—3
Tractor—1Not working
Boats—2Not working
Weapons—13Working—8, fell into the river—2, held at a police station—2, broken by poachers—1
Mkongo camp buildingsTotally ruined

### Table 5.

The WMA work equipment in 2007 and 2017.

### 3.2. Threats facing the Wami Mbiki Wildlife Management Area

The study revealed numerous threats facing the WMA. These include agriculture, settlements, illegal logging and fishing (particularly the use of poisons), charcoal burning, uncontrolled grazing, and bushfires. Also, the wildlife faces unrelenting pressure from poaching, retaliatory killings, and habitat loss. These threats are discussed below:

#### 3.2.1. Uncontrolled cattle grazing

Wami Mbiki was set aside for conservation. Human activity was prohibited in the area. An uncontrolled number of livestock (from within and outside member villages) has caused overgrazing in the area following the end of donor support in 2011. The livestock grazing in the area comes from Arusha and Manyara (Mang’ati and Mbulu tribes), Mwanza and Shinyanga (Sukuma tribe), Kilosa (Maasai tribe), and Kilimanjaro (Pare tribe). Many of these have entered the WMA through Kwamsanja, Mindutulieni, Pongwemsungura, and Bwawani areas. Some pastoralists obtain permits from the village government to enter the WMA. Some villages have registered them as villagers but other villages have denied them registration. Those without a permit force entry and allow their livestock to graze inside the WMA. Regardless of the size of the herd, the village authorities impose a fine of 50,000 TZS. These pastoralists have built settlements and livestock stockades inside the WMA.

Moreover, pastoralists from WMA member villages (Kambala, Mindutulieni, Visakazi, Kaloleni, and Tukamisasa) also graze their cattle in the WMA in drought seasons but do not build stockades (bomas). Due to overgrazing, the potential breeding sites and hiding places for wildlife have been degraded. For instance, one VGS stated “on routine patrol, we have found two impala calves who had been trampled to death by a herd of cattle because the impala fled leaving the calves behind.”

In the process of keeping tsetse flies and dangerous wildlife away, pastoralists use chemicals and burn fires which can cause wild fires. Moreover, they cut down trees to build bomasand settlements and litter the area with plastic bags and bottles. Due to continued degradation, most water pans have dried up. This situation is likely to increase competition for space and resources (food and water) between the livestock and wildlife, resulting in increasing stress for the wildlife. Also, it increases the possibility of poaching, leading to the migratory wildlife escaping to other relatively well-protected areas such as Saadani National Park. Efforts by the VGS to remove pastoralists from the WMA led to attacks on two occasions leaving two VGS severely injured. The expansion of livestock numbers and degraded habitat has discouraged the development of Wami Mbiki WMA as a tourist site since tourists visiting the area see more livestock than wildlife (Interview no. 5, June 2016).

In 2014, with support from KDU and Tanzania Forest Services (TFS), the VGS conducted an operation to remove livestock from the WMA. About 2400 cattle, 125 goats, 76 sheep, and 13 donkeys were removed from the WMA. Using the Mvomero District bylaws, a fine for one cow from WMA member villages was 15,000 TZS (8.7 US$) while non-member village was charged 25,000 TZS (14.5 US$). The Regional Commissioner’s call on WMA invaders to vacate the area by September 1, 2017 appeared to be largely successful.

#### 3.2.2. Farming and settlement

The study revealed that farmers from Kanga and Mziha villages lived inside the WMA before the area was proclaimed a WMA. When protection of the area weakened, people from other villages such as Dihinda (Masimbani), Kunke (Pagani), Kidudwe (Sungwindala), and Mhumbilo invaded the area. They constructed block houses and cattle enclosures (bomas)leading to felling many trees. Due to the presence of large numbers of people living inside the WMA, some political parties, that is, CCM (2010) and CUF, opened branches inside the area (at Kwalubendo and Pagale Forest Reserve) at Kunke Village.

#### 3.2.3. Poaching

The study showed that poaching is a serious issue in the area despite its designation and VGS patrols. In 2008, the VGS retrieved two elephants’ tusks and weapons. The elephant carcasses had been burnt after removal of the ivory so as to destroy evidence. Kikoti [52] also observed poaching signs such as meat racks near Wami River, bullets wounds, trunks cut by snares on four collared elephants, and a burnt elephant skull. It was reported that elephant poachers now not only take the ivory but also collect elephant meat to sell. This renders it impossible to identify the numbers of elephants killed in the area. Two different kinds of poaching occur in the area—commercial (for meat and/or ivory) and subsistence. Commercial poachers mostly kill elephants, hippopotamus, giraffe, buffaloes, hartebeest, and eland using cars or motorcycles, shotguns, and rifles. Subsistence poachers use muzzle loaders, rifles and shotguns, snares, fires, dogs, machetes, torches. and motorcycle horns and sell surplus meat. One respondent stated “Strong light on animals makes them confused and motionless, thus making it easy for poachers to kill them. Through this method, a poacher can kill up to 20 impalas in a day for business purposes. These poachers usually walk on foot or use a bicycle.”The study also showed that some pastoralists who graze livestock in the WMA also poach themselves and/or collaborate with poachers. For instance in 2010, pastoralists killed an elephant at Kwamsanja Village. A study which collared 17 elephants (5 in Saadani NP and 12 in Wami Mbiki WMA) found that 3 of the 12 elephants in the WMA had bullet wounds and 1 had a cut trunk [52]. Among the 24 villages, most poaching is organized from Kunke Village. The meat collected is sold at Madizini (Turiani). One piece of meat can be sold for about 5000 to 7000 TZS (2–3 US$). Meat from one impala can yield 60,000–70,000 TZS (27–31 US$).

Fish are also poached. One VGS stated “in 2014, we caught poachers (men and women) who used insecticide (Thiodan) and dynamite to harvest fish in the Wami River. Many fish died and were spoiled.”Water from the Wami River is used by many people for drinking and cooking. The use of insecticides and dynamite fishing can make water unsafe for human consumption.

Some cases of poaching in the Wami Mbiki WMA are linked with government officials. For instance, the Wami Mbiki Newsletter of June 2009 reported that in 2008 three poachers were arrested with hundreds of kilograms of bush meat carried in a government vehicle. The VGS and WMS face many difficulties dealing with these kinds of cases because the poachers are protected. For instance, one respondent stated “when some notorious poachers are arrested, they get released without any punishment. There are cases when poachers are arrested with all evidence such as guns and wildlife products but after some time they are released without any form of explanations and given back the evidence. After a few days, the same poachers can be found poaching in the same area. This situation makes it very difficult to stop poaching in Wami Mbiki.”The same respondent stated “the current trend of poaching in Wami Mbiki makes the WMA increasingly unlikely to secure an investor.”

#### 3.2.4. Tree cutting

The study revealed overharvesting of trees in the area for firewood (cooking at home, selling, baking bread, and hardening bricks) and construction (houses and toilets). The main tree species used by the community are Acacia melliferaand Spirostachys Africana.Poles and logs from Acacia mellifera(also called black thorn/hook thorn or mkambala) are good for bee hives, building material (termite resistant), domestic uses (pestles), fencing, firewood, fodder, land improvement (nitrogen fixing), and medicine. The Spirostachys Africana(called micharaka) is used because it is not damaged by termites and is thus good for construction of toilets and wood houses.

Tree cutting is undertaken by people from within and outside the WMA. More than 11 cases of the confiscation of illegal logs from the WMA area have been reported. The main destination for logs was Dar es Salaam and Morogoro. Some apprehended culprits were fined, and others were taken to the court. The normal fine for a lorry of more than 3 tones is 1MTZS and a lorry of less than 3 tones is between 500,000 and 700,000 TZS.

The study also showed that the WMA does not have a permit to sell the confiscated logs. One respondent stated: “…seized logs at Pongwekiona, Kwamsanja, and Superdoll (Mtibwa) areas were sold by TFS. The money was deposited with the central government.The same thing happened in other incidents involving logs and charcoal….”The WMA did not receive any share of the revenue even though the trees were harvested in the WMA. This situation created tension and conflict between the Wami Mbiki Society and TFS officials.

#### 3.2.5. Charcoal burning

Charcoal is burnt along the WMA borders and inside the WMA. There is a growing market for charcoal in some WMA member villages, a situation which threatens the existence of the WMA. Most of the charcoal is sold along the Dar es Salaam— Morogoro road. Few of those committing illegal activities in the WMA are caught. For instance, in 2015, there were 20 court cases related to charcoal burning and 8 cases related to wildlife killing/poaching. In 2016, there were few court cases because many of those caught were willing to pay a fine. Presently, 22 motorcycles and 31 bicycles have been confiscated because offenders have failed to pay the fine.

### 3.3. Human/Wildlife conflicts

#### 3.3.1. Crop raiding

The study showed that elephants, impalas, and monkeys are primarily responsible for invading farms. The areas mostly affected are Mwidu, Kwansanja, Makombe, Pongwemsungura, and Diozile villages and Mtibwa Sugar Plantation. The types of crops affected are sugarcane, maize, and banana. Elephants are most destructive because they eat crops and trample over them. In 2015 in Mwidu Village, about 18 acres were destroyed. The elephants’ seasonal movements, expansion of agricultural land, and the proximity of human settlements and agriculture to elephant habitats increase the possibility for crop damage. Large tracts of land for example from Kambala Village have been allocated to sugarcane, a situation that triggers human-wildlife conflicts. The study revealed that the VGS do not respond on time when called in cases of problem wildlife. Due to this, the villagers take matters in their own hands and local hunters kill the offending animal.

#### 3.3.2. Livestock depredation

The study showed that the villages most affected by predators are Mwidu, Tukamisasa, Diozile, Kwamsanja, and Pongwekiona. The most destructive animals are leopard, lion, and hyena. In 2015, at Mwidu Village, two goats were killed by a hyena, and near Pongwemsungura Village, a cow was killed by a lion.

#### 3.3.3. Killing of humans

The study showed that wildlife also kill/injure people in villages adjacent to the Wami Mbiki WMA. For instance, in 2015, hyena injured two people at Maseyu Village. Elephants have also attacked people inside the WMA, especially livestock keepers and poachers. The total number of victims is unknown because most cases of wild animal attacks on human are not reported because it is illegal to enter the WMA without permission. The reasons given for attack were: (a) some people are killed in the process of trying to kill elephants (poaching), (b) some are attacked while grazing livestock in the area, and (c) some are killed because of making a noise that disturbs the elephants. Crocodiles also attack and kill fishermen/women. For instance, in 2016, three pastoralists and two fishermen were killed by crocodiles. In 2015, four pastoralists, two fishermen, and one poacher were killed by crocodiles. Due to frequent attacks from crocodiles, people have ceased to swim in the river.

It is not only the case that wildlife kills people but also humans kill wildlife in retaliation. For instance in 2015, two lions were killed by villagers at Pongwekiona Village.

### 3.4. Factors contributing to poor performance of the Wami Mbiki WMA

#### 3.4.1. Termination of donor funding and lack of a reliable source of income

When donor funding ended in June 2011, the Wami Mbiki WMA was left without any source of income. At this time, no contract for alternative investment had been secured. In 2012, the Wami Mbiki WMA took the initiative to attract investors in photographic tourism and four applications were received. However, before an agreement could be reached, the negotiations failed. The possible reasons for this failure could be the required annual investment fee of TZS 45 million (US$28,125), which was too high considering the low tourism potential and the investment required to develop photographic tourism in the area [44]. Apart from that, the investment agreement was for only for 3 years, which is considered too short a period for an investor to recover their costs. One investor, Safari Legacy, spent about US$300,000 setting up camp between 2008 and 2011. The company discontinued their investment because of the complexity of operating in the WMA which made it impossible to sustain a profitable business [44]. Since 2011, patrol activities in the WMA decreased leading to an increase in illegal activities.

#### 3.4.2. Lack of benefits to local people

A major challenge facing the Wami Mbiki WMA is the ability to generate sufficient benefits for the community to create incentives for them to maintain, manage, and support conservation. There has been no income at household/community level or other benefits from small business (e.g., handicrafts) or other wildlife-related activities. Many respondents felt that the WMA benefits only a few individuals and do not see the importance of keeping it—as one respondent stated “we see no benefits from Wami Mbiki…so it is better for our land to be returned back to us…”WMA records indicate that the WMS collected 689,000 TZS; 1,585,300 TZS; and 2,274,300 TZS in 2004, 2005, and 2006, respectively [53]. Also, interviews show that between 2008 and 2012, some tourists visited the WMA, but now there are none. Some of the revenue collected was distributed to member villages.

#### 3.4.3. Politics

Some political leaders, such as ward councillors, partly contribute to the increase in illegal activities in the WMA because they defend encroachers and people involved in illegal activities. For instance in 2017, the ward councillors for Mtibwa led a demonstration to protest against the dislocation of people from Wami Mbiki (in Pagale Nature Reserve).

#### 3.4.4. Lack of commitment by village leaders

The study showed that village leaders sometimes mislead villagers concerning the formal boundary of the WMA and encourage them to oppose the WMA. This encourages people to continue with illegal activities inside the WMA. Due to this, there has been occasional shifting of the WMA boundary. For instance one respondent stated “The efforts to protect natural resources in the WMA are weakened by many people…leaders, young, and old… people do not like enhanced protection of the WMA so that they can continue with illegal activities…”

#### 3.4.5. Lack of commitment by the village game scouts

The field data showed that most VGS collaborate with poachers and other people who engage in illegal activities inside the WMA. For instance, the WMS leader said “in 2015, a poacher was apprehended with elephant ivory, two guns (rifle and muzzle loader), and a bicycle. …the responsible game scouts employed delaying tactics and released the poacher….”The study also revealed that VGS allow illegal activities inside the WMA (e.g., ruby, rose garnet gemstone extraction, and gold sieving from the Wami River; hunting, etc.) with the intention of receiving financial gain from the perpetrators.

#### 3.4.6. Lack of communication

The study showed that villagers do not receive information and updates from WMS leaders on matters pertaining to the WMA. Since 2011, no meetings have been conducted for village representatives to share information with villagers on the performance of the WMA. The lack of communication between WMS management and local communities has made it difficult to secure full support from local people on conservation issues. The WMS council meetings are primarily financed by revenues from fines.

#### 3.4.7. Mismanagement of WMS properties and double standards

The study showed that in 2015/2016, the WMA in collaboration with KDU, TANAPA (Mikumi, Udzungwa and Sadani NPs), and TFS removed livestock from the WMA. More than 2000 cattle were rounder up, and their owners paid about 37M TZS in fines. Apart from these fines, 8M TZS was collected from seized cars, motorcycles, and apprehended poachers. The revenue was used to pay the VGS, repair a car, and buy food for the VGS. However, there are claims that the WMS mismanaged the money accruing from this exercise.

The study further revealed that there are double standards in deciding the amount of fines, a situation which encourages corruption as one respondent reported: “in 2016, we conducted a joint patrol and confiscated a lorry with charcoal. Instead of paying a set fine of 12Mas, we received 3M …in a similar incident a lorry was charged 1M instead of 7M.”

Since 2002, there have been five changes in WMS leadership. Some leaders were fired due to mismanagement of money and misuse of WMS property. Also, some were accused of showing partiality in handling cases related to illegal activities in the WMA and for defending and protecting those who were illegally harvesting resources in the WMA.

#### 3.4.8. Interests of the facilitator

The DHA interest was to acquire a tourist hunting block for business purpose. This is reflected in the article in WFSA where they stated that an increase in the wildlife populations in the WMA could tolerate controlled hunting “…populations of most game species … can tolerate controlled harvesting through tourist hunting. … but it is of the utmost importance to attain the block allocation as to diversify the economic activities of the WMS” ([54], p 211). However, for ecological reasons, the Ministry of Natural Resources and Tourism (MNRT) revoked user rights for consumptive tourism in the WMA.

#### 3.4.9. Lack of technical personnel

The WMA lacks creative and competent personnel who are able to assist the WMA in business terms to increase income. This situation enforces the dependency of the WMA on fines paid by apprehended poachers and other offenders for its operations.

#### 3.4.10. Conflicts

There have been conflicts among the WMS leaders. Also, there have been cases of VGS being fired without enough evidence, which creates enmity and promotes illegal activities in the WMA. Several meetings have been held to discuss internal conflicts instead of discussing the development of the WMA. There are also conflicts between WMS leaders and government staff (TFS offices in Mvomero and Bagamoyo) in relation to revenue collected from fines and selling confiscated logs. This leads to the lack of cooperation in dealing with illegal activities in the WMA.

### 3.5. People’s perception of the WMA

People perceive the WMA to benefit WMS leaders but not the community. This is because since 2011, they have not received any benefit from the WMA. The villages heard that the WMA received 37 M TZS, but none of this found its way to the local communities. The expenditure of money was not transparent, and the board of trustees was not involved. For different reasons, some villages, for example Mziha, declined to send a representative to the WMS and wished to leave the WMA. Villages like Tukamisasa, Kwamsanja, and Kunke demanded the return of their land so that they could utilize it for agriculture, charcoal burning, etc. Some people were of the opinion that a new donor and/or investor should be sought soon to avoid the complete disappearance of wildlife in the area.

### 3.6. Proposed possible ways to improve the current situation

The community proposed the following so as to improve the current situation:

1. The efforts of the Regional Commissioner, especially those requiring people to vacate the area, together with frequent patrols, are crucial. For instance, the operations conducted in the area reduced the number of cattle in the WMA.

2. Maintenance of roads is important for people to be able to access the area. Currently, the WMA has poor roads and some areas are not accessible by car.

3. The WMA leaders should resolve their differences and work as a team. This is important as it will enhance the success of the WMA.

4. The WMA leadership should use the constitution and regulations to guide WMA operations. The study showed that WMA leaders do not follow procedures on issues pertaining to WMA activities, for example, handling issues related to WMA property and revenue, and hiring and firing WMS staff. Most VGS have been fired in a perfunctory manner without adequate justification. For example, up to 2017, 40 VGS had been fired without any investigation of their behavior. These procedures should be transparent and proper investigation must be undertaken before firing staff.

5. A way should be found for sharing income derived from logs or timber harvested in the WMA. The current situation whereby the TFS takes all the money collected is discouraging. Since the WMA comprises village land and villagers have protected the trees they consider they deserve a share of the proceeds. The money accrued could help pay patrol activities and VGS salaries.

6. WMA leaders should follow the procedures for handling WMA income, for example, depositing money in the bank first before incurring any expenditure. The study showed that money collected from fines has been used without depositing it in the bank. This situation encourages mismanagement of WMA income. Moreover, since periods of office for WMA leaders are relatively short, newly-elected leaders should receive training.

7. The government should give special considerations to the interests of WMA facilitators because experience shows that they have contributed to the success of most WMAs.

8. The government should strengthen the WMA in terms of protection and leadership because it is a guardian of all WMAs.

## 4. Conclusion

The findings of this study showed that following the end of donor support in 2011, almost all activities in the Wami Mbiki WMA ceased. As a result of inadequate protection, the area is severely affected by environmentally unfriendly activities such as poaching, illegal timber harvesting, charcoal burning, overgrazing, and overfishing. The population increase in the area has demanded large tracts of land for agriculture, thereby increasing pressure on the Wami Mbiki WMA. Several factors have been identified that contribute to the poor performance of the WMA. Although the government has tried to improve the situation by removing the livestock inside the area, more effort is still needed to save the remaining wildlife in the area.

## Notes

• The size is given as 63,000 ha (630 km2) by the WMA Authorized Association Consortium (AAC) website (www.twma.co.tz), and 250,000 ha (2500 km2) by the Wami Mbiki Society website (makingithappentz.blogspot.dk).

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© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Sayuni B. Mariki (November 5th 2018). Successes, Threats, and Factors Influencing the Performance of a Community-Based Wildlife Management Approach: The Case of Wami Mbiki WMA, Tanzania, Wildlife Management - Failures, Successes and Prospects, Jafari R. Kideghesho and Alfan A. Rija, IntechOpen, DOI: 10.5772/intechopen.79183. Available from:

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