diff --git a/docs/release-notes.md b/docs/release-notes.md
index c3449ba..e89cbc8 100644
--- a/docs/release-notes.md
+++ b/docs/release-notes.md
@@ -4,6 +4,7 @@
 
 ### Bug Fixes
 - Fix a regression introduced in 0.2.6 where `is_monotonic` was significantly degrading `.sel` performance.
+- Fix `xdas.concat` to gracefully handle empty inputs, preventing errors when selecting out-of-range data from a `DataCollection` (@atrabattoni).
 
 ### Documentation
 - Achieved **100% docstring coverage** (excluding `__magic__` and private `_methods`) (@atrabattoni).
diff --git a/tests/test_datacollection.py b/tests/test_datacollection.py
index d710743..65d6d5f 100644
--- a/tests/test_datacollection.py
+++ b/tests/test_datacollection.py
@@ -409,3 +409,37 @@ def test_sequence_map_invalid_item(self):
         atom = xs.decimate(..., 2, ftype="fir")
         with pytest.raises(TypeError, match="encountered in the collection"):
             ds.map(atom)
+
+    def test_mapping_sel_one_element_becomes_empty(self):
+        da = wavelet_wavefronts()
+        da_near = da.sel(distance=slice(0, 4999))
+        da_far = da.sel(distance=slice(5000, 10000))
+        dc = xd.DataCollection({"near": da_near, "far": da_far}, "instrument")
+        result = dc.sel(distance=slice(0, 2000))
+        assert set(result.keys()) == {"near"}
+        assert not result["near"].empty
+
+    def test_mapping_sel_all_elements_become_empty(self):
+        da = wavelet_wavefronts()
+        da_near = da.sel(distance=slice(0, 4999))
+        da_far = da.sel(distance=slice(5000, 10000))
+        dc = xd.DataCollection({"near": da_near, "far": da_far}, "instrument")
+        result = dc.sel(distance=slice(-1000, -1))
+        assert len(result) == 0
+
+    def test_sequence_sel_one_element_becomes_empty(self):
+        da = wavelet_wavefronts()
+        da_near = da.sel(distance=slice(0, 4999))
+        da_far = da.sel(distance=slice(5000, 10000))
+        dc = xd.DataCollection([da_near, da_far], "instrument")
+        result = dc.sel(distance=slice(0, 2000))
+        assert len(result) == 1
+        assert not result[0].empty
+
+    def test_sequence_sel_all_elements_become_empty(self):
+        da = wavelet_wavefronts()
+        da_near = da.sel(distance=slice(0, 4999))
+        da_far = da.sel(distance=slice(5000, 10000))
+        dc = xd.DataCollection([da_near, da_far], "instrument")
+        result = dc.sel(distance=slice(-1000, -1))
+        assert len(result) == 0
diff --git a/tests/test_routines.py b/tests/test_routines.py
index 3819019..6dc38b6 100644
--- a/tests/test_routines.py
+++ b/tests/test_routines.py
@@ -670,6 +670,31 @@ def test_dim_last(self):
         assert isinstance(result, xd.DataArray)
 
 
+class TestConcatEdgeCases:
+    def test_empty_list_returns_dataarray(self):
+        result = xd.concat([])
+        assert isinstance(result, xd.DataArray)
+        assert result.empty
+
+    def test_all_empty_elements_returns_empty_dataarray(self):
+        da = xd.DataArray(np.zeros((0, 10)), dims=("time", "distance"))
+        result = xd.concat([da, da])
+        assert isinstance(result, xd.DataArray)
+        assert result.empty
+        assert result.dims == ("time", "distance")
+
+    def test_mixed_empty_and_nonempty_uses_nonempty(self):
+        t_empty = np.array([], dtype="datetime64[ns]")
+        da_empty = xd.DataArray(np.zeros((0,)), {"time": t_empty})
+        t = np.array(
+            ["2000-01-01", "2000-01-02", "2000-01-03", "2000-01-04", "2000-01-05"],
+            dtype="datetime64[ns]",
+        )
+        da = xd.DataArray(np.ones((5,)), {"time": t})
+        result = xd.concat([da_empty, da])
+        assert result.equals(da)
+
+
 class TestConcatCoordsEdgeCases:
     def test_tolerance_with_dense_coord_raises(self):
         da1 = xd.DataArray(
diff --git a/xdas/coordinates/interp.py b/xdas/coordinates/interp.py
index 1dc12da..4440166 100644
--- a/xdas/coordinates/interp.py
+++ b/xdas/coordinates/interp.py
@@ -217,7 +217,7 @@ def get_sampling_interval(self, cast=True):
         return delta
 
     def is_monotonic_increasing(self):
-        """Return ``True`` if no segment boundary exhibits a backward jump."""
+        """Return ``True`` if no segment starts before the end of the previous one."""
         return not self.get_split_indices("overlaps", tolerance=False).size
 
     def equals(self, other):
diff --git a/xdas/coordinates/sampled.py b/xdas/coordinates/sampled.py
index 06a9c6f..d05f159 100644
--- a/xdas/coordinates/sampled.py
+++ b/xdas/coordinates/sampled.py
@@ -264,7 +264,7 @@ def get_sampling_interval(self, cast=True):
         return delta
 
     def is_monotonic_increasing(self):
-        """Return ``True`` if no segment starts below the end of the previous one."""
+        """Return ``True`` if no segment starts before the end of the previous one."""
         return not self.get_split_indices("overlaps", tolerance=False).size
 
     def equals(self, other):
diff --git a/xdas/core/routines.py b/xdas/core/routines.py
index 32b0d4f..a058f88 100644
--- a/xdas/core/routines.py
+++ b/xdas/core/routines.py
@@ -942,10 +942,15 @@ def concat(objs, dim="first", tolerance=None, virtual=None, verbose=None):
     Returns
     -------
     DataArray
-        The concatenated dataarray.
+        The concatenated dataarray. Coordinates along axes other than *dim* are
+        taken from the first element; no compatibility check is performed on ``objs[1:]``.
 
     """
-    objs = [da for da in objs if not da.empty]
+    objs = list(objs)
+    non_empty = [da for da in objs if not da.empty]
+    if not non_empty:
+        return objs[0] if objs else DataArray([])
+    objs = non_empty
 
     if virtual is None:
         virtual = all(isinstance(da.data, (VirtualSource, VirtualStack)) for da in objs)
@@ -959,6 +964,7 @@ def concat(objs, dim="first", tolerance=None, virtual=None, verbose=None):
         dims = (dim, *objs[0].dims)
         objs = [da.expand_dims(dim) for da in objs]
 
+    # TODO: check that objs[1:] have the same non-concat coords as objs[0]
     coords = objs[0].coords.drop_dims(dim)
     name = objs[0].name
     attrs = objs[0].attrs