ORCID Profile
0000-0002-9594-9264
Current Organisation
University of Tokyo
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Publisher: Cold Spring Harbor Laboratory
Date: 12-05-2017
DOI: 10.1101/137158
Abstract: Spatially-explicit approaches are widely recommended for ecosystem management. The quality of the data, such as presence/absence or habitat maps, affects the management actions recommended, and is, therefore, key to management success. However, available data are often biased and incomplete. Previous studies have advanced ways to resolve data bias and missing data, but questions remain about how we design ecological surveys to develop a dataset through field surveys. Ecological surveys may have multiple spatial scales, including the spatial extent of the target ecosystem (observation window), the resolution for mapping in idual distributions (mapping unit), and the survey area within each mapping unit (s ling unit). We developed an ecological survey method for mapping in idual distributions by applying spatially-explicit stochastic models. We used spatial point processes to describe in idual spatial placements using either random or clustering processes. We then designed ecological surveys with different spatial scales and in idual detectability. We found that the choice of mapping unit affected the presence mapped fraction, and the fraction of the total in iduals covered by the presence mapped patches. Tradeoffs were found between these quantities and the map resolution, associated with equivalent asymptotic behaviors for both metrics at sufficiently small and large mapping unit scales. Our approach enabled consideration of the effect of multiple spatial scales in surveys, and estimation of the survey outcomes such as the presence mapped fraction and the number of in iduals situated in the presence detected units. The developed theory may facilitate management decision-making and inform the design of monitoring and data gathering.
Publisher: Elsevier BV
Date: 09-2018
DOI: 10.1016/J.JTBI.2018.05.013
Abstract: Population abundance is fundamental in ecology and conservation biology, and provides essential information for predicting population dynamics and implementing conservation actions. While a range of approaches have been proposed to estimate population abundance based on existing data, data deficiency is ubiquitous. When information is deficient, a population estimation will rely on labor intensive field surveys. Typically, time is one of the critical constraints in conservation, and management decisions must often be made quickly under a data deficient situation. Hence, it is important to acquire a theoretical justification for survey methods to meet a required estimation precision. There is no such theory available in a spatially explicit context, while spatial considerations are critical to any field survey. Here, we develop a spatially explicit theory for population estimation that allows us to examine the estimation precision under different survey designs and in idual distribution patterns (e.g. random/clustered s ling and in idual distribution). We demonstrate that clustered s ling decreases the estimation precision when in iduals form clusters, while s ling designs do not affect the estimation accuracy when in iduals are distributed randomly. Regardless of in idual distribution, the estimation precision becomes higher with increasing total population abundance and the s led fraction. These insights provide theoretical bases for efficient field survey designs in information deficiency situations.
Publisher: Wiley
Date: 16-08-2019
DOI: 10.1111/COBI.13097
Abstract: Recent increases in ivory poaching have depressed African elephant populations. Successful enforcement has led to ivory stockpiling. Stockpile destruction is becoming increasingly popular, and most destruction has occurred in the last 5 years. Ivory destruction is intended to send a strong message against ivory consumption, both in promoting a taboo on ivory use and catalyzing policy change. However, there has been no effort to establish the distribution and extent of media reporting on ivory destruction events globally. We analyzed media coverage of the largest ivory destruction event in history (Kenya, 30 April 2016) across 11 nation states connected to ivory trade. We used an online-media crawling tool to search online media outlets and subjected 5 of the largest print newspapers (by circulation) in 5 nations of interest to content analysis. Most online news on the ivory burn came from the United States (81% of 1944 articles), whereas most of the print news articles came from Kenya (61% of 157 articles). Eighty-six to 97% of all online articles reported the burn as a positive conservation action, whereas 4-50% discussed ivory burning as having a negative impact on elephant conservation. Most articles discussed law enforcement and trade bans as effective for elephant conservation. There was more relative search interest globally in the 2016 Kenyan ivory burn than any other burn in 5 years. Ours is the first attempt to track the reach of media coverage relative to an ivory burn and provides a case study in tracking the effects of a conservation-marketing event.
Publisher: Elsevier BV
Date: 09-2017
Publisher: Wiley
Date: 07-12-2022
DOI: 10.1111/CSP2.12857
Abstract: Conservation needs adequate support and funding to address our ecological crises. People support conservation in different ways, from social media engagement to donating money. Various factors influence how people choose to support conservation, including social norms and ecological status. The rise of social media has provided people with an easy and low‐cost way to support conservation: sharing information online. How valuable is social media engagement and activism for conservation funding and outcomes? Here, we develop an evolutionary game‐theoretic framework to understand the complex interactions between in iduals in the context of social media information sharing, conservation philanthropy, and how these interactions ultimately impact ecological outcomes. From a game theory perspective, we can consider donors to be hard‐cooperators, sharers of information on social media to be soft‐cooperators, and those who do nothing to be non‐cooperators. Our model shows that soft‐cooperators can help stabilize conservation funding flows and develop social norms. Supporting conservation through social media sharing can ultimately contribute to conservation success. Our study conceptualizes the complex decision‐making processes of conservation funding and affirms the importance and value of mobilizing all types of supporters in conservation.
Publisher: Cold Spring Harbor Laboratory
Date: 26-04-2017
DOI: 10.1101/131037
Abstract: The abundance of species is a fundamental consideration in ecology and conservation biology. Although broad models have been proposed to estimate the population abundance using existing data, available data is often limited. With no information available, a population estimation will rely on time consuming field surveys. Typically, time is a critical constraint in conservation and often management decisions must be made quickly under the data limited situation. Depending on time and budgetary constraints, the required accuracy of field survey changes significantly. Hence, it is desirable to set up an effective survey design to minimize time and effort of s ling given required accuracy. We examine a spatially-explicit approach to population estimation using spatial point processes, enabling us to explicitly and consistently discuss various s ling designs. We find that the accuracy of abundance estimation varies with both ecological factors and survey design. Although the spatial scale of s ling does not affect estimation accuracy when the underlying in idual distribution is random, it decreases with the s led unit size if in iduals tend to form clusters. These results are derived analytically and checked numerically. Obtained insights provide a benchmark to predict the quality of population estimation, and improve survey designs for ecological studies and conservation.
Publisher: Springer Science and Business Media LLC
Date: 11-12-2018
No related grants have been discovered for Nao Takashina.