Developing political-ecological theory: The need for many-task computing

Models of political-ecological systems can inform policies for managing ecosystems that contain endangered species. To increase the credibility of these models, massive computation is needed to statistically estimate the model’s parameters, compute confidence intervals for these parameters, determine the model’s prediction error rate, and assess its sensitivity to parameter misspecification. To meet this statistical and computational challenge, this article delivers statistical algorithms and a method for constructing ecosystem management plans that are coded as distributed computing applications. These applications can run on cluster computers, the cloud, or a collection of in-house workstations. This downloadable code is used to address the challenge of conserving the East African cheetah (Acinonyx jubatus). This demonstration means that the new standard of credibility that any political-ecological model needs to meet is the one given herein.

I would be happy, however, to further shorten it if it is otherwise found acceptable.
I have also focused the paper on what I believe its key contributions are.
2. In addition, it is recommended that you take note of, and address, comments regarding computational validation presented, and the need for a broader consideration of possible approaches to achieving parallel implementation.

1
The paper now contains additional discussion and results regarding the validity of its computational methods, see lines 805-811. Also, I now point out that at least three alternatives to JavaSpaces exist, see lines 516-528. I make it clear that these alternatives can deliver the parallel computations described in Section 2.
1. In its current form, the manuscript is unpublishable. I say this not unkindly, but constructively. The manuscript reads far more like a thesis, but not one that would be passable. The manuscript is far too long and contains a lot of irrelevant material that obscures its contributions (the important bits). I believe that contributions are there, but they are completely obscured. 2. The emphasis is all wrong. The manuscript is to much front loaded particularly in the introduction and literature review sections. These need to short and sharp and really drive the motivation of the novel contribution of the work. At the moment they are bloated and contain so much discussion that the reader easily forgets what the paper is about. I have replaced all of the lengthy quotes with paraphrasing.
5. Section 1.3: A new algorithm (step-by-step procedure) is added in the literature review section. This would need to go later in the paper.
I have moved the EMT procedure forward to the Materials and Methods section.
6. In general, please make algorithms short with minimal explanation each step, otherwise they become difficult to read. If you need more explanation, provide it in the body of the text.  3. Either the foundational work in Sections 1 and 2 could have been reduced to more tightly focus the paper, or the paper should have been split into two works. If the goal of the work is to provide (and evaluate & justify) a new tool for ecological management, then perhaps it would be better to split the material into (1) a paper that justifies its validity and shows its promise and (2)  4. Re Comments 6/7: The original reviewer's point remains and could be expanded as "Perhaps the search query was too narrow and missed relevant literature". The responses only address the offered example, not the thoroughness of the original search. Re original reviewer comment #12, they have a point. There are now many approaches to achieving parallelism. What they left out was a listing of examples that do support easy deployment of applications across heterogeneous devices, like Docker, which are ignored in in this paper.
I now report that at least three feasible alternatives to JavaSpaces exist, see lines 516-528. There, I note the trade-offs presented by Docker and make my review practical by identifying specific language commands that would be used to develop programs similar in function to the one that I exercise in the case study of Section 3.