Peer review of: Blind spots in global soil biodiversity and ecosystem function research (2021)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
This study provides an overview on potential knowledge gaps in soil biodiversity 
and ecosystem functioning. As the authors acknowledge, the majority of the 
studies available in the literature merely focus on microbes, and there is an 
overall lack of research studies dealing with the temporal variability of many 
other soil organisms across many soil types, land covers, and biomes. However, 
the manuscript does not provide enough novel information to make a significant 
progress that could increase this understanding. Overall, I found the study to be 
very descriptive and lacking more in-depth analyses of the data extracted from 
the literature. For example, I would have expected to see (from what we have) 
whether it is possible to find any meaningful patterns in soil biodiversity and 
ecosystem function at global scales. This would have allowed a more critical and 
detailed outcome. 
 
General comments: 
 
The fact that studies dealing with soil biodiversity and ecosystem functioning at 
large scales are a relative recent research field, the selection of the studies 
appears to be strongly biased and not properly justified. For example, due the 
scanty number of macroecological studies it would have been useful to also 
include those individual studies focusing at national levels. In addition, using 1-
3 studies to make conclusions about metazoans and four soil functions 
(according to Table 2 in the methods) is not appropriate. In fact, the maps 
provided in Figs. S4 are misleading because if I am right, the authors only 
included one study to draw the maps of Collembolans (Fig. S2a/g), nutrient 
cycling (Fig. S2b/c) and water infiltration (Fig. S2b/d). In addition, also 
according to Table 2 in the methods section, the same study (e.g., 151 and 
153) have been used to draw different maps. 
 
In the abstract, the authors claim that > 11,000 sampling sites were included, 
but the actual analyses (and therefore the conclusions) are only based on 45 
studies. According to the text, the initial number of sites (11,065) consisted of 
7,631 sites reporting soil biodiversity data and 3,497 sites with information on 
soil functions (L131-133). Did all these sampled sites were obtained from just 
45 studies (L757-758)? In L168 it is stated in that 63 sites contained both types 
of information, should not they be presented to the reader in a map? This would 
have given a more clear idea of where this type of information is concentrated. 

And, did all the soil biodiversity sites have information on several soil organisms 
or just specific groups? 
 
I am not very convinced that data are mostly absent from most tropical areas 
(L102) when one of the first international initiatives Tropical Soil Biology and 
Fertility Programme in the 80s was focused on that particular biome. I was also 
surprised to see that The International Biological Program (IBP), an effort 
between 1964 and 1974 to coordinate large-scale ecological and environmental 
studies, was not even mentioned. It is also surprising that one charismatic 
group of tropical systems, termites, were not included or mentioned in the 
paper. And what about all the soil atlases produced by FAO, USDA and ESDAC 
that provide abundant soil data? 
 
In addition to these large scales projects, there are currently several databases 
that continuously archive soil organisms and/or soil data, such as Edaphobase, 
DriloBase, Collembola database, etc. Therefore, I would have expected that the 
first effort should be the incorporation of all this information in a study that 
intends to identify knowledge gaps. In addition, before we care about 
macroecological gaps, should we not aim for a better knowledge of soil 
biodiversity when it has been stated that we only know a small fraction (e.g. in 
the macroecological study by Decäens 2010)? 
 
More specific comments: 
 
In several parts of the text there is an overemphasis of the described findings; 
for example, the use of the term “significant” is misleading when no statistical 
tests have been applied to the data reported. 
 
Some kind of description/justification is needed to explain how the class 
intervals for each of the variables depicted in Fig. 2 were established. Were they 
based on a literature survey or on a specific criterion? Also in this multi-panel 
figure, Fig. 2n clearly shows that urban areas are overrepresented, what does 
this mean in terms of number of studies analysed? How can you be sure that 
climatic, soil and above-ground variables are the main determinants of edaphic 
life and not anthropogenic disturbances? 
 
The same can be said for the other charts, how many studies reported these 
values? In several of these charts, 20 intervals were established, meaning that 
2 studies were represented in each one… Also units for Figs. 2f-n? Vascular 
plant richness is also included to describe “global soil ecological blind spots” 
(Fig. 2m), but in several parts of the text it is stated that no links between 
above- and below-ground biodiversity has been found, so which are the reasons 
behind using this metric as potential influential factor explaining knowledge 
gaps in soil biodiversity and ecosystem functioning? 
 
I do agree that lack of standardized protocols hinders our understanding, so 
how was this solved in this study when compiling the data from the different 
studies? For example, measuring C content by loss of ignition, dichromate-
oxidation method, etc. could render different results, as well as different 
methods to extract soil biota. And what about the use of different soil 
classifications when plotting soil types? 
 
A justification is also needed to explain the reasons behind combining just three 
variables when trying to assess which environmental characteristics are used in 
macroecological studies (Fig. 3). Since that according to Fig. 2 and the 
explanations given in the text, soil carbon, land cover are biased, should it not 
be better to illustrate the combination of variables for which we have good 
coverage? Why was not soil type included? This information is usually available 
in many published soil atlases… 
 
I like the overview of the main obstacles that soil ecologists face when trying to 
produce/complete soil surveys and that has been summarised in Table 1. In my 
opinion, scientific challenges are also important. Despite the authors trying to 
convince the reader that data sharing and making data available to be re-used 
again could be the solution to decrease the number of knowledge gaps, I feel 
that this is only one side of the story. Scientists from around the world need to 
publish their findings to progress in their careers and/or to obtain research 
funding. Managing large data sets, having access to global databases on 
climatic and soil information is often a privilege for rich research teams (in 
terms of bibliographic subscriptions, computing power and technical knowledge, 
and graphical software). The text in L365-371 gives the impression that “data 
mobilisation” should be a priority and that by embracing open access and 
connecting the global soil community, we could fulfil all those missing 
knowledge gaps. However, due the current taxonomic deficit for soil biota, the 
priority should be to have more national (and local) surveys to increase the soil 
biodiversity information across a large number of sites and to a deeper 
taxonomical level. Global research projects (L359) would be ideal but unrealistic 
in many practical terms. 
 
Should not the authors acknowledge the authors who helped when obtained the 
locations of the sampled sites? 
 
This is an interesting study that could attract many potential readers if it could 
provide a clearer message and quantitative analyses (including statistical tests 
and not just maps) of the available data. 
 
 
 
Reviewer #2: 
Remarks to the Author: 
The manuscript from Guerra et al. “Blind spots in global soil biodiversity and 
ecosystem function research” represents to me a very interesting contribution 
of outstanding usefulness for future research on global soil biodiversity and 
functions. The topic is highly relevant to the global environmental context and 
the need for humanity to secure the production of goods and services from 
healthy ecosystems and sustainable agrosystems. It is highly strategic as it 
aims at identifying gaps in our knowledge, not only on a geographical basis, but 
also on an environmental basis, i.e. identifying blind points in our knowledge in 
terms of environmental categories that have been under-explored in the 
scientific research dedicated to soil biodiversity and soil ecological functions. 
The approach is sound, and there is no doubt that, once published, it will 
became a reference for justifying more studies on soil biodiversity and functions 
in specific areas of the world, and a basis to fill the gaps in our knowledge in 
this research area. 
 
The paper is globally written in a very understandable way. Methods are 
relevant to the question, even if I have some minor points I would like the 
author to consider for clarification. The discussion is sound and justified by the 
results of the meta-analysis in its first two sections (2.1. “Biogeographical 
biases” and 2.2 “2.2. Ecological blind spots”), then move to a very interesting 
third section that discuss the main constraints soil ecological research is 
currently facing and proposes some solution to bypass them (2.3 “Challenges to 
move beyond blind spots”). 
 
Here is a list of minor comments and recommendations: 
 
- Lines 102-103: I am not sure to understand correctly this sentence. Do you 
mean fungi and bacteria have been the focus of the main taxonomic research 
efforts dedicated to soil biota? I am not sure this is the case, and soil micro-
organisms in general are probably concerned by a very high taxonomic deficit, 
even in temperate areas (see for instance the figure with taxonomic deficit by 
main taxa of soil organisms, and related to the average body-mass in Decaëns 
et al. 2010). 
- Line 131: what do you mean here by “individual sampling site”? This should 
represent different spatial scales across studies and focal groups of soil 
organisms or ecosystem functions. In the method section, lines 763-767 no 
additional information is given regarding this point. 
- Line 723-735: I would have expected to see termites specifically included in 
the keywords. This is a quite important group of soil ecosystem engineer, 
involved in a number of key ecosystem functions especially in the tropics (but 
not exclusively), and a number of studies on global patterns of termite 
biodiversity have been already published (e.g. Eggleton 2000, Eggleton et al. 
1994). 
- Figure 2: “Values (y-axis) correspond to the percentage of sites per study per 
class when compared with the global proportional distribution of each class 
within each variable defining soil ecosystems”… This is not very easy to follow. 
Could you explain this in a more simple way? 
- Figure 2, what are the individual data units in this figure? From the legend I 
understand that these are “studies”, but in this case how can you calculate the 
% of under/over-representation individually at the study scale? The method 
section is useless to respond to this question, and this important figure 
absolutely has to be self-understandable. 
- Figure 2, it would probably also be interesting to check the representation of 
each major biome, and of the different latitudinal bands. This is addressed in 
Figure S3, but in a different way, and it would certainly be interesting to 
highlight here the bias in available data towards temperate areas. This could be 
integrated into Figure 2 or could represent a separate figure integrated to 
section 2.1. 
- Still in Figure 2, I wonder if the categorization of land covers is really relevant. 
What are “lichens and mosses” representing in a land cover classification? Also, 
are you sure of this over-representation of urban areas or could this be an 
artefact of geo-coordinate approximations? Explain the meaning of “mosaic 
(crops)” and “mosaic (forests)”. 
- In the text, you refer to Figure 2 to point blind spots (poorly covered 
environmental categories) and hot spots (environmental categories over-
represented in macroecological literature) in soil biodiversity/function 
knowledge. However I am not sure that you mention in any part of the 
manuscript the threshold above which you will consider the % of 
representativeness to be different from zero (representation of an 
environmental category in macroecological literature proportional to its 
representation in the real world). Is this a hundred %, or more, or less? This 
should be specified, justified and could also be represented in Figure 2 by two 
horizontal dotted lines (one above and the other one bellow the zero line) that 
would help to visualise which boxplots represent a significant trend towards 
over or under-representation. 
- Lines 256-263: I suspect that most of the trends illustrated in Figure 2 
(especially with regard to climate coverage) can be explained by a latitudinal 
gradient, which is detectable in Figure 1b-c, but not explicitly identified in the 
manuscript (see my previous comment recommending the illustration of the 
latitudinal gradient and/or main biomes in Figure 2). In tropical areas, many 
other reasons for a lack of research on soil biodiversity/function can be 
advocated: lack of available support and infrastructure for soil research, huge 
taxonomic deficit on tropical biota, which impairs efficient and repeatable soil 
biodiversity surveys, etc… 
- Figure 3: what are represented by the pie charts on the right side of the 
figures? I do not understand the different percentages indicated in these… 
- Fig. S1: in the figure legend “soil mentions” instead of “soi mentions” 
- Fig. S2a: Could you specify the number of studies (or individual sampling 
sites) represented in each map? It seems strange that you have no more data 
for e.g. collembolan and acari. 
 
References 
Decaëns T (2010) Macroecological patterns in soil communities. Global Ecology 
and Biogeography. 
Eggleton P (2000) Global patterns of termite diversity. In: Termites: evolution, 
sociality, symbioses, ecology; Springer. 
Eggleton P, Williams PH, Gaston KJ (1994) Explaining global termite diversity: 
productivity or history? Biodiversity & Conservation. 
 
 
 
Reviewer #3: 
Remarks to the Author: 
The study by Guerra and collaborators, entitled “Blind spots in global soil 
biodiversity and ecosystem function research” compiled the location of ~11K 
soil studies, some characterizing soil biodiversity, some ecosystem functions, 
and few both. The authors then proceed to map these studies, and to identify 
the density of studies across areas and categories of soil properties (“blind 
spots”). Finally, authors suggest the creating of a network of soil research to 
share soil data and coordinate sampling in areas of poor knowledge. 

I enjoyed reading the manuscript, which is well written. I’m not a soil ecologist, 
and had no prior knowledge on the state-of-art of coverage of soil sampling 
worldwide. 
 
However, I have a concern regarding an underlying assumption of the study: all 
regions require the same number (or density) of samples to characterize the 
biodiversity or ecosystem functions in the region. Although the authors do not 
state the assumption explicitly, inferring blind spots based on the absolute 
count (or density) of soil samples assumes that (1) soil biodiversity and 
ecosystem functions are evenly distributed across space, therefore (2) studies 
should be evenly distributed. In addition, the assumption is not only limited to 
regions (area), but also to the categories of environmental properties. For 
example, the authors claim that soils in areas of low plant diversity (Fig. 2m), 
extremely cold (Fig. 2j) and extremely dry (Fig. 2k) are poorly studied, relative 
to the frequency of those categories across the world. 
 
Again, I’m not a soil ecologist, but I this assumption is most likely unrealistic. 
The number of studies necessary to characterize the biodiversity should be 
proportional to the local biodiversity, and not evenly distributed across space. In 
other words, if the goal is to characterize biodiversity, then sampling the soil in 
areas of lowest plant richness, lowest temperature and lowest precipitation may 
be a waste of time and resources, as these areas are likely to contribute little to 
soil biodiversity and ecosystem functions. So, here I assume the exact opposite 
of what the authors have assumed: regions of highest biodiversity should 
concentrate most studies, and extreme environments are likely to harbor lowest 
biodiversity (at least for aboveground terrestrial biodiversity). 
 
The unrealistic assumption of the study emerges from use of relative 
frequencies (densities, such as number of studies within 1-degree grid cell) of 
studies as an indication of knowledge. In fact, modern methods to estimate 
biodiversity assume that one should contrast known biodiversity (e.g. species 
inventories) against estimated/expected biodiversity (inferred from previous 
studies). Thus, regions/environments of poor biodiversity should need lower 
sampling effort than regions/environments of high biodiversity. In other words, 
is very likely that biodiversity in regions of extremely low temperature, low 
precipitation, high aridity and low plant richness is best described than other 
regions, despite the fewer number of samples. So, it is not necessarily true that 
blind spots are in regions of low number of samples, as the most sampled 
regions may need even sampling effort to characterize the local soil biodiversity.  
Knowledge gaps (i.e. “blind spots”, sensu Guerra and collaborators) are better 
identified using estimates of Completeness/Coverage (e.g.: Anne Chao and Lou 
Jost 2012. Coverage-based rarefaction and extrapolation: standardizing 
samples by completeness rather than size. Ecology 93:2533-2547), which use 
the “novelty” of each new sample to infer how (in)complete the description of 
biodiversity is. Thus, I would recommend using such completeness estimators 
to identify the “blind spots” in soil biodiversity, rather than pure density of 
number of soil samples. 
 
Thiago F. Rangel 
Federal University of Goiás, Brazil