diff --git a/Project.toml b/Project.toml
index 97aedec..3f72b3f 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "NeutralLandscapes"
 uuid = "71847384-8354-4223-ac08-659a5128069f"
 authors = ["Timothée Poisot <timothee.poisot@umontreal.ca>", "Michael Krabbe Borregaard <mkborregaard@sund.ku.dk>", "Michael David Catchen <michael.catchen@mail.mcgill.ca>", "Rafael Schouten <rafaelschouten@gmail.com>", "Virgile Baudrot <virgile.baudrot@posteo.net>"]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
diff --git a/src/updaters/update.jl b/src/updaters/update.jl
index 0434d92..4facf5b 100644
--- a/src/updaters/update.jl
+++ b/src/updaters/update.jl
@@ -41,8 +41,8 @@ and 1. Note that this does not preserve the `rate` parameter for a given
 difference between the total maximum and total minimum across all `mats`.
 """
 function normalize(mats::Vector{M}) where {M<:AbstractMatrix}
-    mins, maxs = findmin.(mats), findmax.(mats)
-    totalmin, totalmax = findmin([x[1] for x in mins])[1], findmax([x[1] for x in maxs])[1]
+    mins, maxs = [NaNMath.min(x...) for x in mats], [NaNMath.max(x...) for x in mats]
+    totalmin, totalmax = NaNMath.min(mins...), NaNMath.max(maxs...)
     returnmats = copy(mats)
     for (i,mat) in enumerate(mats)
         returnmats[i] = (mat .- totalmin) ./ (totalmax - totalmin)
diff --git a/test/updaters.jl b/test/updaters.jl
index 7f51733..8d829f0 100644
--- a/test/updaters.jl
+++ b/test/updaters.jl
@@ -30,7 +30,23 @@ function testupdaters(model)
     @test env != oldenv 
 end 
 
+function testnormalize(model)
+    updater = model()
+    env = rand(MidpointDisplacement(0.5), 50, 50)
+    seq = update(updater, env, 30)
+    normseq = normalize(seq)
+    @test length(findall(isnan, normseq[end])) == 0
+    for m in normseq
+        @test min(m...) >= 0 && max(m...) <= 1
+    end
+
 
+    env = [NaN 5 2 1 NaN; 3 4 5 2 1; 6 NaN 0 5 2; NaN NaN 0 4 5]
+    seq = update(updater, env, 30)
+    normseq = normalize(seq) 
+    @test length(findall(isnan, normseq[end])) == 5
+
+end
 
 models = [
     TemporallyVariableUpdater, 
@@ -38,4 +54,6 @@ models = [
     SpatiotemporallyAutocorrelatedUpdater
 ]
 
+
+testnormalize.(models)
 testupdaters.(models)